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The Globular Star Clusters of the Andromeda Galaxy (Iop Concise Physics) [Concise ed.]
 1643277472, 9781643277479

Table of contents :
PRELIMS.pdf
Preface
Acknowledgments
Author biography
Charli M Sakari
CH001.pdf
Chapter 1 The Andromeda Galaxy
1.1 An introduction to Messier 31, the Andromeda Galaxy
1.1.1 M31 and its neighbors
1.1.2 M31 as a test of cosmological models
1.2 Observations of M31
1.2.1 Photometry
1.2.2 Spectroscopy
1.2.3 Photometry versus spectroscopy
1.2.4 Surveys of M31
1.3 M31’s globular cluster system
References
CH002.pdf
Chapter 2 Globular clusters in the Milky Way
2.1 An introduction to globular star clusters
2.2 Observations of Milky Way globular clusters
2.2.1 Photometry of GCs
2.2.2 Spectroscopy of GCs
2.3 Scientific lessons from Milky Way GCs
2.3.1 GC numbers and masses
2.3.2 Metallicities and kinematics
2.3.3 Ages
2.3.4 Chemical evolution and tagging
2.3.5 Multiple populations
2.4 Summary: Milky Way GCs
References
CH003.pdf
Chapter 3 The inner halo/disk/bulge clusters
3.1 Inner versus outer clusters
3.2 Integrated light observations of distant systems
3.3 A Census of M31 GCs
3.4 The young clusters
3.5 The intermediate-age clusters
3.6 The old clusters
3.6.1 Metallicities
3.6.2 Ages
3.6.3 Masses
3.6.4 Kinematics
3.6.5 Calcium abundances
3.7 Summary and a comparison with Milky Way GCs
References
CH004.pdf
Chapter 4 The outer halo clusters
4.1 The outer halo
4.2 The contents of the outer halo
4.3 The outer halo GC system
4.3.1 Locations and brightnesses
4.3.2 Metallicities and ages
4.3.3 Kinematics
4.3.4 Calcium abundances
4.3.5 Specific frequencies
4.4 Associations with specific streams
4.4.1 The giant stellar stream
4.4.2 The southwest cloud
4.4.3 The eastern cloud
4.4.4 The northwest stream
4.4.5 Streams C and D
4.4.6 The GCs without streams
4.4.7 M33 and its GCs
4.5 Summary: the nature of the outer halo
References
CH005.pdf
Chapter 5 Multiple populations in M31 GCs
5.1 Multiple populations
5.2 Lessons and theory from resolved GCs
5.2.1 A definition of ‘multiple populations’ from observations
5.2.2 The proposed formation scenarios for multiple populations
5.2.3 Open problems with the multiple populations scenarios
5.2.4 The role of M31 GCs in understanding multiple populations
5.3 Multiple populations in M31 GCs
5.3.1 Inferring the presence of multiple populations from IL
5.3.2 Trends with cluster properties
5.3.3 Perspectives on the mass budget problem
5.3.4 Summary: light element spreads in M31 GCs
5.4 The iron-complex GCs
5.4.1 Suspected iron-complex M31 GCs
5.4.2 Comparisons with Milky Way GCs
5.4.3 Multiple populations in M31 iron-complex GCs
5.4.4 Summary: M31 iron-complex GCs
References
CH006.pdf
Chapter 6 M31 and beyond
6.1 Important results from M31 clusters
6.2 Connections with other galaxies
6.3 The future
References

Citation preview

The Globular Star Clusters of the Andromeda Galaxy

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari San Francisco State University, San Francisco, California, USA

Morgan & Claypool Publishers

Copyright ª 2019 Morgan & Claypool Publishers All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher, or as expressly permitted by law or under terms agreed with the appropriate rights organization. Multiple copying is permitted in accordance with the terms of licences issued by the Copyright Licensing Agency, the Copyright Clearance Centre and other reproduction rights organizations. Rights & Permissions To obtain permission to re-use copyrighted material from Morgan & Claypool Publishers, please contact [email protected]. Multimedia content is available for this book from http://iopscience.iop.org/book/978-1-64327-750-9. ISBN ISBN ISBN ISBN ISBN

978-1-64327-750-9 978-1-64327-747-9 978-1-64327-752-3 978-0-7503-3023-7 978-1-64327-748-6

(ebook) (print) (myPrint) (PoD) (mobi)

DOI 10.1088/2053-2571/ab39de Version: 20191201 IOP Concise Physics ISSN 2053-2571 (online) ISSN 2054-7307 (print) A Morgan & Claypool publication as part of IOP Concise Physics Published by Morgan & Claypool Publishers, 1210 Fifth Avenue, Suite 250, San Rafael, CA, 94901, USA IOP Publishing, Temple Circus, Temple Way, Bristol BS1 6HG, UK

To Ben.

Contents Preface

x

Acknowledgments

xi

Author biography

xii

1

The Andromeda Galaxy

1-1

1.1

An introduction to Messier 31, the Andromeda Galaxy 1.1.1 M31 and its neighbors 1.1.2 M31 as a test of cosmological models Observations of M31 1.2.1 Photometry 1.2.2 Spectroscopy 1.2.3 Photometry versus spectroscopy 1.2.4 Surveys of M31 M31’s globular cluster system References

1.2

1.3

2

Globular clusters in the Milky Way

2.1 2.2

An introduction to globular star clusters Observations of Milky Way globular clusters 2.2.1 Photometry of GCs 2.2.2 Spectroscopy of GCs Scientific lessons from Milky Way GCs 2.3.1 GC numbers and masses 2.3.2 Metallicities and kinematics 2.3.3 Ages 2.3.4 Chemical evolution and tagging 2.3.5 Multiple populations Summary: Milky Way GCs References

2.3

2.4

1-1 1-2 1-5 1-6 1-6 1-7 1-8 1-9 1-10 1-11 2-1 2-1 2-3 2-3 2-6 2-10 2-10 2-11 2-13 2-15 2-17 2-19 2-20

3

The inner halo/disk/bulge clusters

3-1

3.1 3.2 3.3

Inner versus outer clusters Integrated light observations of distant systems A Census of M31 GCs

3-1 3-2 3-4

vii

The Globular Star Clusters of the Andromeda Galaxy

3.4 3.5 3.6

3.7

The young clusters The intermediate-age clusters The old clusters 3.6.1 Metallicities 3.6.2 Ages 3.6.3 Masses 3.6.4 Kinematics 3.6.5 Calcium abundances Summary and a comparison with Milky Way GCs References

3-8 3-12 3-13 3-13 3-17 3-19 3-19 3-21 3-25 3-27

4

The outer halo clusters

4.1 4.2 4.3

The outer halo The contents of the outer halo The outer halo GC system 4.3.1 Locations and brightnesses 4.3.2 Metallicities and ages 4.3.3 Kinematics 4.3.4 Calcium abundances 4.3.5 Specific frequencies Associations with specific streams 4.4.1 The giant stellar stream 4.4.2 The southwest cloud 4.4.3 The eastern cloud 4.4.4 The northwest stream 4.4.5 Streams C and D 4.4.6 The GCs without streams 4.4.7 M33 and its GCs Summary: the nature of the outer halo References

4-1 4-2 4-5 4-5 4-8 4-11 4-13 4-13 4-15 4-15 4-18 4-20 4-20 4-21 4-22 4-23 4-23 4-26

5

Multiple populations in M31 GCs

5-1

5.1 5.2

Multiple populations Lessons and theory from resolved GCs 5.2.1 A definition of ‘multiple populations’ from observations 5.2.2 The proposed formation scenarios for multiple populations 5.2.3 Open problems with the multiple populations scenarios

5-1 5-2 5-2 5-5 5-9

4.4

4.5

4-1

viii

The Globular Star Clusters of the Andromeda Galaxy

5.3

5.4

5.2.4 The role of M31 GCs in understanding multiple populations Multiple populations in M31 GCs 5.3.1 Inferring the presence of multiple populations from IL 5.3.2 Trends with cluster properties 5.3.3 Perspectives on the mass budget problem 5.3.4 Summary: light element spreads in M31 GCs The iron-complex GCs 5.4.1 Suspected iron-complex M31 GCs 5.4.2 Comparisons with Milky Way GCs 5.4.3 Multiple populations in M31 iron-complex GCs 5.4.4 Summary: M31 iron-complex GCs References

5-11 5-11 5-11 5-13 5-16 5-17 5-17 5-18 5-19 5-19 5-20 5-20

6

M31 and beyond

6-1

6.1 6.2 6.3

Important results from M31 clusters Connections with other galaxies The future References

6-1 6-3 6-4 6-4

ix

Preface This book presents a brief compilation of results from nearly a century of research on the globular star clusters in the Andromeda Galaxy (M31). This is not intended to be a thorough review; instead, it is intended to explore the techniques and limitations of the observations, the successes and challenges of the models, and the paradigm for the formation of M31 that has gradually emerged. These results will eventually be superseded by new data, better analysis techniques, and more complex models. However, the emphasis of this book is really on the techniques, thought processes, and connections with other studies. This book is intended to be a review of M31 globular cluster research for a nonexpert audience. I have tried to aim the book at a level for undergraduates who have taken a basic astronomy course; at times, some background knowledge is needed to fully understand various concepts. For example, I discuss stellar evolution in brief terms, but do not provide a full description of various evolutionary stages. Students who wish to gain a more thorough background in astronomy and physics before (or while) reading this text may wish to consult another source, such as an introductory astronomy textbook. There are several particular areas that are necessarily very incomplete in this book, both due to space limitations and because I did not want to overwhelm the reader with extensive citations. As an observer, I have naturally focused on the observations of M31 clusters. I have not provided an exhaustive list of the observations of M31 GCs, particularly those surveys that occurred throughout the 1980s, 1990s, and early 2000s. I have also only discussed the field stars in M31 as a complement to the discussions of the globular clusters, although there are many other valuable results from the M31 field stars. While I have mentioned models occasionally, I have not done justice to the intricacies or challenges of modeling. Similarly, the globular clusters of the Milky Way have formed the subject of many publications, including many books; the content provided here has been selected to complement the discussions of the M31 clusters. Finally, I have chosen not to provide a complete list of references for the sake of the target reader; however, I have noted throughout the text that the references are not complete. I have provided learning goals at the beginning of each chapter to guide the reading. I will also provide supplementary discussion questions online. It is my hope that these questions will help the reader to think critically about the application of the Scientific Method to these data.

x

Acknowledgments I would like to thank several people for contributing figures or data that were used for this book, including Nelson Caldwell, Robert Gendler, Ryan Leaman, and Ricardo Schiavon. I have of course benefitted from all the excellent observations and modeling of M31 that has been done over the years, particularly the work of the Pan-Andromeda Archaeological Survey (PAndAS). I would also like to thank everyone who has made their data publicly available. Thank you to Susanne Filler for approaching me about writing this book. I would also like to thank my post-doctoral supervisor, George Wallerstein, for his support. I also thank Velda Arnaud and Benjamin Gerard for their continuing encouragement and proofreading.

xi

Author biography Charli M Sakari Charli M Sakari is an Assistant Professor in the Physics and Astronomy Department at San Francisco State University. Originally from Springfield, OR, Dr Sakari attended Whitman College in Walla Walla, WA, graduating cum laude with a BA in Physics-Astronomy and Applied Mathematics, with honors in Physics-Astronomy. She then completed her PhD at the University of Victoria in Victoria, BC, Canada, where she was a Vanier Scholar. Her PhD thesis was titled ‘Chemical Abundances of Local Group Globular Clusters’. Dr Sakari then completed her post-doctoral research at the University of Washington, in Seattle. Dr Sakariʼs research interests include chemical abundances of stars in globular clusters and galaxy field stars, including metal-poor stars. She is also interested in stellar evolution, nucleosynthesis (the creation of the elements), and galaxy formation and evolution.

xii

IOP Concise Physics

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 1 The Andromeda Galaxy

Learning goals After completing this chapter, readers will be able to: • List some similarities and differences between the Milky Way and the Andromeda Galaxy (M31). • Explain how observations of M31 are useful for testing cosmological models of the Universe and galaxy assembly. • Compare and contrast the two general types of observations that astronomers use to study M31.

1.1 An introduction to Messier 31, the Andromeda Galaxy The Andromeda Galaxy, also known as Messier 31 (M31), is the closest large neighbor to our own Milky Way Galaxy. It is one of only a few galaxies that can be seen with the naked eye (i.e. without a telescope), along with the Milky Way itself and the Large and Small Magellanic Clouds. Because it is so close and bright, M31 has been observed for centuries, even before it was seen through a telescope. In the 18th century, Charles Messier listed it as the 31st object in his now famous catalog of bright, fuzzy objects [33]. Since then, the development of increasingly better telescopes and instrumentation has resolved M31 from a fuzzy blob into a complex system of stars, gas, and dust (see figure 1.1). It is now known that M31 is a gravitationally-bound group of stars known as a galaxy. More specifically, M31 is a spiral galaxy, like the Milky Way. Images of M31 show an inclined disk (by about 77° from face on; [8]), with spiral arms made of dust lanes, gaseous nebulae, old and young stars, and star clusters. In addition to stars and gas, the central regions of M31—the bulge or nucleus—contain a supermassive black hole (e.g., [2]). Though it is not immediately obvious from figure 1.1, a more diffuse, extended stellar halo surrounds the entire galaxy out to

doi:10.1088/2053-2571/ab39dech1

1-1

ª Morgan & Claypool Publishers 2019

The Globular Star Clusters of the Andromeda Galaxy

Figure 1.1. A visible light image of the inner regions of M31, taken by Robert Gendler, and reproduced by permission of Robert Gendler. (Note that although the image is aligned with the disk, M31 is actually oriented in a north-west/south-east direction with respect to the celestial equator.) The image is a combination of spacebased and ground-based imaging; the pink image shows hydrogen (H-α) emission from star forming regions. The bulge, disk, and halo of M31 are labeled. The boxes show the satellite galaxies M32 (below the disk) and NGC 205 (above the disk). The positions of some of the brightest globular star clusters are shown with red circles (see chapter 3).

very large distances (>100 kpc; see figure 1.2). The distribution of stars is not smooth, particularly in the outer halo; the streams and arcs of stars which are particularly evident in figure 1.2 are the result of low-mass dwarf galaxies that are being shredded as they fall into the more massive galaxy. Observations of M31 can therefore shed light on its assembly, both past and present. This book will examine the assembly and star formation history of M31 through the observations of its star clusters. First, however, the basic properties of M31 and its satellite galaxies are summarized (section 1.1.1) along with their general use for testing scientific theories (section 1.1.2). The different types of observations, as well as several large surveys dedicated to studies of M31, are described in section 1.2. The system of globular star clusters in M31 is finally introduced in section 1.3, along with an outline for the subsequent chapters in this volume. 1.1.1 M31 and its neighbors M31 and the Milky Way are the most massive galaxies in the Local Group of Galaxies. M31 was one of the first galaxies to be identified as a separate, distinct entity from the Milky Way through observations of its variable stars [20]. Modern observations have demonstrated that M31 is 783 ± 25 kpc1 [31] away, moving toward the Milky Way; in ∼4–5 billion years, the two galaxies will have their first encounter [41], eventually leading to a merger. 1

1 kpc = 1000 pc, where 1 pc is 3.26 ly.

1-2

The Globular Star Clusters of the Andromeda Galaxy

Figure 1.2. An image from McConnachie et al. [30] showing the density distribution of stars in the outer regions of M31 and its neighboring galaxy, M33. The solid white lines show the extent of the observations. The magenta dashed circles show projected distances of 50, 100, and 150 kpc from the center of M31 and 50 kpc from the center of M33. The black ellipses show the extent and orientation of the disks of M31 and M33. This image highlights the number of dwarf galaxies and stellar streams that are present in M31’s outer halo. M33 is visible in the lower left, while NGC 147 and 185 are visible at the top. Copyright AAS, reproduced with permission.

M31 also has a number of lower mass dwarf galaxies orbiting around it, some of which are actively being eaten up, or accreted, by the larger galaxy. Figure 1.3 shows a mass comparison of these satellite galaxies. The most massive satellite of M31 is the spiral galaxy Messier 33, which lies to the south of M31 (see figure 1.2). Despite its current location >200 kpc from the center of M31, M33 could have orbited much more closely to M31 in the past. Debates currently exist as to whether M33 has previously passed by M31, or whether it is on its first infall (e.g., [11, 41]). If the two galaxies have interacted in the past, the consequences of the gravitational effects should still be observable today (see chapters 3, 4, and 6). The other relatively massive satellite galaxies are M32 and NGC 205, both of which are visible in images of the inner regions of M31 (figure 1.1). M32 is a bright, compact elliptical [28] near M31’s disk, while NGC 205 is a dwarf elliptical galaxy to the north of M31’s disk ([34]; note the different appearance of the two galaxies in figure 1.1). Although the two galaxies currently exist in a similar environment close to M31’s disk, M32’s compactness indicates that it has had a different history from NGC 205. It is possible that NGC 205 may be on its way into M31 for the first 1-3

The Globular Star Clusters of the Andromeda Galaxy

Figure 1.3. Pie chart from McConnachie et al. [30] showing the contribution of individual galaxies to the total mass budget of M31’s satellites. Copyright AAS, reproduced with permission.

time [18], while M32 has had a long history of interactions with M31. Indeed, one proposed formation mechanism for compact ellipticals like M32 is an interaction with a more massive galaxy, during which the outer stars are stripped from the smaller galaxy. Under this framework, some of the stars that are now present in M31 may have formed in M32 ([11]; though see other papers, e.g., [10]). The resulting gravitational interaction may also lead to perturbations in M31’s disk, such as rings or warps [5], which would be observable today. The next most massive galaxies are NGC 147 and NGC 185, two dwarf spheroidal galaxies further to the north of M31 ([16, 17]; see figure 1.2). These two dwarfs appear to be associated with each other, i.e., they may be binary galaxies. Comparisons with models suggest that their proximity to each other and their similar motions through space are unlikely to be random [13]. The models also suggest that these two galaxies (possibly along with a third, less massive dwarf) may have had a previous interaction with M31 (e.g., [1]). In addition to these more massive dwarf galaxies, there are about 30 more intact galaxies surrounding M31 (see the review by McConnachie et al. [30]). Roughly half of M31’s satellites appear to be in a rotating plane [23]—this has important consequences for the formation of these satellites, as will be discussed in subsequent chapters. Figure 1.2 also shows a number of streams and arcs of stars surrounding M31; this substructure is stellar debris from shredded (accreted) dwarf galaxies [29, 30]. The most prominent stream, the Giant Stellar Stream (GSS) [22], lies to the South. Models of this stream (e.g., [12]) suggest that this stream was created by a fairly 1-4

The Globular Star Clusters of the Andromeda Galaxy

massive galaxy (∼109.5 M⊙, about 3 billion times more massive than the Sun). Recently, D’Souza & Bell [11] have suggested that the GSS was created by M32 (the compact elliptical below M31’s disk). If this theory is correct, M32’s progenitor could have been as massive as 25 billion M⊙, making it the third largest galaxy in the Local Group of galaxies. Other bright, coherent streams in the outer regions of M31 have also been named and modeled, and are thought to come from the recent accretion of fairly massive dwarf galaxies, as will be discussed in subsequent chapters. In general, stellar streams dissolve and become fainter over time as the stars become part of their new host galaxy. Bright streams are therefore likely to be from fairly recent accretion events, within the last few billion years. McConnachie et al. [30] find that most of the stars in the outer halo are found in ‘amorphous substructure’, where the stars seem to be clumped together but are not part of an obvious, coherent stream. The stars in the amorphous substructure could be from fainter dwarf galaxies (which do not have as may stars to create bright streams) or older accretion events (whose streams have dissolved in the larger halo and are now virtually undetectable). About a third to a quarter of the outer halo stars are in a ‘smooth’ component, with no obvious substructure, and may reflect ancient accretion events. The ‘M31 system’ is therefore more than just the single spiral galaxy in figure 1.1—it is a complex system that is actively changing over time. As this book will demonstrate, the number, types, and properties of the dwarf galaxies surrounding M31, both the surviving ones and those that were long ago disrupted, will be essential for understanding M31 in a cosmological context and for testing models of the Universe. 1.1.2 M31 as a test of cosmological models Under the current paradigm, 69% of the Universe is in the form of dark energy (represented by a cosmological constant, Λ), 26% is Cold Dark Matter (CDM), and all other matter (i.e. protons and neutrons) accounts for only 5% [37]. Simulations of ΛCDM universes (e.g., [38, 39]) suggest that large galaxies form through ongoing mergers of smaller dark matter subhaloes. This framework predicts that there will be many more low mass subhaloes than massive haloes; assuming that these dark matter systems will have gas and star formation, ΛCDM therefore predicts that there should be more dwarf galaxies than massive galaxies in the Universe which is exactly what is observed around M31. However, more precise details, such as the exact numbers, masses, and properties of the dwarf galaxies, provide specific constraints for physical models of the Universe. For example, Oman et al. [35] compare the masses and rotation speeds of the observed dwarf galaxies to simulations, directly testing predictions from ΛCDM. M31 is therefore a useful test for theories of the Universe, galaxy formation, and galaxy evolution, particularly when compared to the Milky Way. Although the Milky Way can be studied in much better detail (since its stars are closer than distant galaxies), parts of the Milky Way (e.g., the inner regions) are difficult to study because of the Sun’s location in the disk and the resulting intervening stars, gas, and 1-5

The Globular Star Clusters of the Andromeda Galaxy

dust. From an observer’s perspective on Earth, the Milky Way also covers the entire sky, making it more difficult to observe the entire Galaxy in a homogeneous way. M31 and other external galaxies offer the advantage of providing a more holistic view. Furthermore, the Milky Way is only a single galaxy, one whose formation and evolutionary history may not be representative of all spiral galaxies, much less of other types of galaxies in very different environments. At first glance, M31 and the Milky Way seem fairly similar: both are spiral galaxies with roughly similar masses (e.g., [26, 43]; but note that there is still some uncertainty as to which galaxy is the more massive). Despite these similarities, the two galaxies seem to have had different star formation histories, both in the galaxies themselves [3, 45] and in their satellite galaxies [44], which suggests they have had different assembly histories. These similarities and differences will be important in understanding the details of galaxy assembly in the Local Group of galaxies and, ultimately, in a cosmological context, but require high quality observations of M31 to test these theories (e.g., [13]).

1.2 Observations of M31 For many astronomers, the only available tool for studying astronomical objects is electromagnetic radiation, or light. Astronomers therefore have to manipulate light in various ways to take maximal advantage of the information present in the incoming photons. The two most common types of astronomical observations are photometry and spectroscopy—both involve collecting light from astronomical objects, but the techniques differ slightly in how the information is recorded.2 These concepts will be explained more in chapter 2, particularly in how they are utilized to study stars and star clusters, but they are briefly introduced below. 1.2.1 Photometry Loosely speaking, photometry is the process of taking images of astronomical objects to measure their brightness (i.e. counting the number of photons that hit the dectector). Brighter objects will produce more photons than fainter objects, and will therefore appear brighter in images. In practice, this involves many calibration steps (e.g., to attenuate noise from the detectors) and requires knowledge of the wavelength of the observations. Photometry is typically conducted with filters that define the central wavelength and coverage of the observations (see figure 1.4). These filters are crucial because the relative brightness of stars can change with wavelength. For example, a hot star will appear brightest at blue wavelengths, while a cool star will appear brightest at red wavelengths; even if the hot star is brighter in total luminosity than the cool star, it may be fainter in red filters. Photometric observations are complicated by the fact that a star’s brightness also changes with distance, foreground extinction from dust, composition, age, etc. Ultimately, however, by making measurements in different filters, photometry can provide 2 Other ways of manipulating light, such as polarimetry, are not discussed here, nor are other techniques that do not utilize electromagnetic radiation, such as studies of meteorites or neutrino detections.

1-6

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Figure 1.4. Sample spectra of dwarf stars from the Pickles atlas [36]. Stars with three different spectral types are shown: B1V (purple, T≈ 22 000 K), G2V (blue, T≈ 5800 K), and K5V (cyan, T≈ 4200 K). Also shown are the curves for the Johnson–Bessel filters [4]; note that these curves illustrate the transmission of light, rather than flux.

insight into the physical properties of stars, particulary for star clusters (see chapter 2). Photometry also provides information about the locations of stars, enabling identifications of new galaxies or star clusters from clustering analyses. Repeated observations over time can reveal how stars move through space and if their brightness varies over time. 1.2.2 Spectroscopy Spectroscopy also involves collecting light from an astronomical object, but instead of creating an image, the light is dispersed (spread out) into different wavelengths, creating a spectrum. The benefit of this observational technique is that it reveals the details of an object’s spectral energy distribution, including spectral lines.3 Objects like stars produce a blackbody spectrum; this means that stars radiate light at all wavelengths, with the brightness distribution peaking at a color that depends on its temperature (blue stars are hotter than red stars). In observed spectra, dark absorption lines are present on top of the blackbody spectrum—these dark bands occur where atoms in the stellar atmosphere remove (or absorb) incoming energy from the deeper layers of the star. This absorption occurs at specific wavelengths in the spectrum. Because of the Doppler effect, the observed spectral lines shift around slightly as a star moves relative to the Earth. Comparing the wavelengths of lines in observed spectra with the known rest-frame wavelengths enables a star’s radial velocity to be calculated. Combined with other measurements of distance and proper motion, these radial velocities reveal the motion of an object through space. 3 Though there are many uses for spectroscopy (including for targeting astronomical objects other than stars), this book will focus on chemical abundances and velocities.

1-7

The Globular Star Clusters of the Andromeda Galaxy

Once a stellar spectrum has been corrected for its radial velocity, the presence of spectral lines at specific wavelengths reveals the atoms that are present in the star’s atmosphere. Furthermore, the strengths of these lines reveal the abundance of that element in the stellar atmosphere (though note that the strength and presence of spectral lines is also dictated by many other factors, such as the star’s temperature, brightness, etc.). For example, the strong spectral lines at 5172 and 5183 Å4 are caused by magnesium (Mg); stars with lots of Mg will generally have stronger Mg lines than those with scarce amounts of Mg. These measurements reveal the presentday chemical abundances of stars, which are powerful probes of the environment in which the stars formed billions of years ago. Stars form in clouds of gas and dust, and their subsequent chemical composition is generally dictated by the composition of their birth environment (with some exceptions from evolutionary effects). In the early Universe, soon after the Big Bang, the first stars to form should have been composed only of hydrogen (H), helium (He), and trace amounts of lithium and beryllium ([7]; though note that the first stars have never been observed). Over time, as stars form, evolve, and die, they enrich the gas around them, polluting a galaxy’s interstellar medium with more heavy elements. This process of chemical evolution within a galaxy is dependent on several factors, including the mass of the galaxy; chemical evolution will proceed differently between dwarf galaxies and massive galaxies like the Milky Way. Stellar spectroscopy, which can probe the chemical composition of a star, therefore provides insight into the conditions of a star’s birth environment, as described in chapter 2. One technical factor to consider for spectroscopic observations is resolution. The resolution of an image describes how well two objects (e.g., two nearby stars) can be distinguished from each other. Similarly, the resolution of a spectrum describes how well two nearby spectral lines can be separated. A very high-resolution spectrum spreads the light out more, enabling nearby absorption lines to be separated; in a low-resolution spectrum the lines are generally blended together. While it may seem as though a high-resolution spectrum would also be preferable to a low-resolution spectrum, it actually requires more observing time to obtain a suitable highresolution spectrum. For many objects, particularly faint objects, there is a tradeoff between resolution and signal-to-noise (S/N) ratio.5 The decision of which resolution to use for an observing program is often based on the science goals. This is a particularly important distinction for M31, whose stars are much further away (and therefore appear fainter) than Milky Way field stars. 1.2.3 Photometry versus spectroscopy In reality, photometry and spectroscopy are not that different—both record the (relative or absolute) brightness of objects at different wavelengths. In a sense, photometry is similar to very low resolution spectroscopy; the wavelength coverage 1 Å = 10−10 m The S/N ratio quantifies the amount of noise in an image or a spectrum of a target with a specific signal. A S/N of 0 would indicate that there is no signal, while a S/N of 100 would indicate that the signal is 100 times stronger than the noise. 4 5

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of photometric filters can even be narrowed to cover specific spectral lines. There are strengths and weaknesses for each type of observation. One general principle is that higher resolution spectroscopy requires more observing time than lower resolution spectroscopy. Similarly, narrow-band photometry and lower resolution spectroscopy require more observing time than broadband photometry. Narrower filters and higher spectral resolution both require more photons to achieve the same S/N ratio as broadband photometry and lower-resolution spectroscopy. In the former case, this is because fewer photons make it through a narrow-band filter in a given amount of time; in the latter case, it is because fewer photons make it into each resolution element. The choice of observing type is tied to the science goals and the specific instrument being used. If an observer is hoping to characterize large numbers of stars relatively quickly, e.g., to identify clumps of stars or investigate the relative magnitudes within a large sample of stars, then photometry is the better choice. If the goal is to obtain abundances of many elements for a smaller sample of stars, high-resolution spectroscopy is required. Beyond these general decisions, the differences between observation type can be quite subtle. For instance, in some cases it may be possible to determine the rough metallicity6 of an object from photometry; a metallicity can often be determined from moderate-resolution spectroscopy; and high-resolution spectroscopy will enable abundances of individual elements. The ultimate choice will likely rest on the required amount of valuable telescope time. 1.2.4 Surveys of M31 As mentioned in section 1.1, M31 has been observed for centuries. The 20th century brought a significant increase in the numbers and quality of observations, particularly due to the ability to photographically record observations, resolve individual stars, and perform detailed scientific analyses. Some of this work will be discussed in subsequent chapters. The 21st century, however, has given rise to large surveys dedicated to obtaining high-quality, complete coverage of various parts of the M31 system. Because these surveys have been revolutionary for understanding M31 and its satellite galaxies, and because they will heavily impact the discussions of M31 in subsequent chapters, they are briefly introduced here. The Panchromatic Hubble Andromeda Treasury (PHAT; Dalcanton et al. 2012 [9]): PHAT was a Hubble Space Telescope deep photometric survey of about a third of M31’s disk and its central region. This deep imaging survey was able to obtain high-quality photometry of individual M31 stars, including much fainter stars than had previously been observed. PHAT observed M31 in six different filters, from the near-ultraviolet to the near-infrared. This wide photometric coverage provides constraints on the spectral energy distributions of stars and clusters. PHAT’s deep data set enabled identification of new star clusters [25], characterizations of the ages and metallicities of 6 Astronomers often refer to all elements heavier than helium as metals. The metallicity of an object therefore refers to how enriched a star is in heavy elements.

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field stars [15], determinations of M31’s star formation history [45, 46], and much more. The Spectroscopic and Photometric Landscape of Andromeda’s Stellar Halo (SPLASH; e.g., Kalirai et al. 2006 [27]): this survey utilized photometry and moderate-resolution spectroscopy to study several fields of M31 and its dwarf satellites, offering the possibility to investigate changes in M31’s stellar populations with increasing distance from the center. SPLASH has characterized the nature of M31’s stellar halo [27], identified tidal streams (e.g., [14]), and characterized the nature of several dwarf satellites [40, 42]. The Pan-Andromeda Archaeological Survey (PAndAS; McConnachie et al. 2009 [32]): PAndAS was a deep photometric survey that focused on the outer regions of M31, out to a projected distance of 150 kpc (and including the nearby galaxy M33). These deep observations and wide area coverage yielded discoveries of a vast number of new satellite galaxies, star clusters, and coherent stellar streams in M31’s outer halo ([21, 24, 29, 30]; see figure 1.2). The locations, densities, and metallicities derived from this photometry provide insight into the ongoing assembly of M31’s outer halo and the nature of the dwarfs that are being accreted. The results from this survey will be discussed further in chapter 4. In addition to these large surveys, other groups have focused more specifically on the star clusters in M31. These surveys will be discussed throughout subsequent chapters.

1.3 M31’s globular cluster system In 1932, based on photometric observations, Hubble reported the presence of 140 ‘nebulous objects’ distributed around M31 [19]. He wrote that ‘their numbers and their spherical distribution suggest that the objects are associated with the great spiral itself’ rather than the Milky Way. This suggestion was supported by a spectroscopic radial velocity measurement, which showed that one object had a similar velocity as the M31 galaxy itself. Hubble argued that ‘on the basis of structure, luminosity, diameters, and colors, the objects are provisionally identified as globular clusters’. Globular clusters (GCs), dense clusters of hundreds of thousands to a million stars, were already well known in the Milky Way. Although GCs comprise a very small part of a galaxy’s mass, they have been incredibly useful in understanding the properties of a wide variety of galaxies (see, e.g., [6]). The properties of a GC system are strongly correlated with the properties of its host galaxy, suggesting a) that GC formation is an important part of galaxy formation, and b) that GCs trace the assembly and formation histories of their host galaxies. Since Hubble’s 1932 paper, observations of M31’s GCs have yielded a vast amount of information about the GC system and M31’s star formation and assembly histories as a whole. These clusters will be the subject of this book, 1-10

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particularly the information they reveal about the assembly history of M31. In chapter 2, the general properties of GCs are summarized, considering both what photometry and spectroscopy of GCs reveal and what has been learned from the GCs in the Milky Way. Chapter 3 then discusses the limitations of observational techniques in applications to the distant M31 GCs and explores the results from GCs in the inner regions of M31. Chapter 4 examines the GCs in the outer halo. The nature of M31’s GCs (specifically the signatures of multiple populations) is discussed in chapter 5. Finally, the findings are summarized in chapter 6, along with comparisons to more distant galaxies and the possibilities for future studies of the formation and evolution of M31.

References [1] Arias V, Guglielmo M, Fernando N, et al. 2016 Mon. Not. R. Astron. Soc. 456 1654 [2] Bender R, Kormendy J, Bower G, et al. 2005 Astrophys. J. 631 280 [3] Bernard E J, Ferguson A M N, Chapman S C, et al. 2015 Mon. Not. R. Astron. Soc. 453 L113 [4] Bessell M S 1990 Publ. Astron. Soc. Pac. 102 1181 [5] Block D L, Bournaud F, Combes F, et al. 2006 Nature 443 832 [6] Brodie J P and Strader J 2006 Annu. Rev. Astron. Astrophys. 44 193 [7] Coc A and Vangioni E 2017 Int. J. Mod. Phys. E 26 1741002 [8] Courteau S, Widrow L M, McDonald M, et al. 2011 Astrophys. J. 739 20 [9] Dalcanton J J, Williams B F, Lang D, et al. 2012 Astrophys. J Suppl. Ser. 200 18 [10] Dierickx M, Blecha L and Loeb A 2014 Astrophys. J. 788 L38 [11] D’Souza R and Bell E F 2018 Nat. Astron. 2 737 [12] Fardal M A, Babul A, Geehan J J, et al. 2006 Mon. Not. R. Astron. Soc. 366 1012 [13] Fattahi A, Navarro J F, Starkenburg E, et al. 2013 Mon. Not. R. Astron. Soc. 431 L73 [14] Gilbert K M, Fardal M, Kalirai J S, et al. 2007 Astrophys. J. 668 245 [15] Gregersen D, Seth A C, Williams B F, et al. 2015 Astron. J. 150 189 [16] Herschel J F W 1833 Philos. Trans. Roy. Soc. Lond. Ser. I 123 359 [17] Herschel W 1789 Philos. Trans. Roy. Soc. Lond. Ser. I 79 212 [18] Howley K M, Geha M, Guhathakurta P, et al. 2008 Astrophys. J. 683 722 [19] Hubble E 1932 Astrophys. J. 76 44 [20] Hubble E P 1929 Astrophys. J. 69 103 [21] Huxor A P, Mackey A D, Ferguson A M N, et al. 2014 Mon. Not. R. Astron. Soc. 442 2165 [22] Ibata R, Irwin M, Lewis G, et al. 2001 Nature 412 49 [23] Ibata R A, Lewis G F, Conn A R, et al. 2013 Nature 493 62 [24] Ibata R A, Lewis G F, McConnachie A W, et al. 2014 Astrophys. J. 780 128 [25] Johnson L C, Seth A C, Dalcanton J J, et al. 2015 Astrophys. J. 802 127 [26] Kafle P R, Sharma S, Lewis G F, et al. 2018 Mon. Not. R. Astron. Soc. 475 4043 [27] Kalirai J S, Gilbert K M, Guhathakurta P, et al. 2006 Astrophys. J. 648 389 [28] Legentil G 1755 Sav. étrangers, Vol. II 137 [29] Mackey A D, Ferguson A M N, Huxor A P, et al. 2019 Mon. Not. R. Astron. Soc. 484 1756 [30] McConnachie A W, Ibata R, Martin N, et al. 2018 Astrophys. J. 868 55 [31] McConnachie A W, Irwin M J, Ferguson A M N, et al. 2005 Mon. Not. R. Astron. Soc. 356 979 [32] McConnachie A W, Irwin M J, Ibata R A, et al. 2009 Nature 461 66

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[33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46]

Messier C 1774 Mémoires de laAcademie Royale des Sciences: 1771 435 Messier C 1798 Connaissance des Tems 1801 434 Oman K A, Navarro J F, Sales L V, et al. 2016 Mon. Not. R. Astron. Soc. 460 3610 Pickles A J 1998 Publ. Astron. Soc. Pac. 110 863 Planck Collaboration, Aghanim N, Akrami Y, et al. 2018 arXiv e-prints arXiv: 1807.06209 Schaye J, Crain R A, Bower R G, et al. 2015 Mon. Not. R. Astron. Soc. 446 521 Springel V, Wang J, Vogelsberger M, et al. 2008 Mon. Not. R. Astron. Soc. 391 1685 Tollerud E J, Beaton R L, Geha M C, et al. 2012 Astrophys. J. 752 45 van der Marel R P, Fardal M A, Sohn S T, et al. 2019 Astrophys. J. 872 24 Vargas L C, Geha M C and Tollerud E J 2014 Astrophys. J. 790 73 Watkins L L, Evans N W and An J H 2010 Mon. Not. R. Astron. Soc. 406 264 Weisz D R, Skillman E D, Hidalgo S L, et al. 2014 Astrophys. J. 789 24 Williams B F, Dalcanton J J, Dolphin A E, et al. 2015 Astrophys. J. 806 48 Williams B F, Dolphin A E, Dalcanton J J, et al. 2017 Astrophys. J. 846 145

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IOP Concise Physics

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 2 Globular clusters in the Milky Way

Learning goals After completing this chapter, readers will be able to: • Describe what globular clusters (GCs) are and how they differ from other star clusters. • Explain what photometric and spectroscopic observations of resolved systems have shown about GCs. • Discuss what observations of Milky Way GCs have revealed about the Milky Way’s assembly history.

2.1 An introduction to globular star clusters In the Milky Way, GCs can be studied in exquisite detail because of their proximity to Earth. Figure 2.1 shows a Hubble Space Telescope image of the Milky Way GC Messier 15 (M15). In appearance, M15 is a prototypical Milky Way GC: it is a centrally concentrated, dense blob of old stars that are more metal-poor than the Sun. Most Milky Way GCs are similarly massive, centrally concentrated, metalpoor, and old (e.g., [77]). However, the last few decades have revolutionized the standard views of GCs, largely thanks to high-quality observations in the Milky Way and its nearest dwarf satellites. Star clusters come in a variety of masses, ages, and chemical compositions. It is not trivial to define exactly what makes a cluster of stars a ‘GC’; however, one of the most important distinguishing characteristics is the total cluster mass. Historical observations within the Milky Way found that the high-mass GCs were distinct from the lower-mass open clusters. The Milky Way GCs were generally thought to be massive, centrally concentrated, old, and associated with the Milky Way halo, while the open clusters were thought to be lower mass, sparse, young, primarily metal-rich, and associated with the Milky Way disk. In recent years, the definition of a GC has become murkier as observations have identified clusters that violate this classic dichotomy. In the Milky Way, there are several clusters whose masses lie between doi:10.1088/2053-2571/ab39dech2

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Figure 2.1. A Hubble Space Telescope image of the Milky Way GC, M15 (image credit: NASA, ESA).

typical open clusters and GCs; these clusters sometimes also have intermediate ages (∼5 Gyr;1 e.g., [67]). Older open clusters are unlikely to exist in the Milky Way, as they should have been broken up long ago by the gravitational influence of the Milky Way (models have shown that lower-mass clusters are easier to disrupt than massive GCs). The nature of these unclassifiable Milky Way clusters is still unknown. There are also a number of clusters in the Large Magellanic Cloud (LMC; a massive dwarf satellite of the Milky Way) that look like GCs, i.e., bright, centrally concentrated, and massive, but are much younger than the classical Milky Way GCs (e.g., [20]). These LMC clusters seem to suggest that GCs may not always be old—however, it is unknown if these clusters will resemble the Milky Way GCs after billions of years of evolution. Ultimately, the former distinction between globular and open clusters is no longer quite so clear cut, though there may be important chemical differences between the two types of clusters (see Section 2.3.5). Future chapters will occasionally discuss the low-mass clusters; however, the primary focus is on the higher mass clusters. At the high-mass end, a precise definition of a ‘GC’ also remains elusive. Very high-mass GCs have stellar masses similar to low-mass galaxies; however, GCs have historically been considered to be distinct from galaxies, primarily because, unlike galaxies, there is no evidence that GCs contain their own dark matter. The discovery of new types of galaxies in extragalactic systems, e.g., ultracompact dwarf galaxies and nuclear star clusters at the centers of galaxies, suggests 1

1 Gyr=109 yr.

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that a distinction between a GC and a galaxy is not always straightforward (see, e.g., [4]). Even in the Milky Way, it is not entirely clear whether some objects, such as the cluster ω Centauri (hereafter ω Cen), can truly be considered classical GCs, nuclear remnants of galaxies, or some combination of the two. Again, chemical abundances may shed some light on this distinction, as will be discussed in chapter 5. Regardless of how they are defined, GCs are intimately connected to the field stars2 in their host galaxies. GC populations are a common feature in all but the lowest mass galaxies, indicating that massive cluster formation may be a natural outcome during periods of intense star formation. After billions of years of evolution, however, these GCs are located far from their birth sites. For example, Milky Way GCs are found primarily in the halo (though some are also located in the disk and central bulge; e.g., [45]), though they likely did not form there—identifying where they originated and how they traveled into the present-day halo will reveal how the larger Milky Way Galaxy has assembled over time. As will be discussed in section 2.3.4, some Milky Way GCs have likely been accreted from dwarf satellite galaxies during mergers—the most obvious evidence for the accretion of GCs from dwarfs comes from the shredded Sagittarius dwarf spheroidal galaxy, which has several GCs lying along its stellar streams, moving with the main body of the galaxy [38]. Like the field stars, GCs can therefore be used to unravel the assembly histories of their host galaxies, ultimately providing important observational constraints for cosmological models of the Universe.

2.2 Observations of Milky Way globular clusters 2.2.1 Photometry of GCs As discussed in chapter 1, photometric observations measure the brightness of objects with filters that only allow specific wavelengths of light to pass through. One way to utilize photometric observations of a GC is to make a color-magnitude diagram (CMD), where a star’s apparent magnitude in one filter (e.g., the visual V band) is plotted against its color, the difference between the magnitudes in two different filters (e.g., the difference between the visual and the near-infrared magnitudes, or V − I). A CMD is similar to a Hertzprung–Russell Diagram,3 except that observational quantities are plotted instead of temperature and brightness. Section 1.2.1 described how the observed brightness of a star depends on many factors, including its intrinsic brightness, its distance, the amount of intervening interstellar dust, etc., all of which make it difficult to interpret observational quantities in physically meaningful ways. However, for photometry, GCs provide several advantages over field stars: 1. Stars within a GC are all at (roughly) the same distance from the Earth,4 removing the distance uncertainty in interpreting observed magnitudes. In 2

Fields stars are stars in a galaxy that are not in star clusters. The Sun is an example of a Milky Way field star. Readers who are unfamiliar with HR Diagrams and stellar evolution may wish to review an introductory astronomy textbook before proceeding with this chapter. 4 The distance of a GC is much greater than the physical extent of the GC. 3

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other words, if a star within one GC appears brighter than another star in the same cluster, it is because that star is intrinsically brighter than the other. GC photometry therefore provides indications of relative brightness without having to know the distance to the stars.5 Of course, there will still be some amount of contamination in the CMD from intervening foreground stars, and it may not be obvious if the stars in a CMD are truly cluster members. Most GCs in the Milky Way halo have little field star contamination because there are fewer stars along the line of sight compared to, e.g., sightlines through the disk or bulge. Similarly, because they lie at the same distance, most stars within a GC have similar amounts of reddening due to intervening dust. This is not always true—some GCs are affected by differential reddening, where the dust density varies across the face of the cluster. However, significant differential reddening is not common, and is generally only seen in GCs that are viewed through dense regions like the Milky Way’s disk or bulge. 2. Even after its distance is known, a star’s position in a CMD depends on its mass, age, chemical composition, and more. GCs contain stars with a range of masses, which removes that level of uncertainty from CMD analyses. This means that the distribution of GC stars in a CMD can be used to determine the age and metallicity of that cluster. Galaxies also contain stars with a wide range of masses; however, the stellar populations in galaxies can be quite complex, with large age and metallicity spreads. Compared to a galaxy like the Milky Way, GCs are simpler stellar populations. If the Milky Way GCs have age spreads, they must be very small. Similarly, though all GCs are now known to have star-to-star abundance spreads in light elements (e.g., [7]), most do not have significant metallicity spreads. GCs are therefore simple enough that interpretation of their CMDs is easier than for galaxies. It is also generally difficult to obtain ages for field stars. However, in GCs the location of the main sequence turnoff directly reveals the cluster age. GCs therefore offer a rare opportunity to obtain high-quality ages, as discussed in section 2.3.3. 3. GCs contain tens of thousands to a million stars, and are generally centrally concentrated. As an ensemble, they are brighter than their individual stars, and can be detected and observed at greater distances (the same holds for spectroscopy). This is an important point for observations of distant GCs and galaxies. With these points in mind, figure 2.2 shows a CMD of a Milky Way GC, 47 Tucanae (47 Tuc), based on Hubble Space Telescope data from the ACS Survey of Galactic Globular Clusters [68]. The distribution of cluster stars in a CMD is not random; instead, the stars are clumped into distinct groups based on mass/evolutionary state. Recall that higher mass stars evolve faster than lower mass stars. The lowest

5

Note that distances can also be derived from CMDs.

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Figure 2.2. A Color-Magnitude Diagram of the Milky Way GC 47 Tuc (grey points), using the Hubble Space Telescope photometry from the ACS Survey of Galactic Globular Clusters [68]. The apparent visual magnitude, V, is plotted against the V−I color, the difference between the visual and near-infrared magnitudes. Remember that brighter stars have smaller magnitudes; stars at the top of the plot are brighter, while those at the bottom are fainter. Similarly, stars at the left end of the plot are bluer (and hotter), while those at the right end are redder (and cooler). Also shown are Teramo isochrone models [59]; the models have been shifted to the distance of 47 Tuc [22]. Left: isochrones with a fixed metallicity ([Fe/H] = −0.70 ) and varying ages (from 1 to 14.0 Gyr). Right: isochrones at a fixed age (12 Gyr) and varying metallicities (from [Fe/H] = −2.27 to +0.26). Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

mass GC stars occupy the hydrogen-burning main sequence, while those of slightly higher mass have exhausted hydrogen in their cores and started to ascend the red giant branch (RGB). The slightly higher mass stars have started to burn helium and settled onto the horizontal branch; the more massive stars remaining in GCs have exhausted helium in their cores and have moved onto the asymptotic giant branch. The highest mass GC stars have long since evolved and died. The physics of these evolutionary states are well understood enough to create stellar evolution models over a wide variety of stellar masses, chemical compositions, and more. Figure 2.2 shows isochrones, models that show how a population of stars with the same age, but varying stellar masses, would populate a CMD, and how these isochrones change with age (in Gyr) and metallicity (in [M/H]).6 For this set of isochrones (from the Teramo group; [59]), 6

The logarithmic quantity [M/H] describes the overall metal-content of a star, relative to the Sun. The Sun, by definition, has [M/H] = 0 . Negative quantities mean the star has less metals than the Sun; a star with [M/H] = −1 has ten times fewer metals (i.e., 10−1 = 0.1 times the Solar value). The ‘overall metal content’ is easier to define in models than it is to determine observationally. Observers typically use iron to represent the metallicity, and quote the [Fe/H] value. Note that the [Fe/H] ratio is usually not equal to the [M/H] ratio.

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47 Tuc is best fit with an age of 12 Gyr and a metallicity of [M/H] = −0.35 [77]. Note that there are also other ways to determine the relative ages of resolved GCs (e.g., [77]). The cluster 47 Tuc is a fairly well-behaved, well-populated, nearby GC. The proximity of 47 Tuc ensures that even its faintest stars can be observed to high precision. GCs with significant metallicity spreads will necessarily be harder to interpret (see chapter 5). CMDs of sparse, lower mass GCs are also difficult to interpret, as they are more sensitive to field star contamination and may not have enough stars for a confident age or metallicity determination (see [68] for several examples). Differential reddening can also complicate CMD analyses. More distant GCs become increasingly difficult to analyze for observational reasons, as discussed in section 3.2. 2.2.2 Spectroscopy of GCs Spectroscopy of GC stars is generally fairly similar to spectroscopy of field stars, with a few subtle differences. Radial velocities The stars within a GC are gravitationally bound to one another and are moving together through space with the same net motion. The individual stars do not all have identical line-of-sight velocities, however, as the cluster has a dispersion about the mean velocity. This velocity dispersion, σ, generally increases with cluster mass; a fairly normal cluster like 47 Tuc has σ = 11 km/s, while the most massive Milky Way GC, ω Cen, has σ = 16.8 km/s [22]. These values are lower than the velocity dispersions of massive galaxies, which are on the order of hundreds of km/s. For resolved GCs (where individual stars can be observed), radial velocities can be used to identify cluster members and remove field star contaminants, as long as the net GC velocity does not coincidentally match the surrounding field stars. Temperature and brightness As mentioned briefly in section 1.2.2, the appearance of a stellar spectrum (both the continuum brightness and the strengths of spectral lines) changes with temperature and brightness—this is the source of the OBAFGKM and luminosity classification schemes. These parameters can therefore be derived for any star from the observed spectra, particularly in combination with photometry. Because their distances are known reasonably well, it is slightly easier to derive the temperature and luminosity of GC stars, simply because it removes one level of uncertainty from the analysis.7 Figure 2.3 shows an example of how temperature and luminosity affect a stellar spectrum. Here, the luminosity is parameterized by the logarithm of the surface gravity, log g; giant stars have low log g values, while dwarfs have higher log g values. In figure 2.3, the chemical composition is kept constant while the temperature and log g are varied; the resulting changes in the spectral line strengths are 7 The Gaia mission [19] is beginning to provide parallax-based distances for bright Milky Way stars, which is making it easier to determine the atmospheric parameters for all stars; future data releases will provide highquality parallaxes for even fainter stars. Gaia will also provide radial velocities for bright stars, which can be used to remove field star contaminants from cluster CMDs.

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Figure 2.3. Synthetic spectra (red lines) around the strong Mgb lines, showing the effects of varying temperature and surface gravity. The synthetic spectra were created with the 2017 version of the line analysis code MOOG [73]. The black points show a high-resolution spectrum of the Sun [36]. Top: synthetic spectra with a fixed log g = 4.5 and [Fe/H] = 0.0 and temperature varying from to 5100 to 8200 K. It is evident that the Sun has T ∼ 5800 K. Bottom: synthetic spectra with a fixed T = 5800 K and [Fe/H] = 0.0 and log g varying from 0.5 to 4.5. As time goes on, the surface gravity increases, i.e., the star gets fainter. The best fit to the Solar spectrum has log g ∼ 4.5. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

dramatic. This figure also demonstrates that if the goal is to use the strengths of spectral lines to determine chemical abundances (hereafter referred to as abundances), the temperature and brightness must be known reasonably well. Note that there are many other factors that can affect line strength, including stellar rotation and small scale motions in the stellar atmospheres, but those will not be discussed here. Stellar composition The strength of a spectral line from a particular element X will vary as the abundance of element X changes, often not linearly. There are a variety of reasons why the abundance of a particular element can vary in stellar atmospheres:

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1. The abundances of many elements depend on the star’s total metal content (i.e., its metallicity). For most elements, metal-poor stars generally have lower absolute abundances than metal-rich stars. As mentioned in section 2.2.1, the logarithmic ratio [Fe/H] is often used as a proxy for stellar metallicity, with the Sun at [Fe/H] = 0 by definition. A star at [Fe/H] = −2 has 100 times less (10−2) iron than the Sun; if the elements all scale together (an often incorrect assumption; see point 2 below) then all elements, including Mg, will be 100 times less abundant than the Sun in that metal-poor star. Figure 2.4 shows how a spectrum changes with metallicity (assuming a standard scaled-Solar mixture). 2. The abundances of each element can vary beyond the standard Solar mixture— this is because each element has a slightly different nucleosynthetic site (i.e., each element forms in slightly different processes, in different types of stars, and at different times). On average, over an extended period of time, the chemical abundances of stars tend to converge to similar abundance patterns as a function of metallicity, but this is not the case for all stars. Furthermore, the abundances of different groups of elements do not always vary together in the same way. It is valuable to know how specific elements change with respect to, e.g., Fe, and how these variations change with age or environment. These variations are again quantified using logarithmic ratios with respect to the Sun; a positive [Ti/Fe], for example, would indicate that a star has more Ti relative to Fe than the Sun. Figure 2.2 shows the effect of varying the Ti abundance in syntheses of the star Arcturus. 3. Additionally, some elemental abundances will change as a star ages. In particular, a star’s carbon and nitrogen will vary as the star ascends the RGB.8 Knowing the star’s evolutionary stage may be important for interpreting the derived abundances. Note that deriving stellar abundances from observed spectra is not a simple task—it requires detailed knowledge of atomic physics, a model of the stellar atmosphere, and a line analysis code (such as MOOG; [73]). It is important to remember that, unlike stellar magnitudes, chemical abundances are not an observed quantity; they are derived from observed spectra using models. The derived abundances can vary considerably if different parameters, models, or assumptions are adopted. Figure 2.5 demonstrates how resolution affects spectra. Here, resolution is defined as the minimum spacing between two points. For stars, the resolution is primarily set by the spectrograph (the instrument at the telescope that records the observed spectrum). As the resolution is degraded, individual lines are blended together

8 Changes in C and N occur as a result of convection, during which material that has undergone fusion is brought to the surface.

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Figure 2.4. Synthetic spectra (red lines) showing the effects of varying metallicity and titanium abundance. The synthetic spectra were created with the 2017 version of the line analysis code MOOG [73]. The black points show a spectrum of the RGB star Arcturus [28]. Top: synthetic spectra with a fixed Teff = 4300 K and log g = 1.5 with the metallicity, [Fe/H], varying from −4.0 to 0.0. The Arcturus spectrum is fit best with [Fe/H] ∼ −0.5. Bottom: synthetic spectra with a fixed Teff = 4300 K, log g = 1.5, and [Fe/H] = −0.5 and with [Ti/Fe] varying from −0.6 to +0.6. A single Ti line is shown. Whereas changes in the total metallicity influence the strengths of all spectral lines, changes in [Ti/Fe] only affect the Ti lines. A value of [Ti/Fe] ∼ +0.4 best matches the observations of Arcturus. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

because the separation between the lines can no longer be resolved. At the lowest resolution, the weakest spectral lines are no longer detectable. This figure illustrates that high-precision abundances for the maximum number of elements requires observations at high-resolution (R ≳ 30, 000). At the lowest resolution, it may only be possible to characterize the overall metallicity of an object rather than abundances of individual elements. Recall from section 1.2.2 that the choice of resolution is often dictated by the science goals, the brightness of the object, and more.

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Figure 2.5. Synthetic spectra (red lines) around the strong Mgb lines, showing the effects of varying spectral resolution from R = 1000 to 120 000. The synthetic spectra were created with the 2017 version of the line analysis code MOOG [73], assuming a fixed Teff = 4300 K, log g = 1.5, and [Fe/H] = −0.5. The black points show a spectrum of the star Arcturus [28]. Animation available at https://iopscience.iop.org/book/978-1-64327750-9.

2.3 Scientific lessons from Milky Way GCs Before continuing to the Andromeda Galaxy (M31) GC system, it is worth briefly summarizing the scientific results from studies of the GCs in the Milky Way and its satellite galaxies. A considerable amount of work has been done in the last century; this section only contains brief highlights that will be useful in comparisons with M31’s GC system. 2.3.1 GC numbers and masses The MW has ∼150 confirmed GCs [22], although, as discussed in section 2.1, an exact number remains somewhat elusive because a ‘GC’ is not always well-defined, either at the high- or low-mass ends. Figure 2.6 demonstrates the general mass distribution of Milky Way GCs, using the masses from McLaughlin and van der Marel [52]. The Milky Way open clusters are also shown to highlight the general difference in mass between classical GCs and open clusters, using the masses from Piskunov et al. [60]; note that this sample only contains nearby open clusters, and could be biased or incomplete. As mentioned earlier, in the Milky Way the classical GCs are primarily old (with ages ≳10 − 12 Gyr; [77]), while the open clusters are all young (see section 2.3.3 for more discussion on ages). High-mass GCs are fairly rare, and, as expected, there are not many of them in the Milky Way. The most massive GC, ω Cen, is expected to be the nuclear star cluster from a now-disrupted dwarf galaxy, and therefore likely had a slightly different formation pathway from most Milky Way GCs (see chapter 5). Low-mass, old clusters are also rare, because lower-mass systems are more likely to be torn apart as they orbit in the gravitational potential of the high-mass Milky Way. The

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Figure 2.6. The distribution of Milky Way GC masses [52] compared to a sample of Milky Way open clusters [60] and young, massive LMC clusters [52]. The open cluster sample consists of nearby clusters, and may not be representative of all open clusters in the Milky Way. While the Milky Way GCs are on average more massive than local open clusters (note that there is some overlap with the open cluster sample); this is where the low-mass, intermediate-age, GC candidates lie. The LMC clusters overlap with the lower mass end of the GCs; however, it is not clear what these LMC clusters will look like after ∼10 Gyr of evolution.

timescale and magnitude of this disruption is also likely to be a function of location in the Galaxy, such that clusters near the inner regions may be more easily disrupted (e.g., [64]). The shape of the cluster mass distribution will also depend on properties of the host galaxy. For example, low-mass clusters that form in lower-mass dwarf galaxies may be able to survive longer than those that form in the Milky Way. This cluster disruption paradigm means that at least part of the Milky Way’s halo could be composed of debris from disrupted star clusters (see section 2.3.5). This dichotomy between young, low-mass open clusters and old, high-mass GCs is confused by the addition of massive clusters from the LMC [52]. Many of these clusters are young or intermediate-age (with ages ≲6 Gyr), yet figure 2.6 shows that they have comparable masses as old Milky Way GCs. As discussed in section 2.1, these clusters will lose mass as they orbit through the gravitational potential of the LMC (and as they interact with the Milky Way), and it is unknown whether these younger clusters will resemble the current Milky Way GCs after 10 Gyr of evolution. However, the addition of the LMC clusters to this distribution shows that it is not trivial to separate open clusters from GCs based on mass alone. 2.3.2 Metallicities and kinematics In the late 20th century it was discovered that the Milky Way has two distinct subpopulations of GCs, one that is more metal-rich and one that is metal-poor. This is 2-11

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Figure 2.7. Top: the [Fe/H] distribution of Milky Way GCs, based on the 2010 version of the Harris catalog [22] with spectroscopic metallicities from Carretta et al. [6]. A two component Gaussian fit is shown, with the metal-poor population (centered at [Fe/H] = −1.6 ) in blue and and the metal-rich population (centered at [Fe/H] = −0.5) in red. Bottom: the distribution of GC metallicities as a function of distance from the center of the Milky Way. The Milky Way GCs are divided into two populations: metal-rich GCs (red) and metal-poor GCs (blue); the dividing line between the two populations is [Fe/H] = −1. The green crosses show the GCs that are being accreted into the Milky Way from the Sagittarius dwarf spheroidal.

evident purely from a histogram of metallicities (figure 2.7), which also shows that the Milky Way has more metal-poor GCs than metal-rich ones. Although it was known earlier that GC metallicities varied substantially, it was only possible to see this metallicity bimodality when large samples of clusters were analyzed in a homogeneous way (meaning that all the clusters were analyzed using the same techniques; e.g., see [17]). The average metallicity of GCs also changes with distance from the center of the Milky Way, leading to a radial gradient. The most metal-rich GCs are located closer to the center of the Milky Way; the average metallicity then gradually decreases for GCs lying further away (figure 2.7(b)). This gradient is seen

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in both the metal-rich and the metal-poor GC populations; however, the gradient flattens in the outermost parts of the Galactic halo, where the scatter in metallicity becomes very large [72]. The motions (kinematics) of the Milky Way GCs further show that the two metallicity groups are distinct populations, possibly with different formation sites. In 1985, Zinn [82] established that the GCs could be kinematically divided into two populations: one with the kinematics typical of disk stars and the other with halo kinematics. The former GCs were found to be more metal-rich, while the latter were more metal-poor. This finding hinted that the separate metallicity components likely formed in different ways, leading to distinct compositions and kinematics. Zinn’s paper was also one of the first to demonstrate that GCs trace the properties of the Milky Way field star populations. This early work on metallicities and kinematics placed some valuable constraints on galaxy formation models. Previous models (e.g., [13]) had suggested that the Galaxy formed from the collapse of a large gas cloud, a model often referred to as the ‘monolithic collapse’ model. This framework was supported by observations of nearby stars. However, the metallicity spread amongst Milky Way GCs, the lack of a gradient in the outer regions, and the existence of a metallicity bimodality cast serious doubt on the monolithic collapse framework. Continued observations have shifted the paradigm of galaxy formation towards the gradual buildup by accretion of smaller satellite galaxies (i.e., the ΛCDM framework) rather than a single monolithic collapse. For example, the recent advent of the Gaia mission [19] has made it possible to determine high-quality orbits for Milky Way stars and GCs. Through an examination of the orbits of the current GCs, Massari et al. [50] found that only 40% of the GCs likely formed in the Milky Way (i.e., formed in situ). Of the others, they identify 35% that are likely associated with specific streams in the Milky Way and another 16% with high energy that are likely to have been accreted, but do not yet have an obvious host galaxy. 2.3.3 Ages In a seminal paper from 1978, Searle and Zinn [72] used photometric observations of Milky Way GCs to infer age differences between clusters. They found that GCs in the inner regions of the Milky Way had a small age spread, while those in the outer regions had a much larger spread—they argued that this was evidence that the Milky Way was continually accreting stars and GCs into its outer halo after the central regions had already formed, creating a mixture of old and young GCs. They also suggested that these GCs could have formed in dwarf galaxies that were later accreted into the Milky Way halo (a prediction for hierarchical assembly that occurred before ΛCDM simulations). Since then, various studies have confirmed the old ages of the classical (bright and centrally concentrated) GCs in the Milky Way (e.g., [77]) and several dwarf galaxies, finding small cluster-to-cluster age differences. The age differences between clusters of the same metallicity are often interpreted as a signature that the clusters formed in different environments with distinct agemetallicity relations (AMRs). Broadly speaking, the AMR examines how rapidly 2-13

The Globular Star Clusters of the Andromeda Galaxy

Figure 2.8. An adaptation of the AMR from Leaman et al. [39]. The majority of the cluster ages are from the homogeneous photometric analysis of VandenBerg et al. [77], with five additions from Leaman et al. [39]; their analysis used the Carretta et al. [6] metallicities, which are also used here, with a few exceptions. For Ruprecht 106, the spectroscopic metallicity and photometric age from Villanova et al. [80] and Dotter et al. [12] are adopted. The ages and metallicities of Palomar 1, Segue 3, and NGC 6791 are from Sakari et al. [67], Hughes et al. [30], and Brogaard et al. [5], respectively. The yellow squares show GCs that are strongly suspected to have originated in the Sagittarius dwarf spheroidal, while the magenta diamonds show other GCs that are suspected to have been accreted from other (as yet unidentified) dwarf galaxies. The lines show very simple models for three different galaxies [40], in order of decreasing mass: the LMC, the Small Magellanic Cloud (SMC), and the Wolf–Lundmark–Melotte (WLM) dwarf galaxy. Note that a similar model cannot be made for the Milky Way, because it is too complex. Leaman et al. also note the different AMRs between the old GCs in the inner bulge, which are offset to higher [Fe/H] ratios compared to the GCs in the halo.

galaxies have enriched in iron, where the specific shape of the AMR depends on the mass of the Galaxy. Recall that all iron is produced in stars. After the early period of Big Bang nucleosynthesis, the Universe only contained hydrogen, helium, and trace amounts of light elements. Because the Milky Way is such a massive galaxy, it very quickly formed many stars, which created a lot of iron. Dwarf galaxies, on the other hand, require more time (i.e., more rounds of star formation and evolution) to create the same amount of iron—some of the lowest mass dwarf galaxies may not have enough gas for extended periods of star formation, and may only contain populations of metal-poor stars. The relationship between age and metallicity therefore changes between galaxies of different mass.9 Figure 2.8 shows a recent AMR for GCs in the Milky Way, based on the ages from VandenBerg et al. [77] and Leaman et al. [39]. Previous studies (e.g., [15]) have used plots such as this to identify potentially accreted GCs. The clusters that were likely accreted from dwarf galaxies are younger than the classical Milky Way GCs at the same metallicity, simply because it took the dwarf galaxies much longer to enrich to that metallicity. Again, the numbers and properties of the accreted satellites are valuable properties for comparisons with cosmological simulations. The observed AMR can provide insight into the assembly history of a galaxy. Leaman et al. [39] compared the AMR 9

A galaxy’s AMR is also dependent on other factors, such as assembly history, environment, etc.

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in figure 2.8 to models for various low-mass galaxies and estimated the numbers and masses of the galaxies that were accreted into the Milky Way, along with the outer halo GCs. Similarly, Kruijssen et al. [35] compared the AMR from Milky Way GCs to those from simulations, finding that the Milky Way has likely accreted at least three massive satellite galaxies, one of which is the Sagittarius dwarf spheroidal. The most massive of these galaxies were accreted early on, and could have been the birth sites of 40% of the Milky Way’s GCs. The AMR is therefore a powerful tool for understanding how a galaxy has formed. 2.3.4 Chemical evolution and tagging A star’s iron abundance ([Fe/H]) is dictated by the previous generations of stars that existed before it formed. Iron is created primarily during supernovae explosions, including core collapse Type II supernovae, which are at the end stage of massive stellar evolution, and the Type Ia supernovae that result from the detonation of a white dwarf (the former core of a lower mass star). Iron therefore has multiple nucleosynthetic sites. Other elements form in different processes and different types of stars. For instance, calcium is primarily made in massive stars, though very little is produced in Type Ia supernovae. Because massive stars evolve more quickly than lower mass stars, the relative amounts of calcium and iron within a single galaxy will change over time. The early Universe contained no calcium or iron, since none was created in the Big Bang. As the early massive stars evolve and explode in corecollapse supernovae, the amount of Ca and Fe increases with time. Eventually, when enough time has passed for lower mass stars to evolve to the white dwarf phase, Type Ia supernova start to occur, producing lots of iron, but very little calcium. The chemical evolution of these two elements is typically investigated by looking at the [Ca/Fe] ratio10 versus [Fe/H], as shown in figure 2.9 for Milky Way field stars and GCs. This plot contains all the information described above. The [Fe/H] ratio is commonly interpreted as a proxy for time, since the iron content of a galaxy generally increases with age (though see below), while the [Ca/Fe] ratio compares the contributions from massive and low mass stars. The shape of figure 2.9 can be explained by the scenario outlined above: at the low [Fe/H] end, only massive stars have had time to evolve, and though there is scatter, on average the [Ca/Fe] ratio is relatively constant with [Fe/H] (i.e., with time). Once the Type Ia supernovae start to explode, more Fe is produced, and the [Ca/Fe] ratio starts to decrease. This turnover point, or ‘knee,’ occurs at about [Fe/H] ∼ −1 in the Milky Way. Note that the Milky Way GCs track the chemical evolution of the Milky Way field stars very well (at least in [Ca/Fe]). Figure 2.9 also shows stars and GCs in various dwarf satellites of the Milky Way. From this comparison, it is evident that the position of the ‘knee’ shifts to a lower [Fe/H] in the dwarf galaxies. The [Fe/H] at which the knee occurs is dependent on the mass of the Galaxy. This can be understood by considering the different AMRs in these systems. The time it takes a star to evolve to the white dwarf phase is the 10

Again, [Ca/Fe] is a logarithmic ratio with respect to the Sun.

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Figure 2.9. A plot showing [Ca/Fe] versus [Fe/H] for stars and GCs in various galaxies. The GC abundances are averages from individual stars. The stellar masses of the galaxies (from [51]) are also shown to illustrate how the distribution of stars changes with galaxy mass. The Milky Way field stars are shown with grey points (from [16, 63, 66, 78]); the Milky Way GC averages, shown with black stars, are from the compilation by Pritzl et al. [62]. The blue open circles are field stars in the LMC (from [61] and [76]) while the blue stars are the LMC GCs (young, intermediate-age, and old; from [11, 34, 56, 57, 65]). Stars (open circles, from [21, 53, 55, 69]) and GCs (stars, from [8, 10, 54, 70]) associated with the Sagittarius dwarf spheroidal (Sgr) are shown in purple. Note that there are additional Milky Way GCs that are suspected to have been accreted from Sgr [38], but they are not included here. Also, note that, because Sgr is in the process of being disrupted, its stellar mass may be higher than the estimate from McConnachie et al. [51]. The field stars in the Fornax dwarf spheroidal (from [16, 25, 41, 44, 74]) are shown with yellow open circles, while its GCs (from [25, 37, 43]) are shown with stars. Finally, stars from two lower mass dwarf galaxies without any GCs are also shown: the Sculptor dwarf spheroidal (green open circles, from [16, 27, 74]) and the Carina dwarf spheroidal (magenta open circles, from [14, 16, 42, 79]). Animation available at https://iopscience.iop.org/book/978-1-64327-750-9. Otherwise, only the Milky Way field stars and LMC stars and GCs are shown.

same in massive and low-mass galaxies. However, figure 2.8 shows that the [Fe/H] of stars at a given age differs between the Milky Way and its dwarf satellites. This means that in the Milky Way the knee (the onset of Type Ia supernovae) happens at a higher [Fe/H] than in a system like the LMC. One benefit of these differing chemical evolution patterns is that a star’s position in a [Ca/Fe] versus [Fe/H] plot provides a way to link it chemically to its birth environment. If a star or GC in the Milky Way is found to have a lower [Ca/Fe] ratio than most Milky Way stars at that [Fe/H], it was likely accreted into the Milky Way from a dwarf galaxy. This comparison is strengthened by examining as many different abundance ratios as possible. These chemical tagging analyses have identified several GCs in the Milky Way that look to have been accreted, including several along the streams from the Sagittarius dwarf spheroidal (see [75] for a review). Furthermore, because the location of the knee in the [Ca/Fe]−[Fe/H] plot is dependent on the mass of the birth galaxy (see above), a GC’s Ca and Fe abundances provide constraints on the mass of its original host galaxy. For example,

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the abundances of stars in Palomar 1, a fairly low-mass star cluster, imply that it was accreted from a fairly massive satellite, that was roughly the mass of the LMC [67]. Recall from section 2.3.3 that chemical enrichment has proceeded somewhat differently in the various components of the Milky Way. The most metal-rich stars and GCs are typically found in the disk and bulge regions,11 while the halo stars and GCs are predominantly metal-poor. The presence of a metallicity gradient within the Milky Way (Section 2.3.2) means that the stars in a plot like figure 2.9 will change subtly as a function of distance from the center of the Galaxy. Young, metalrich, low [Ca/Fe] stars or GCs in the outer halo at large distances from the center of the Milky Way are likely to be there as a result of an interaction with another galaxy; either they were accreted from the dwarf galaxy itself as it fell into the larger gravitational potential of the Milky Way, or they were pulled out of the inner regions of the Milky Way as the dwarf galaxy fell in. The combination of ages, metallicities, detailed chemical abundances, and kinematics all provide essential information about a galaxy’s assembly history. 2.3.5 Multiple populations For several decades, astronomers have known that GCs are not chemically homogeneous—that is, not all stars within a GC have the same chemical composition. In 1973, Zinn [81] observed variations within the GC M92, showing that stars with identical temperatures and surface gravities could have vastly different strengths of spectral lines from the molecule CH. Since then, various groups have identified many more chemical variations within Milky Way GCs. The advent of large photometric and spectroscopic surveys has shown that abundance spreads seem to be a ubiquitous feature of classical Milky Way GCs (i.e., the indisputable, old, massive GCs), though the nature and extent of these spreads can vary substantially between clusters. Chapter 5 will be dedicated exclusively to these ‘multiple populations’ (i.e., abundance variations) in GCs,12 but the current discoveries from Milky Way GCs are briefly summarized below. Note that Freeman and Norris [17] provide a nice review of the early detections of abundance spreads, while Bastian and Lardo [1] provide a modern review. Carbon and nitrogen variations: all GCs seem to have variations in C and N. Some variations occur during stellar evolution, as a star ascends the RGB and the products of hydrogen fusion are brought to the surface. However, these CN variations are seen even in unevolved, main sequence stars (e.g., [3, 26]), which implies that there must be a primordial source of C and N variations. In some clusters the C and N variations are so large they can lead to distinct tracks in CMDs (see, e.g., [47]). CN spreads have even been seen in intermediate-age GCs in the LMC [29]. 11

There are also subtle chemical differences in the thick versus thin disk components (e.g., [2]). Note that the meaning of the phrase ‘multiple populations’ varies between studies. Sometimes it refers to any abundance variations; other times it refers only to populations with different Na/O. The definition of the term ‘multiple populations’ will be discussed in more detail in chapter 5. 12

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The sodium–oxygen anticorrelation: significant variations in Na and O have been observed in all classical Milky Way GCs. The sodium variations were first noticed by Cohen in 1978 [9] in the GCs Messier 3 and Messier 13. Since then, large homogeneous samples (e.g., [7]) have established that Na and O spreads are ubiquitous in Milky Way GCs. All GCs seem to have a Na–O anticorrelation, with Na increasing and O decreasing relative to the ‘normal’ Milky Way values. The magnesium–aluminum anticorrelation: strong variations in Mg and Al have also been identified in some GCs, particularly the massive, metalpoor ones. The Al variations were first noted in 1981 by Norris et al. [58] in the GC NGC 6752. Again, subsequent analyses have established that the variations exist in the form of an anti-correlation, although some clusters have no evidence of Mg or Al spreads [7]. Helium variations: helium is very difficult to measure spectroscopically, but photometric observations have identified signatures of He spreads (e.g., [47]; see chapter 5). Iron spreads: spreads in metallicity (often parameterized by Fe) are confined to only a few clusters, generally the most massive (and brightest) ones. The massive Milky Way GC ω Cen is the prototypical GC in this class. Freeman and Rodgers first noted a metallicity spread in ω Cen in 1975 [18]; since then a sample of 855 RGB stars in ω Cen by Johnson and Pilachowski [33] has established that the cluster contains stars with −2.26 < [Fe/H] < −0.32. The sub-populations with different metallicities also have their own Na/O anticorrelations. Although ω Cen is the most extreme example in the Milky Way, other clusters with Fe spreads have been identified. Johnson et al. [32] refer to these systems as ‘iron-complex’ clusters. Other elements: some GCs have spreads in the heaviest elements, like barium and europium, although these GCs are also rare. These heavy element variations are not connected to either the metallicity variations or the light element variations, and will not be discussed further. The potential sources for these variations (which are hotly debated) will be discussed more in chapter 5 (also see [1]). However, it is worth noting two important things. First, the light-element abundance variations (in C, N, O, Na, Mg, and Al) seem to be a unique chemical signature of GCs, as a result of some physical scenario that only occurs in cluster environments. A handful of field stars with this chemical signature have been identified in the Milky Way halo and bulge [48, 49, 71], but these stars are suspected to have been stripped from GCs. GC formation, evolution, and dissolution, both from GCs that form within the Milky Way and those that are accreted from dwarf galaxies, may therefore play an important role in assembling various components of the Milky Way. A second point to consider is that the ‘multiple populations’ phenomenon is not unique to Milky Way GCs. Various groups have detected C, N, O, and Na 2-18

The Globular Star Clusters of the Andromeda Galaxy

variations within old GCs in dwarf satellites of the Milky Way, including the Fornax dwarf spheroidal, the SMC, and the LMC. There may also be C and N variations within intermediate-age GCs in the LMC [29], though Na and O variations have hitherto only been observed in old GCs. One of the GCs associated with the Sagittarius dwarf spheroidal, M54, also has significant spreads in Fe [8]. Like ω Cen, M54 is thought to have been a nuclear star cluster, largely based on its proximity to the main body of the Sagittarius dwarf spheroidal [31]. Taken together, the body of evidence from the GCs associated with the Milky Way and its dwarf satellites suggests that light element chemical variations are a common, perhaps even ubiquitous, feature of massive, old GCs, regardless of their birth site. This means that the GCs in M31 will likely also host multiple populations, but the chemical spreads will be much more difficult to detect because of the observational techniques needed to study distant GCs. Variations in heavier elements are much more rare and tend to only be seen in the most massive GCs—however, these massive GCs are the easiest targets to observe, because they are brighter than their fainter counterparts. It is important to keep in mind that the presence of undetected multiple populations within distant GCs may complicate observational studies; however, observations of M31 GCs also offer more opportunities to study the nature of multiple populations within GCs (see chapter 5).

2.4 Summary: Milky Way GCs For over a century, GCs have been used to study the Milky Way Galaxy. Early on, GC ages and metallicities provided challenges to the existing paradigms for the formation and assembly of the Milky Way. Since then, observations of GCs and individual stars have continued to assess the chemical evolution of the various components of the Milky Way. Observations have shown that some of the field stars in the Milky Way may have formed in GCs that are now dissolved. The observed chemical complexity of GCs has also challenged the paradigm for cluster formation. The astrophysical mechanism for creating star-to-star chemical variations within GCs is not yet established, yet it seems to occur in all old, massive GCs. Star cluster formation itself seems to be a natural consequence of periods of intense star formation, as evidenced by the presence of young massive clusters in the LMC; however, it is still unknown if these young clusters will resemble Milky Way GCs after 10 Gyr of evolution. The formation and nature of GCs, their connections to the field stars, and the details of cluster evolution all remain somewhat shrouded in mystery, necessitating additional studies of systems beyond the Milky Way and its dwarf satellites. Despite these uncertainties, studies of the Milky Way’s stars and GCs have demonstrated that, for the most part, the recent assembly history of the Milky Way has been fairly quiet. The ongoing accretion of dwarf satellites is a fundamental prediction of the ΛCDM model of the Universe, but the Milky Way may have a below average accretion rate, according to comparisons with simulations [35]. Recent analyses of data from the Gaia satellite [24] and the Apache Point Observatory Galactic Evolution Experiment (APOGEE; [46]) survey [23] have 2-19

The Globular Star Clusters of the Andromeda Galaxy

shown that there is chemical and kinematic evidence for a merger with a fairly massive dwarf galaxy (about the size of the SMC) roughly 10 Gyr ago. This galaxy, dubbed the Gaia-Enceladus galaxy, may have brought in ten or so of the Milky Way’s GCs, including the massive cluster ω Cen. The Milky Way is also currently accreting the Sagittarius dwarf spheroidal and its GCs, while several GCs have chemical abundances that indicate that another dwarf spheroidal has been accreted (including Pal 1 and Rup 106). However, there is little evidence to suggest that many major accretions have occured within the last few Gyr. If the Milky Way does have a lower than predicted accretion rate, this raises several questions. Is the Milky Way’s apparently low accretion rate a result of an observational bias? Is the Milky Way unlike typical spiral galaxies of similar mass? Or could the ΛCDM model of the Universe be incomplete? Answering these questions requires observations of galaxies other than the Milky Way; because of its proximity, M31 is the natural place to begin.

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Schiavon R P, Zamora O, Carrera R, et al. 2017 Mon. Not. R. Astron. Soc. 465 501 Searle L and Zinn R 1978 Astrophys. J. 225 357 Sneden C 1973 Astrophys. J. 184 839 Tafelmeyer M, Jablonka P, Hill V, et al. 2010 Astron. Astrophys. 524 A58 Tolstoy E, Hill V and Tosi M 2009 Annu. Rev. Astron. Astrophys. 47 371 Van der Swaelmen M, Hill V, Primas F, et al. 2013 Astron. Astrophys. 560 A44 VandenBerg D A, Brogaard K, Leaman R, et al. 2013 Astrophys. J. 775 134 Venn K A, Irwin M, Shetrone M D, et al. 2004 Astron. J. 128 1177 Venn K A, Shetrone M D, Irwin M J, et al. 2012 Astrophys. J. 751 102 Villanova S, Geisler D, Carraro G, et al. 2013 Astrophys. J. 778 186 Zinn R 1973 Astrophys. J. 182 183 Zinn R 1985 Astrophys. J. 293 424

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IOP Concise Physics

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 3 The inner halo/disk/bulge clusters

Learning goals After completing this chapter, readers will be able to: • Explain the difficulties in cataloguing and characterizing the globular clusters (GCs) of the Andromeda Galaxy (M31). • Describe how M31’s GCs are observed. • Summarize the observational and photometric properties of M31’s inner GCs. • Identify key differences between the inner M31 and Milky Way GCs, and the implications for M31’s inner assembly history.

3.1 Inner versus outer clusters The discussion of the M31 GCs begins with those in the inner regions, with projected distances from the center of R proj ≲ 25 kpc [29]. Note that because the GCs are viewed in projection (i.e. we see a two-dimensional rendering of a three-dimensional, or 3D, system), some of these clusters could have 3D distances beyond 25 kpc. Most of the GCs in the M31 system lie within the inner regions, in projection. Many are likely to be a part of M31’s halo, though as shown later, some are also likely to be associated with the disk or the central bulge regions. There are several reasons to consider the inner and outer GCs separately. The primary motivation is that these two components of the Galaxy may have distinct formation channels, as in the Milky Way (see section 2.3). The analysis techniques may differ slightly as well—GCs located in the more crowded central regions will be more sensitive to contamination from field stars than the GCs in the sparse outer regions. The inner GCs were also the first to be discovered based on photographic images from Hubble in 1932 ([22]; see section 1.3). Investigating the properties of M31’s GC population requires identifying candidate GCs and confirming that they are indeed star clusters, rather than foreground Milky Way stars or very distant background galaxies. This chapter first describes doi:10.1088/2053-2571/ab39dech3

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The Globular Star Clusters of the Andromeda Galaxy

the observing methods that are required to observe GCs in M31 (section 3.2). Section 3.3 then summarizes the efforts that have been made since Hubble’s 1932 catalog to perform a census of objects in M31. The properties of the young (section 3.4), intermediate-age (section 3.5), and old (section 3.6) GCs are then summarized, along with comparisons to the Milky Way GC system.

3.2 Integrated light observations of distant systems Section 2.2 described the observational techniques that are utilized for nearby systems whose individual stars can be observed. The M31 GCs are farther away than any object in the Milky Way and therefore cannot be studied at the same level of detail as the Milky Way GCs. As a cluster moves farther away, it becomes increasingly difficult to observe its individual stars, both photometrically and spectroscopically, simply because a distant star appears fainter than a closer star. For two stars with the same absolute magnitude (i.e. the same intrinsic brightness), observations of the distant star will collect fewer photons than observations of the nearby star in the same amount of time; as a result, the images and spectra of the distant star will have lower signal-to-noise ratios. It also becomes increasingly difficult to separate (or resolve) individual stars in the cluster center as a result of crowding. Eventually individual distant stars will be prohibitively faint for observations. Figure 3.1 shows the effects of distance on a color-magnitude diagram (CMD) by comparing a Milky Way GC, Messier 3 (M3; from [48]), to a GC in M31, H10 (from [46]). To compare the two GCs, which lie at different distances, the apparent V-band magnitudes have been shifted to absolute magnitudes.1 The two clusters have similar ages, chemical compositions, and masses [46]; yet the two CMDs look different as a result of observational limitations. If H10 were at the same distance as M3, the CMDs would look nearly identical (possibly with differences in the horizontal branches). However, because of H10’s distance, the faintest stars in H10 are much fainter; as a result, the main sequence turnoff in H10 is undetectable. The brighter stars in H10 can still be observed, but the photometric errors are larger than in M3; the larger errors associated with each point effectively broaden out the red giant branch (RGB), an effect that becomes increasingly worse for fainter RGB stars. Furthermore, because the stars in the center of H10 are crowded together and cannot be separated from one another, only the stars in the outer regions of the cluster can be analyzed. There are thus many fewer stars in H10’s CMD than in the CMD of M3, even though the clusters actually have similar masses. This figure demonstrates that individual stars are very difficult to observe in more distant GCs, even photometrically. It is therefore much harder to determine an M31 GC’s age and metallicity from its CMD than it is for a Milky Way GC. The problem only gets worse for sparse or reddened GCs, or those with significant foreground contamination. 1 The apparent magnitudes can be converted to absolute magnitudes using the distance modulus, (m − M )V , and the reddening, E (B − V ).

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Figure 3.1. Hubble Space Telescope CMDs of a Milky Way GC, M3 (grey; from [48]), and an M31 GC, H10 (black), adapted from Sakari et al. [46]. Because the clusters are at different distances, they have been shifted to absolute magnitudes (by correcting for distance) and intrinsic colors (by correcting for reddening). Note that H10 is actually an outer halo cluster, and will be discussed in more detail in chapter 4. Reproduced with permission of Oxford University Press on behalf of the Royal Astronomical Society.

Instead of observing individual stars, the brightness and concentration of GCs provide another way to analyze distant systems: the entire cluster can be observed in integrated light (IL), meaning that a single spectrum or magnitude is obtained for an entire cluster. As a whole, the cluster is much brighter than its individual stars, and IL observations can be obtained for GCs at much greater distances than individual stars. Naturally, analyses of IL photometry and spectra are much more complicated than for individual stars, since they require models of the underlying stellar populations (see below). However, stellar models or empirical template spectra will enable the information in IL observations to be unraveled. IL photometry provides valuable constraints on GC mass, age, and metallicity. If the distance is known, a single integrated magnitude reveals information about the total absolute magnitude, which is related to the cluster mass (as well as age and metallicity). Magnitudes in additional filters provide colors and rough spectral energy distributions for the GCs, which are dependent upon GC age and metallicity. To understand why this is useful, consider figure 2.2, which shows a CMD of the individual stars in the Milky Way GC 47 Tuc and isochrones of varying age and metallicity. The V magnitudes and the V−I colors of the individual stars change with both age and metallicity, which means that the total IL magnitudes and colors will also change with age and metallicity. For example, a younger cluster has brighter, bluer stars on the main sequence, compared to an older GC—the IL color of a 3-3

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young GC will therefore be bluer than the color of an old GC at the same metallicity. Similarly, old GCs with a higher [Fe/H] have redder RGBs than more metal-poor GCs, meaning that metal-rich GCs will have redder IL colors than metal-poor GCs. These two parameters are somewhat degenerate, i.e. it is difficult to isolate the effects of age from those of metallicity, and vice versa, but these problems can be mitigated by using specific filters, or by combining the photometric observations with spectroscopic observations. Just as with individual stars, IL spectroscopy provides information about the kinematics, ages, and chemical compositions of GCs. Section 2.2.2 demonstrated how the strengths of spectral lines were sensitive to the temperature and brightness of the stars, while figure 2.2 demonstrated that the temperature (color) and brightness (magnitude) of stars changes with age and metallicity. This means that the strengths of IL spectral lines will be sensitive to the GC age and metallicity. Figure 3.2 shows an example of an observed IL spectrum (again of the Milky Way GC 47 Tuc, from McWilliam and Bernstein [34]) and synthetic IL spectra where the age and metallicity of the synthetic population are adjusted. The cluster’s velocity dispersion also affects the IL spectrum. Recall that within a star cluster, not all stars have exactly the same velocity—instead, they show some dispersion about the mean velocity. Some stars are shifted blueward of the average GC velocity, while others are shifted redward; as a result, the IL spectral lines are broadened. The effect is similar to a decrease in resolution (see figure 2.5), which explains why the spectral lines in the 47 Tuc spectrum (figure 3.2) are broader than the lines in a typical stellar spectrum (figure 2.4). Because of the cluster velocity dispersion, most of the features in an IL spectrum are blends of multiple lines— determining abundances of individual elements is therefore generally harder than characterizing the overall metallicity of a GC. These IL analyses are more complicated than observations of individual stars. As a result, these techniques have been repeatedly validated with Milky Way GCs (e.g., [8, 15, 43]) to ensure that the IL ages and abundances truly reflect those of the GC. There has also been considerable effort dedicated to quantifying the systematic uncertainties that occur, particularly as a result of modeling the underlying stellar populations (e.g., [45, 52, 53]). These calibrations and tests have been essential for applying IL techniques to distant systems like M31. Note that M31 lies at an intermediate distance where its stars can generally be resolved with large telescopes (except when crowding is an issue, e.g., in the centers of GCs), but spectroscopic observations require a considerable investment of telescope time for a small number of stars. This means that M31 GCs must be studied using a mixture of resolved and IL photometry and spectroscopy. The mixture of observing techniques also ensures that the M31 field stars can also be studied and compared to the IL results from the GCs.

3.3 A Census of M31 GCs Hubble’s original sample of M31 GCs contained 148 candidates [22]. Since then, various studies have attempted to 1) compile more comprehensive catalogs, 2) 3-4

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Figure 3.2. Synthetic spectra (red lines) around the strong Mgb lines, showing the effects of varying age and metallicity. The synthetic spectra were created with the 2017 IL version of the line analysis code MOOG [44, 55]. The black points show a spectrum of the Milky Way GC 47 Tuc [34]. The spectrum has a fairly high resolution, but the velocity dispersion of σ ∼ 11 km/s lowers the effective resolution. Top: spectra with a fixed [Fe/H] = −0.6 and varying age from 6 to 14 Gyr. Bottom: spectra with a fixed age of 12 Gyr and varying [Fe/ H] from −2.27 to +0.06. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

establish whether the objects are truly M31 GCs, and 3) characterize the parameters (e.g., age and metallicity) of the confirmed GCs. Achieving these goals typically involves several steps, from detecting ‘fuzzy’ objects (i.e. objects that are not obviously stars) in photometric data sets to follow-up observations that confirm membership in M31. In many early surveys, the initial photometric measurements typically utilized only a handful of filters and only discovered the brightest clusters. It is also easier to find GCs in regions without a significant amount of contamination from the M31 field stars; GCs in the bulge regions, for instance, may be harder to detect against the bright M31 background. Identifying the clusters may be difficult to do in an automated fashion, often requiring significant human input. If the goal of

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a survey is completeness, i.e. discovering all of the star clusters in M31, this can make the process of cluster identification very time intensive.2 After initial discoveries of candidate GCs, follow-up observations reveal additional information about the objects. A ‘fuzzy’ object (an object that does not look like a point source) may indeed be a star cluster, but it could also be a background galaxy or a chance alignment of Milky Way or M31 field stars. If the target does reside within M31, it should have a radial velocity similar to the Galaxy itself. Hubble cited the radial velocity of one of his 148 candidate GCs as evidence that the object could indeed be an M31 GC. The first published spectroscopic observations, by Mayall and Eggen in 1953 [30], confirmed membership in M31 for six cluster candidates.3 Furthermore, if a candidate object is a cluster, it should also have an appropriate spectrum, including a reasonable velocity dispersion. A background galaxy will have a much larger velocity dispersion and, consequently, broader spectral lines; conversely, a single foreground star will have much narrower spectral lines (both will also likely have discrepant radial velocities). Deeper, higher spatial resolution imaging (e.g., with the Hubble Space Telescope) can also distinguish true star clusters from foreground stars, background galaxies, and chance alignments. The definition of a ‘cluster’ is also important when considering the numbers of GCs in various catalogs. In their catalog of star clusters from the PHAT footprint, Johnson et al. [24] define a cluster as a ‘grouping of stars that are spatially and temporally correlated’. This definition necessarily includes lower mass open clusters, and may technically also apply to galaxies. More restrictive definitions, however, run the risk of removing legitimate clusters from the catalogs. Although the definition of a GC may not be scientifically necessary for some science goals (recall chapter 2), the definition of a GC is essential when considering the completeness of a catalogue and when comparing M31 observations with the Milky Way. To summarize the above points, photometric surveys will have the most success in identifying the brightest, most centrally concentrated GCs in uncrowded regions. These bright GCs will also be the easiest clusters to follow up spectroscopically, and they will be unambigous GCs in high-quality, resolved photometry. GCs will also be easier to discover in high density regions with many targets, i.e. in the inner halo and disk, because there will be more data sets available for those areas. These factors explain why the original GC catalogs were biased towards bright, compact, GCs in the inner halo and disk. Since Hubble’s 1932 catalog, many research groups have conducted surveys of M31, searching for new clusters and seeking to establish membership for candidates. The Revised Bologna Catalog [14] contains a list of GC candidates in M31; as of 2012, they list ∼700 GCs, although several of these are not yet confirmed. Caldwell and Romanowsky [3] argue for a robust detection of 441 old, massive, unambigous GCs (including clusters that will be discussed in chapter 4). 2

See Johnson et al. [24] for a description of the Andromeda Project, during which 29 262 citizen scientists aided in helping to categorize objects in the PHAT dataset as stars, M31 clusters, background galaxies, or image artifacts. Johnson et al. also provide a thorough discussion of the completeness of the PHAT survey’s cluster catalogue. 3 Note that two of their original targets have Rproj > 25 kpc , which makes them outer halo GCs (see chapter 4).

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Again, the definition of a GC is important when considering the numbers from these catalogs. As mentioned in section 2.1, there is not always a clear distinction between globular and open clusters. Considering all star clusters, Johnson et al. [24] find 2753 star clusters in the PHAT footprint alone, which represents only 1/3 of the disk and the central bulge. Although the young, very low-mass clusters are clearly counterparts of the Milky Way open clusters, several of the new higher mass clusters could be considered GCs. Given that the GCs and the open clusters share some similar characteristics that may indicate similar formation channels (see the discussion in Johnson et al. [25]), it may not be appropriate to consider them as separate, distinct populations. A necessary part of spectroscopic and photometric follow-up therefore involves determining the masses, ages, and chemical compositions of GCs. Even just considering its 441 classical GCs [3], M31 has more GCs than the Milky Way (which has ∼150 classical GCs; [18]). This implies that M31’s assembly history has led to a higher specific frequency than the Milky Way. The specific frequency quantifies the number of GCs in a galaxy, relative to its total magnitude.4 Figure 3.3 shows a plot of specific frequency, SN, versus galaxy magnitude, based on data from the Harris catalog of extragalactic GC systems [20]. Note that in this plot, M31 has a higher MV than the Milky Way; however, it is difficult to determine the total magnitude of the Milky Way, given our position inside of it. Despite the disparate number of GCs, the Milky Way and M31 have similar specific frequencies,

Figure 3.3. Top: the specific frequency, SN (a quantification of the number of GCs in a galaxy of a given MV; see Harris et al. [20] for the definition), versus the total absolute V band magnitude of a galaxy. The solid grey points are galaxies from the Harris ‘Catalog of Globular Cluster Systems in Galaxies’ [20]. The points for the Milky Way and M31 utilize all confirmed GCs in the inner and outer regions. This plot is a modification of figure 10 from Harris et al. [20].

4 Note that it may be better to compare the total number of GCs relative to the total mass of a galaxy (the specific mass); see Harris et al. [20].

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suggesting that M31 may indeed by brighter (and more massive) than the Milky Way. However, various studies have found the Milky Way to be higher mass than M31 (see the discussion in chapter 1). M31’s higher number of GCs could also be a result of the accretion of satellites with high specific frequencies (see chapter 4).

3.4 The young clusters This section examines the properties of young, massive clusters in M31. Here, a young cluster is defined as having an age less than 2 Gyr. Although figure 2.2 does not show isochrone models younger than 1 Gyr, by extrapolation it is evident that young clusters will have very bright main sequence stars that can be observed more easily than the fainter main sequence stars in old GCs. Because the bright main sequence can be detected photometrically, from high-quality Hubble Space Telescope CMDs, ages for these young clusters can be directly measured, as shown in figure 3.4(a). Alternatively, ages can also be determined from IL photometry and spectroscopy (e.g., [2, 13]). For example, Caldwell et al. [2] utilize the strengths of the hydrogen Balmer lines5 in IL spectra as an age indicator. Figure 3.5 shows lowresolution spectra of several young clusters from the Caldwell et al. [2] sample, demonstrating how an optical IL spectrum changes with age. A young cluster has very bright, massive main sequence stars; its spectrum peaks in the blue, and it has strong Balmer lines. As clusters age, the hottest main sequence stars evolve and move off the main sequence; the cooler stars in the cluster become the brightest stars, the peak of the IL spectrum moves redward, and the strengths of the Balmer lines change.6 It is difficult to determine metallicities from the spectra of young clusters; for this reason, they are typically assumed to have solar metallicities, as expected from young clusters in the Milky Way. Figure 3.6 shows the locations of a sample of young, bright clusters on optical and infrared images of M31 (from [2]). The bright parts of the infrared image show star forming regions, where dust is hot and bright. The young clusters appear to lie on or near these active star forming regions, including a bright ring of star formation about 10 kpc from the center of M31 [2, 24]. The spatial association with the star formation regions further confirms that these clusters are indeed likely young, have formed recently during major star formation events along with field stars in the Galaxy, and have not yet had time to migrate away from their natal star forming regions. Various studies have shown that M31 has many young, low mass star clusters in its disk and inner regions that are likely to be similar to Milky Way open clusters. Unlike the Milky Way, however, M31 has a population of young clusters that, based on their masses, could be classified as GCs. Figure 3.7 shows the mass distribution of the young clusters from Caldwell et al. [2], compared to a sample of Milky Way 5

The Balmer lines, such as Hα, Hβ, Hγ, etc., are generally the strongest hydrogen lines in the optical. They are commonly used in spectral typing for individual stars. 6 Note that the presence of hot, evolved horizontal branch stars in metal-poor GCs can alter the IL spectrum in similar ways. Consequently, some old, metal-poor GCs were previously identified as young, metal-rich clusters (see the discussion in Caldwell et al. [2]).

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Figure 3.4. Hubble Space Telescope CMDs of a young (B367, left) and an old (B008, right) M31 GC using the data from Perina et al. [37]. The grey points show individual stars within 6′ and 7.5′ of the cluster centers, respectively. These small regions are selected to minimize contamination from the foreground Milky Way stars, background galaxies, and the M31 field stars in the inner halo, disk, or bulge, though some contamination remains in these CMDs. The red lines show isochrones (from [39]) with a single metallicity and varying age. The rough location of the main sequence turnoff (MSTO; the best age indicator for a cluster) is also labeled. In the case of B367, solar metallicity models are used; the best-fitting age of 200 Myr (from Perina et al.) is shown with a solid line. An older age of 500 Myr is also shown with a dashed line, to illustrate how the MSTO moves with age; even considering the uncertainties and the large amount of field star contamination, B367 does indeed look like a young cluster. For B008, the metallicity of [Fe/H] = −1 from Perina et al. is shown, along with ages of 11 ± 4 Gyr. The MSTO is not detectable in this old GC, and the age effects on the RGB are virtually undetectable; this demonstrates the difficulty of determining the ages of old M31 clusters from resolved photometry.

open clusters [40], Milky Way GCs [33], and the massive LMC clusters (also from [33]). The Caldwell et al. M31 sample only contains the most massive, bright clusters—adding in the more complete lower mass catalog from PHAT [24] would populate more of the open cluster mass region in the M31 parameter space, but only for the region of M31 that was observed by PHAT. Also note that the Milky Way open cluster sample may be biased and incomplete, as it only includes nearby open clusters. From the Caldwell et al. sample, it is clear that there are young, massive M31 clusters that, based on their total mass (and brightness), could be classified as

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Figure 3.5. Observed spectra of young M31 GCs from Caldwell et al. [2]. These moderately low-resolution spectra were provided by N. Caldwell (private communication). The GCs all have different absolute brightnesses based on differences in, e.g., mass, but the spectra have been shifted to have similar flux in the red portions of the spectra. The hydrogen Balmer lines are labeled. As GCs age and the massive, blue stars evolve, the peak of the spectral energy distribution shifts redward and the strengths of the Balmer lines change. A cluster of a constant mass will also become fainter with age, as its brightest (most massive) stars evolve and die. It will therefore be easier to identify low-mass clusters when they are younger and brighter. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

Figure 3.6. A figure from Caldwell et al. [2] showing the spatial distributions of young GCs in M31. The background image is an optical Digitized Sky Survey image, with an infrared Spitzer 24 μm image on top in red to highlight regions of active star formation. The clusters with ages < 0.1 Gyr are shown in magenta, those with ages between 0.1 and 0.32 Gyr are shown in blue, and those with ages between 0.32 and 2 Gyr are shown in green. The positions of these young GCs are projected onto the disk and star forming regions, which supports the derived young ages. Copyright AAS, reproduced with permission.

GCs. These young clusters also have similar masses as the young LMC clusters.7 Caldwell et al. particularly identify ten clusters with masses above 10 000 M⊙, three of which they show are very similar to the LMC clusters. 7 This similarity was noted in 1988 by Elson and Walterbos [11], who noticed that the M31 GCs had similar colors to the LMC clusters.

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Figure 3.7. An adaptation of a figure from Caldwell et al. [2], showing the mass distribution of spectroscopically-confirmed clusters in M31 [2] compared to the Milky Way open clusters [40], Milky Way GCs [33], and massive LMC clusters [33]. While many of the young M31 clusters in this sample overlap with the Milky Way open clusters, many are more massive, in the range of the LMC massive clusters and the Milky Way GCs. Note that the lowest mass young M31 clusters are incomplete in the dataset from Caldwell et al. [2]. Copyright AAS, reproduced with permission.

These young, massive clusters provide an opportunity to learn about star cluster formation. With the 2015 catalog of star clusters in the PHAT footprint [24], Johnson et al. [25] calculated a cluster mass function for the 1249 young clusters with ages between 10–300 Myr. They found that the cluster mass function was truncated (i.e. cut off) at a mass ∼104 M⊙, deviating from the distribution of the lower-mass clusters. In other words, there are fewer young massive clusters than predicted by extrapolating the distribution from the lower-mass clusters. They further showed that this cutoff mass varies between galaxies, and is strongly correlated with the amount of star formation in that galaxy. Essentially, Johnson et al. [25] used the young M31 clusters to demonstrate that high-mass clusters can only form during times of intense star formation, in agreement with predictions from models (e.g., [26]). Johnson et al. also argue that the higher-mass GCs should also follow this trend and that the mass distribution of GCs reveals the intensity of star formation when those GCs formed.

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Under this framework, its population of young, massive clusters implies that M31 experienced a burst of intense star formation within the last ∼2 Gyr, which is supported by PHAT observations of disk stars [58]. This high star formation rate allowed a population of massive and low-mass clusters to form. As stated above, the Milky Way does not seem to possess a significant population of similarly young, massive GCs; some key difference between the two galaxies therefore led to recent massive cluster formation in M31, but not the Milky Way. One major difference between M31 and the Milky Way is the presence of the fairly massive spiral galaxy M33 to the south of M31. A prior interaction between M31 and M33 could indeed have triggered a burst of recent star formation. After discovering a stream of stars surrounding M33, McConnachie et al. [32] produced a model of the interaction, demonstrating that M33 could have passed near M31 within the last few Gyr. However, more recent models, some based on cosmological simulations, suggest that a past interaction is unlikely and that M33 is currently on its way to its first encounter with M31 [36, 57]. Many less massive galaxies are currently interacting with M31, as discussed in chapter 1. The compact elliptical galaxy M32 may have fallen into the inner regions within the last few billion years, triggering massive bursts of star formation (e.g., [10]). Similarly, the Giant Stellar Stream (GSS; [23]) is a major feature to the south of M31 (see figure 1.2). As discussed in chapter 1, some models suggest that the GSS has been created from the disruption of a galaxy with a mass similar to the LMC [12] about 1 Gyr ago. McConnachie et al. [31] note that this age is similar to that of the star forming ring in M31. It is therefore possible that the accretion of the GSS progenitor triggered an intense round of recent star formation in M31, creating young GCs that are not found in the Milky Way (though see below).

3.5 The intermediate-age clusters Before continuing on to the old GCs (with ages older than ∼8 Gyr; [4]), which comprise the bulk of M31’s GC system, this section briefly discusses the ‘intermediate-age’ clusters, which have ages from 2–8 Gyr. In the Milky Way, the few clusters in this age range are fairly low-mass (see section 2.1). However, in the last few decades several groups have identified a population of intermediate-age, massive clusters in M31. The more recent analysis by Caldwell et al. [4] shows that most of these clusters are actually misidentified old, metal-poor GCs that were mistaken for younger, metal-rich clusters. As mentioned in section 3.2, it is difficult to determine precise ages for old, distant systems, even when individual stars can be photometrically observed, as in M31, since the CMDs for these systems do not reach the main sequence turnoff (see figure 3.1 and [38]). Caldwell et al. [4] identify only six probable intermediate-age clusters (with another six candidates), all of which are ∼7 Gyr old and have high masses typical of GCs; they find no evidence for clusters with ages between 2 and 6 Gyr. Most of their candidate interemediate-age clusters are metal-rich and close to the center of M31.8 8

Note that Colucci et al. [7] found one GC to have an age of ∼2 Gyr. However, their spectrum had a lower S/N ratio and Caldwell et al. [4] find this GC to be old. Since this cluster’s age has been contested, it is not included here.

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Though it does have a few older intermediate-age, massive GCs, M31 therefore does not have a significant population of these clusters. While many lower-mass clusters likely did form within the last 2–8 Gyr, they have probably since been disrupted. Returning to the earlier framework of Johnson et al. ([25]; see section 3.4), the lack of a significant number of intermediate-age GCs implies that M31 did not experience high enough rates of star formation during the last 2–6 Gyr to form any massive clusters. This hypothesis is consistent with PHAT observations of the M31 disk [58]. The lack of a significant number of intermediate-age massive clusters therefore indicates that M31 did not experience many significant interactions during the last 2–8 Gyr.

3.6 The old clusters The majority of the massive clusters in the M31 system are old. Figure 3.8 shows the spatial distribution of the old inner GCs that were analyzed by Caldwell et al. [4]. Unlike the young clusters, the old GCs do not all lay along the disk; instead, they are distributed more spherically about the center of the galaxy, much like the Milky Way GCs, and are therefore likely associated with the halo (though some may also be associated with the bulge). As with the intermediate-age clusters, ages cannot generally be obtained from resolved photometry. Instead, ages can be determined from IL photometry or spectroscopy. However, the changes in the strengths of spectral features are affected by both age and metallicity (as well as other parameters, such as the color of the evolved horizontal branch stars). Care must therefore be taken to identify specific photometric filters or spectral features that are sensitive to individual parameters (see, e.g., [49]). 3.6.1 Metallicities Figure 3.9 demonstrates how the strengths of spectral lines change with metallicity in low-resolution spectra of old GCs (provided by N Caldwell, private communication). To determine the ages and metallicities of these clusters, Caldwell et al. [4] measured the indices (absorption features in lower-resolution spectra that are blends of multiple spectral lines) that were previously defined in the Lick system [59].9 Though there have been several analyses of large samples of M31 GCs, this section uses the ages and metallicities from Caldwell et al. [4], whose large, homogeneous sample has been carefully analyzed with the best combination of Lick indices to avoid age/metallicity degeneracies (e.g., to avoid mistaking old, metal-poor GCs for young clusters). Figure 3.9 shows the two Fe features that they utilize to derive [Fe/H], along with the Hβ hydrogen Balmer line that is used to derive the age. 9 The Lick indices, originally developed for analyses of old, elliptical galaxies, are named after the Lick Observatory. The indices themselves are related to physical quantities like age and metallicity through calibrations with models. GCs have served as essential tests for the Lick indices, because they are simpler stellar populations than more complicated galaxies (e.g., [15]).

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Figure 3.8. A figure from N Caldwell showing the spatial distributions of old GCs in M31 (from [4]), which are color-coded by metallicity (red shows the most metal-rich GCs, while orange, yellow, green, and blue are progressively more metal-poor). The background image is an optical Digitized Sky Survey image. Figure reproduced by permission of N Caldwell.

As mentioned in section 3.5, Caldwell et al.’s ages and metallicities are occasionally in disagreement with other groups, who identified metal-poor GCs as young—again, this is an issue of age/metallicity degeneracy. The carefully-calibrated, homogeneous sample from Caldwell et al. represents one of the best samples of M31 GC ages. However, despite the high-quality of the analysis, these techniques are not immune to the age/metallicity degeneracy. Of the ∼320 old GCs that Caldwell et al. [4] analyzed, several overlap with other studies, some of which utilized observational techniques that are the least sensitive to the age/metallicity degeneracy, including resolved Hubble Space Telescope analyses [37], medium-resolution observations of metallicity-sensitive calcium features in the near-infrared [47], and high-resolution IL spectroscopic analyses of individual Fe lines [6, 7, 44]. These other studies provide high-quality [Fe/H] ratios, though for most old GCs they cannot provide high-precision ages. The [Fe/H] ratios from these independent studies are generally in excellent agreement with Caldwell et al., which further suggests that the Caldwell et al. ages are reasonably accurate. Figure 3.10 shows the [Fe/H] distribution of the old clusters; the Milky Way distribution from section 2.3.2 is also shown for comparison. Again, it is evident that M31 has many more GCs than the Milky Way. Whereas the Milky Way GC population is clearly bimodal (double-peaked) in metallicity, the M31 distribution is

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Figure 3.9. Observed spectra of old M31 GCs, from Caldwell et al. [4]. These moderately low-resolution spectra were provided by N Caldwell (private communication). The GCs all have different absolute brightnesses based on differences in, e.g., mass, but the spectra have been roughly normalized (the continuum level set to a value of one). The Hβ (an age-sensitive Balmer line) and Fe-sensitive indices are shown; the grey bars show the wavelength ranges for the index definitions [60]. For these old clusters, Caldwell et al. use the Hβ index as an age indicator and the two Fe indices as metallicity indicators. The Ca feature is used to determine the Ca abundance (by [50]; see section 3.6.5). Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

not. Caldwell et al. [4] performed statistical tests to show that the M31 distribution is not well-fit by a single Gaussian function;10 they quote only a 28% chance that the distribution is unimodal (fit by a single Gaussian function), though they note that the distribution is also not well-fit with two Gaussians. Thus, while the Milky Way has two distinct GC populations, based on the [Fe/H] distribution, M31’s GC system appears to be more complex. In addition, figure 3.10 also shows that the relative metallicities are different between the Milky Way and M31: M31 has more metal-rich (high [Fe/H]) clusters than the Milky Way. Indeed, in this sample, the median [Fe/H] is −0.90 ± 0.07 in M31, compared to −1.35 ± 0.14 in the Milky Way. Caldwell et al. [4] further compared the number of metal-poor ([Fe/H] ⩽ −1) and metal-rich ([Fe/H] > −1) GCs in the two systems. In the Milky Way, 67% of the GCs fall into the metal-poor category; in M31, only 48% fall into the metal-poor category. M31 therefore does not just have more GCs than the Milky Way—it has relatively more metal-rich GCs. Figure 3.11 shows the metallicities of the old GCs as a function of their projected radial distance from the center of M31. Both M31 and the Milky Way (figure 2.7(b)) show some evidence for a metallicity gradient in their inner GC populations, where the average metallicity steadily decreases with increasing distance from the center. Recall that in the Milky Way, where the GCs can be clearly split into metal-rich and metal-poor populations, the gradient is more clearly pronounced in the metal-rich population, though it is still apparent in the metal-poor population as well. Alhough

10

Recall that a Gaussian function is a bell-curve.

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Figure 3.10. Top: the distribution of [Fe/H] ratios for old M31 GCs in the Caldwell et al. [4] sample. Bottom: The [Fe/H] distribution for the Milky Way GCs; the figure is similar to figure 2.7(a), except that the GCs beyond 25 kpc from the center of the Milky Way have been removed. The Milky Way has a bimodal GC population, as shown with the two component Gaussian fits. Unlike the Milky Way, M31’s distribution is not well-represented by a two-component Gaussian. The distribution also shows that M31 has more GCs, particularly more metal-rich GCs, than the Milky Way.

the M31 GCs cannot be as clearly separated into distinct populations, in figure 3.10 they are color-coded based on the three metallicity populations identified by Caldwell and Romanowsky [3]. The most metal-rich M31 GCs are radially closer to the center of the Galaxy (and vertically closer to the disk) than the more metal-poor GCs [4]. None of the very metal-rich GCs are located very far from the center. Like in the Milky Way, the intermediate-metallicity and metal-poor GCs are more spherically distributed around M31 and are presumably associated with M31’s halo. The metalpoor GCs appear to be located throughout the inner regions, but the decreasing number of higher metallicity GCs in the outer regions means that the metal-poor GCs become increasingly dominant with increasing distance from the center of M31. The 3-16

The Globular Star Clusters of the Andromeda Galaxy

Figure 3.11. The [Fe/H] ratios of old M31 GCs in the Caldwell et al. [4] sample as a function of their projected distance from the center of M31. The GCs are color-coded according to the three metallicity groups identified by Caldwell and Romanowsky [3]: red circles show GCs with [Fe/H] ⩾ −0.4 , green circles show GCs with −1.5 ⩽ [Fe/H] < −0.4 , and blue circles show GCs with [Fe/H] < −1.5. The solid black line shows the metallicity gradient for all GCs. The dashed vertical line shows Rproj = 25 kpc , the definition for the inner versus outer halo. This chapter only discusses the inner GCs—more will be added to this plot in chapter 4.

changing relative numbers of metal-rich versus metal-poor GCs certainly leads to an overall gradient in the entire GC population, although there do not appear to be significant gradients within each metallicity subpopulation. These results from the GCs are consistent with the results from the M31 field stars. Observations of >1500 red giant branch stars as part of the SPLASH survey demonstrated a clear metallicity gradient throughout the inner halo [16], while PHAT observations show a metallicity gradient in the disk [17].11 As discussed in section 2.3.2, the presence or absence of a metallicity gradient reveals important information about the assembly history of a galaxy. The present-day stars and GCs within a galaxy are the result of a combination of star formation within the larger galaxy and the accretion of dwarf satellites, both of which have different effects on an existing gradient. In the Milky Way, for example, Searle and Zinn [54] interpreted the lack of a strong metallicity gradient in the halo as evidence for dwarf satellite accretion. Similarly, in M31, Gilbert et al. [16] demonstrated that the inclusion of stellar streams, e.g., from the GSS, affects the measurement of a metallicity gradient. Examinations of GC metallicities as a function of distance from the center therefore probe the relative contributions of star formation within M31’s disk compared to the accretion of dwarf satellites. 3.6.2 Ages Caldwell et al. [4] also derived ages for these old GCs, using the strength of the Hβ line (see figure 3.9). Note that this technique does not have the ability to determine 11

Note that in both surveys, the field stars have higher median metallicities than the GCs [3].

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The Globular Star Clusters of the Andromeda Galaxy

Figure 3.12. Ages (in Gyr) versus integrated [Fe/H] for M31 GCs with Rproj < 25 kpc . The grey circles show the clusters from Caldwell et al. [4]: the grey points with error bars are actual measurements, while the blue circles without error bars are the clusters whose ages are set to 14 Gyr, either because they are metal-poor ([Fe/H] < −0.95) or because the derived ages are older than 14 Gyr. The purple stars are from high-resolution optical analyses [6, 7, 44]. The curves for three dwarf galaxies from Leaman et al. [28] are also shown.

accurate cluster ages for GCs below [Fe/H] ∼ −1.12 Although the spectra of these metal-poor GCs indicate that they are old, Caldwell et al. cannot determine an exact age; as a result, they assume an age of 14 Gyr. Caldwell et al. also have a number of clusters whose calculated ages (again, from the strengths of the Hβ line and comparisons with models for how that line changes with age and metallicity) are older than the age of the Universe. This situation is obviously unphysical, and Caldwell et al. therefore adopt an age of 14 Gyr for these clusters. Also note that metallicities are not available for the young clusters from Caldwell et al. [2]; however, those clusters are likely to have solar or supersolar metallicities. Figure 3.12 shows the age-metallicity relation (AMR) for the old M31 GCs in the disk and inner halo, based on IL spectroscopy (also see [5]). The Caldwell et al. [4] GCs whose ages were set to 14 Gyr (see above) are shown with blue circles without error bars. This figure also includes several clusters that were analyzed at high spectral resolution [6, 7, 44]. Although the high-resolution sample is much smaller than the low-resolution sample, the [Fe/H] ratios are much better constrained, for several reasons: (1) individual Fe lines can be resolved, which reduces the random uncertainties in individual measurements; (2) more Fe features can be detected

12 The reason that this technique is uncertain for clusters with [Fe/H] < −1 is because metal-poor GCs generally have blue horizontal branches. Figure 3.1 provides an example of a moderately blue horizontal branch in the Milky Way GC, M3. The color of a GC’s horizontal branch stars (also known as the horizontal branch morphology) is heavily dependent on cluster metallicity, but other factors (e.g., age or helium abundance) are also known to influence the horizontal branch morphology, making it difficult to accurately model the horizontal branch in metal-poor GCs. In clusters without high-quality Hubble Space Telescope photometry (which includes most of the M31 GCs), the horizontal branch morphology is entirely unknown. As a result, because they cannot be well-modeled in unresolved systems, the blue horizontal branch stars in an IL spectrum can be mistaken for young main sequence stars [53].

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(because weaker lines can be observed), which decreases the uncertainty in the mean [Fe/H] ratio; and (3) the strengths of the iron lines are themselves less sensitive to the age. A natural consequence of this latter point is that the uncertainties in the adopted ages are larger in the high-resolution samples, which generally do not examine the same age-sensitive (Balmer) lines as lower-resolution studies. The resulting AMR in figure 3.12 has a similar shape to the Milky Way, but the error bars are necessarily much larger. The oldest GCs cover a wide range of metallicities, from [Fe/H] ∼ −2.8 to +0.5, while metal-rich GCs cover a wide range of ages. The most metal-poor GCs from the high-resolution samples of Colucci et al. [6, 7] and Sakari et al. [44] are all consistent with old ages as expected from the observations of Milky Way GCs. Ultimately, a plot such as this would be useful for unraveling differences in the various metallicity subpopulations and for identifying accreted GCs, as has been done in the Milky Way (e.g., [27, 28]). However, the large error bars on the spectroscopic ages truly limit the usefulness of M31’s AMR. Future analyses will benefit from improvements in models and deeper photometry. The former would allow spectroscopic age techniques like those used by Caldwell et al. to push to more metal-poor GCs; the latter would enable direct detections of horizontal branch morphology or determinations of age from the main sequence turnoff (see figure 3.1). 3.6.3 Masses Masses can also be obtained for the old M31 GCs. Figure 3.13 shows the mass distributions of old M31 GCs (from [56] or [50]) compared to Milky Way open clusters, GCs, and LMC massive clusters (see figure 3.7 for references). These inner clusters fall in the mass range of the Milky Way GCs, and are unlike the Milky Way open clusters. This result is to be expected, given that low-mass old clusters are fainter than younger clusters at the same mass and are therefore harder to detect (though see chapter 4). Furthermore, in the inner regions of M31, one would expect low-mass, old GCs to have been disrupted long ago [42]. Figure 3.13 also shows that, compared to the Milky Way, M31 has more clusters at the highest mass end, some of which are more massive than the most massive Milky Way GCs. The presence of these very high-mass GCs indicates something important about the mass and star formation rate of M31 and the low-mass subhaloes that have built up the Galaxy over time. Recall the paradigm of Johnson et al. ([25]; section 3.4), which was based on observations of lower-mass, young clusters. Johnson et al. found that the maximum mass of a star cluster was connected to the density of star formation in the host galaxy. If this result can be extrapolated to the highest mass GCs, then this difference in the mass distribution implies that M31 had higher rates of star formation than the Milky Way, allowing the formation of these very high-mass clusters. 3.6.4 Kinematics Just like the Milky Way GCs, the motions of M31’s GCs reveal valuable information about the various subpopulations within the GC system. As discussed 3-19

The Globular Star Clusters of the Andromeda Galaxy

Figure 3.13. The same as figure 3.7, but showing the mass distribution of old M31 GCs, based on the ages from Caldwell et al. [4], the dynamical masses from Strader et al. [56], and, for the ∼25% of GCs without dynamical masses, the masses from Schiavon et al. [50], which were calculated from the total luminosity, assuming a constant mass-to-light ratio. A similar figure can be found in Caldwell et al. [4].

in section 3.1, it is more difficult to assess the positions and kinematics of M31’s GCs because they are far away, making it difficult to measure distances or proper motions. As a result, the GCs have to be investigated in terms of their projected distances from the center and their observed radial velocities, rather than their actual 3D locations and motions within M31.13 By examining the radial velocities of the M31 GCs relative to the Galaxy itself, Caldwell and Romanowsky [3] showed that the most metal-rich, old GCs (the population with [Fe/H] > −0.4 ) have disk-like motions, i.e. they seem to move in similar ways to the field stars within the disk. This is indicated by their proximity to the disk (radially and vertically) and the fact that they seem to be rotating with the field stars and gas in the disk, according to results from the SPLASH and PHAT surveys [9]. Caldwell and Romanowsky argue that these GCs are therefore associated with the disk itself (though some may be associated with the bulge as well) and likely formed in the main body of the Galaxy during periods of intense star formation. 13

The Gaia mission is already beginning to provide proper motions of stars in M31 (e.g., [57]); these values will get more accurate with subsequent data releases, and will enable much more accurate kinematics in the M31 system.

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Caldwell and Romanowsky also found that a non-negligible number of the more metal-poor GCs show signs of rotation, even though they are more extended than the metal-rich GCs, are more spherically distributed and seem to be associated with the halo. They show that ∼2/3 of the GCs with [Fe/H] < −0.4 look to be rotating with the central galaxy. This result is distinct from the Milky Way GCs, many of which are not rotating with the bulk of the Galaxy (see, e.g., [19]). Similarly, Dorman et al. [9] found signs of rotation in the field stars in M31’s halo. Any formation scenario for the halo of M31 must therefore yield a GC population whose majority rotates with the host galaxy. Not all of M31’s inner GCs rotate with the Galaxy. Perina et al. [37] identified three metal-rich GCs (with [Fe/H] > −1), which are located farther out than typical metal-rich GCs and have discrepant radial velocities, given their projected locations in M31 (also see [3]). They argued that these GCs could have been accreted from a massive dwarf satellite. They also claim that one of these GCs, B407, may be the remnant nucleus of the dwarf galaxy that created the GSS (see section 4.4.1). Caldwell and Romanowsky [3] add several other targets to this list of potentially accreted GCs based on their metallicities and projected distances from the center. Identifying inner halo GCs that have been accreted based on their positions and radial velocities will only produce a subset of accreted GCs, namely those that have been accreted recently from dwarf galaxies on particular orbits. The detailed abundances of GCs, however, can shed light on the masses of the GCs’ host galaxy. 3.6.5 Calcium abundances Deriving abundances of most individual elements requires spectroscopy. Abundances of some elements can be determined from low-resolution spectroscopy if the lines are strong enough (see figure 3.9); others require observations at high spectral resolution (see figure 2.5). Abundance analysis techniques can differ substantially between individual studies; it is important to remember that every technique has its own systematic errors that could lead to offsets from other studies. For IL spectra, each analysis will provide abundances that have different sensitivities to the adopted age and metallicity of the GC. These uncertainties may themselves be dependent on age, metallicity, or other cluster parameters, so that systematic errors can occur within a given analysis. The papers quoted here (and many others) have attempted to identify and (when possible) quantify these uncertainties as well as possible. Early studies of the abundances of M31’s GCs focused on Mg, which has several strong spectral lines in the optical. These early studies demonstrated that M31 GCs generally had elevated [Mg/Fe] ratios (e.g., [41]), just like stars and GCs in the Milky Way (see figure 2.9). With the low-resolution Caldwell et al. [4] sample of GCs, Schiavon et al. [51] conducted a detailed comparison of line strengths (including Ca- and Mg-sensitive indices) between old M31 and Milky Way GCs. By comparing average spectra of the same age and metallicity, Schiavon et al. could directly assess the differences between the Milky Way and M31 GC systems without using any models (and therefore with a minimum of systematic errors). For this combined sample, they found, in general, no significant differences in line strengths, indicating 3-21

The Globular Star Clusters of the Andromeda Galaxy

Figure 3.14. Integrated [Ca/Fe] ratios as a function of [Fe/H] in inner M31 GCs. The Milky Way field stars are shown with grey points for comparison (see figure 2.9 for references). The abundances from Schiavon et al. [50] are shown with open blue circles: these abundances were derived from Lick indices in low-resolution spectra. The abundances from high-resolution optical spectra are shown with purple stars, using the data from Colucci et al. [6, 7] and Sakari et al. [44]. The green triangles show abundances derived from high-resolution infrared spectra taken as part of the APOGEE survey [44]. Some systematics are evident between the analyses. The outliers are labelled and are described further in the text. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

‘an absence of important differences in chemical composition between the two cluster systems’.14 This suggests that M31’s inner halo, disk, and bulge GCs have experienced a similar chemical evolution history as the Milky Way GCs, across a wide range of metallicities. This comparison by Schiavon et al. [51] is supported by the chemical abundance ratios that have been calculated using various models. Figure 3.14 shows the [Ca/Fe] ratios as a function of [Fe/H] for three different samples of M31 GCs, which are discussed below. Low-resolution abundances from Schiavon et al.: these abundances were derived by Schiavon et al. [50] using the low-resolution spectra from Caldwell et al. [4]. The Ca abundances were derived from a single Ca-sensitive feature (shown in figure 3.9). Since some indices become prohibitively weak in metalpoor GCs and since ages cannot be derived for the metal-poor GCs, their analysis is limited to GCs with [Fe/H] > −0.95. Schiavon et al. also derived Mg abundances, which generally show similar behavior as Ca. High-resolution optical abundances from Colucci et al. and Sakari et al.: Colucci et al. [6, 7] and Sakari et al. [44] analyzed 5, 26, and 5 GCs, respectively, using high-resolution (R ≳ 30 000) optical spectra and a technique that is similar to those used to analyze individual Milky Way stars. Because individual lines can be resolved in these spectra, the abundance ratios have very small 14

See chapter 5 for a discussion of C and N.

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random errors. These papers (and [45]) also show that the systematic errors in [Ca/Fe] are generally very small.15 High-resolution infrared abundances from Sakari et al.: as an ancillary part of APOGEE, a sample of moderately high-resolution (R = 20 000) spectra of M31 GCs were obtained in the infrared. Sakari et al. [44] analyzed 25 GCs that had been previously observed by Colucci et al. [6, 7]. In the infrared, IL spectra of old GCs are largely insensitive to the cluster age, since only the evolved red giant and asymptotic giant branch stars contribute significantly to the infrared IL. Note that the infrared Ca lines are much weaker than the optical Ca lines; as a result, the random errors in the [Ca/Fe] ratios are generally higher in the most metal-poor GCs. These samples all contain overlapping GCs, both for scientific and practical reasons. The overlap allows an individual study to assess possible systematic offsets from other studies. However, the clusters analyzed at high-resolution are necessarily among the brightest GCs (see section 2.2). The duplicates are generally not removed in order to illustrate the systematic offsets that can occur as a result of differences in resolution and wavelength coverage. The resulting distribution in figure 3.14 also shows the Milky Way field stars for comparison. From figure 3.14, it is evident that the low-resolution analysis has provided abundances for more clusters, though the higher-resolution analysis provides higher precision abundances (i.e. [Ca/Fe] ratios with lower random errors) over a greater range in [Fe/H]. The M31 GCs show that in M31 the [Ca/Fe] evolution with [Fe/H] has proceeded very similarly to the Milky Way, with a small number of potentially interesting outliers. One cluster (B457, at [Fe/H] ∼ −1.2) has low [Ca/Fe] for its [Fe/H], while another metal-rich GC (B193, at [Fe/H] ∼ −0.2) has higher [Ca/Fe] than Milky Way field stars. A major benefit of high-resolution analyses is the ability to obtain abundances of many elements, including elements that form in similar ways to Ca, such as O, Mg, Si, and Ti. Though all these elements are categorized as ‘α-elements’, they actually form in slightly different places and at different times (e.g., [35]). Investigating another abundance ratio, such as [Si/Fe] (figure 3.15), can probe whether a GC is uniformly offset in all α-elements, whether the effect is limited to [Ca/Fe], or whether it is an effect only seen in certain α-elements (e.g., the heavier elements like Ti). Figure 3.15 shows that most of the M31 GCs have similar [Si/Fe] ratios to the Milky Way field stars. The two clusters mentioned above also have offset [Si/Fe] ratios, in both the optical and infrared, suggesting that most of the α-elements are likely offset. (There is also an additional cluster with low [Si/Fe], but since it has normal [Ca/Fe], this may be a systematic effect.) Recall that the location of a GC in the [Ca/Fe] (or [Si/Fe]) versus [Fe/H] plot is dependent on properties of its birth environment. Low [Ca/Fe] at a given [Fe/H] is a feature of low-mass dwarf galaxy stars and clusters, which experience slower star 15 For the three GCs in common between the studies, the values from Sakari et al. [44] are utilized instead of those from Colucci et al. [6, 7], though note that the differences between the studies are negligible.

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Figure 3.15. The same as figure 3.14, but for [Si/Fe]. Only the high-resolution samples are shown [6, 7, 44], because Si has not been determined from optical, low-resolution spectra. The clusters that are outliers in [Ca/Fe] are also outliers in [Si/Fe]; there is also an additional cluster with low [Si/Fe] which has ‘normal’ [Ca/Fe].

formation and chemical enrichment than massive galaxies. The metallicity at which a galaxy’s [Ca/Fe] starts to decrease (the ‘knee’ in the plot) changes with galaxy mass; lower mass galaxies have more metal-poor knees than more massive galaxies, as shown in figure 2.9. B457’s low [Ca/Fe] and [Si/Fe] ratios could indicate formation in a lowmass dwarf galaxy that is currently being accreted into M31, a result that is further supported by the [Mg/Fe] ratios from Colucci et al. [7].16 However, it is worth noting that B457 had the lowest S/N spectrum in the Colucci et al. sample, and was the lowest mass cluster (according to the total magnitude and velocity dispersion). It is therefore possible that B457’s α-abundances are systematically too low. Additional follow-up observations to achieve a higher S/N spectrum would help to assess whether B457 truly has the chemical signature of a dwarf galaxy. Additional evidence from B457’s kinematics or proximity to stellar streams could further help establish its birth site. The other outlier, B193, has high [Ca/Fe] and [Si/Fe] ratios relative to Milky Way disk stars, both in the optical and infrared. It is interesting to speculate that B193’s high [Ca/Fe] and [Si/Fe] ratios could indicate formation during an early period of rapid, intense star formation, especially since B193 is the only GC in the highresolution sample that falls in the most metal-rich population (with [Fe/H] > −0.4 ) and does lie along the disk. However, the low-resolution [Ca/Fe] ratio from Schiavon et al. [50] is not elevated. Furthermore, Colucci et al. [7] found an age of 8 Gyr for B193, whereas Caldwell et al. [4] found B193 to be 12.9 Gyr. It is possible that the age difference could explain the difference between the optical high- and low-resolution analyses, though the infrared abundances (which are also high) should be much less sensitive to the adopted age. B193 is the also most metal-rich cluster in the highresolution sample and may be subject to systematic errors that are not present in the 16 Note that Colucci et al. [7] found elevated [Ti/Fe] in B457, albeit with large error bars. They therefore argue that the low [Ca/Fe] may be due to a systematic effect.

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more metal-poor clusters. In their IL analysis of Milky Way GCs, Colucci et al. [8] note that their most metal-rich Milky Way GC also had a lower age and higher [Ca/Fe] and [Si/Fe] ratios than expected. This suggests that additional work should be done with very metal-rich GCs in order to interpret the derived abundances. With the exceptions of B193 and B457 (and possibly a few clusters in the lowresolution sample), the [Ca/Fe] ratios for the inner halo, disk, and bulge M31 GCs are generally consistent with the Milky Way field stars. Given that these GCs are all old, this indicates that the early phases of chemical enrichment proceeded similarly in the Milky Way and M31. For the GCs that may have been accreted, such as B403 [37], these abundances place constraints on the masses of the potential host galaxies. Colucci et al. [7] found a normal [Ca/Fe] = 0.26 ± 0.04 for B403, at [Fe/H] = −0.80. If B403 and these other GCs were accreted, they must have come from a fairly massive galaxy, at least as big as the LMC.

3.7 Summary and a comparison with Milky Way GCs This chapter has provided a very brief summary of the tools and techniques that are used to study the stellar populations in M31 through observations of GCs, as well as the scientific results that have emerged from the observations. Throughout, emphasis has been placed on comparisons with the Milky Way GCs and possible explanations for the similarities and differences between the two GC systems. Below, the main results for the inner M31 GCs are summarized. M31 has more GCs than the Milky Way: the precise number of M31 GCs fluctuates depending on how GCs are defined and whether candidate GCs are included. By conservative estimates, however, M31 has at least 3 times as many GCs as the Milky Way. This difference would be consistent with M31 having a higher mass. However, various studies have shown that two galaxies have roughly equal masses (see chapter 1). M31 has more metal-rich and more massive GCs than the Milky Way: the very metal-rich GCs (with [Fe/H] > −0.4 ) are likely associated with M31’s disk, as indicated by their spatial distribution along the disk and their rotation with the disk stars. The excess of these clusters seems to indicate that the disk of M31 has experienced higher rates of star formation than the Milky Way, both for young and old clusters. The [Ca/Fe] and [Si/Fe] abundances of B193, the only GC from this population in the high-resolution sample, are consistent with a period of early, rapid star formation. However, more work needs to be done to understand the systematic uncertainties that can occur in analyses of very metal-rich GCs. A larger sample size of highresolution abundances of metal-rich GCs that could be associated with the disk would also help to address these questions. M31 has a population of young, massive clusters that is not present in the Milky Way: the presence of these clusters implies that M31 has experienced more intense star formation than the Milky Way in the last 2 Gyr. Star formation

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could have been triggered through an interaction with another galaxy (e.g., the massive galaxy M33 or the dwarf galaxy that created the GSS). M31 has more intermediate-metallicity and metal-poor GCs: although they seem to be distributed spherically around the center of M31, a significant number of these more metal-poor GCs (with [Fe/H] < −0.4 ) look to be rotating with the main galaxy. There is also a net metallicity gradient in the GC sample (though the median GC metallicity is lower than the median metallicity of the field stars). These findings seem to suggest that a non-negligible number of the GCs in the inner halo either formed in the body of M31 (the in situ scenario) or formed in 1-2 massive dwarf galaxies that were later accreted but happened to be rotating around M31 with the field stars. The [Ca/Fe] abundances (and, in a handful of cases, the ages) of the majority of these GCs also indicate that they had to have formed in a fairly massive galaxy. The Milky Way does not have a similar dominant population of rotating metal-poor GCs. This could mean that M31 experienced higher rates of star formation early on, creating more massive metal-poor and intermediatemetallicity GCs that have survived to the present day; or it could mean that M31 has accreted more massive satellites. Indeed, the presence of the GSS strongly suggests that M31 is in the process of accreting a satellite about the mass of the LMC. This massive galaxy likely brought in many of the GCs in the inner region, or triggered high rates of star formation in M31.17 There are signs that several inner M31 GCs were accreted: one moderately metalpoor ([Fe/H] ∼ −1.2) GC in this section, B457, looks to have low [Ca/Fe] and [Si/Fe], relative to the other M31 GCs and the Milky Way field stars and GCs. This is a chemical signature of a low-mass dwarf galaxy and could indicate that the accretion of lower-mass satellites is also contributing to the build-up of M31’s inner regions. Although these abundances could reflect uncertain systematic effects, it is possible that some low-mass satellites could have brought GCs into the inner regions of M31, as will be discussed in chapter 4. Alternatively, B457 could actually be located in the outer regions, even though it is currently projected into the inner regions. More metal-poor GCs could also have originated in low-mass systems, but the chemical abundances of metal-poor stars and GCs are very similar between massive and low-mass systems. A look at figure 2.9 shows that the majority of the stars and GCs in low-mass galaxies are indeed metal-poor. Ultimately, however, low-mass accretion is expected to dominate more in the outer regions, because higher mass satellites are brought closer in to the center of the Galaxy as they are disrupted [1]. The relative importance of accretion from low-mass satellites will therefore likely change in the outer regions, beyond R proj = 25 kpc . These GCs will be discussed in chapter 4.

17

Also recall that the Milky Way may have experienced an early merger with a fairly massive satellite [21].

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References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44]

Amorisco N C 2017 Mon. Not. R. Astron. Soc. 464 2882 Caldwell N, Harding P, Morrison H, et al. 2009 Astron. J. 137 94 Caldwell N and Romanowsky A J 2016 Astrophys. J. 824 42 Caldwell N, Schiavon R, Morrison H, et al. 2011 Astron. J. 141 61 Chen B, Liu X, Xiang M, et al. 2016 Astron. J. 152 45 Colucci J E, Bernstein R A, Cameron S, et al. 2009 Astrophys. J. 704 385 Colucci J E, Bernstein R A and Cohen J G 2014 Astrophys. J. 797 116 Colucci J E, Bernstein R A and McWilliam A 2017 Astrophys. J. 834 105 Dorman C E, Guhathakurta P, Fardal M A, et al. 2012 Astrophys. J. 752 147 D’Souza R and Bell E F 2018 Nat. Astron. 2 737 Elson R A and Walterbos R A M 1988 Astrophys. J. 333 594 Fardal M A, Babul A, Geehan J J, et al. 2006 Mon. Not. R. Astron. Soc. 366 1012 Fouesneau M, Johnson L C, Weisz D R, et al. 2014 Astrophys. J. 786 117 Galleti S, Federici L, Bellazzini M, et al. 2004 Astron. Astrophys. 416 917 Gibson B K, Madgwick D S, Jones L A, et al. 1999 Astron. J. 118 1268 Gilbert K M, Kalirai J S, Guhathakurta P, et al. 2014 Astrophys. J. 796 76 Gregersen D, Seth A C, Williams B F, et al. 2015 Astron. J. 150 189 Harris W E 1996 2010 edition Astron. J. 112 1487 Harris W E 2001 ed L Labhardt and B Binggeli Saas-Fee Advanced Course 28: Star Clusters 223 Harris W E, Harris G L H and Alessi M 2013 Astrophys. J. 772 82 Helmi A, Babusiaux C, Koppelman H H, et al. 2018 Nature 563 85 Hubble E 1932 Astrophys. J. 76 44 Ibata R, Irwin M, Lewis G, et al. 2001 Nature 412 49 Johnson L C, Seth A C, Dalcanton J J, et al. 2015 Astrophys. J. 802 127 Johnson L C, Seth A C, Dalcanton J J, et al. 2017 Astrophys. J. 839 78 Kruijssen J M D 2012 Mon. Not. R. Astron. Soc. 426 3008 Kruijssen J M D, Pfeffer J L, Reina-Campos M, et al. 2019 Mon. Not. R. Astron. Soc. 486 3180 Leaman R, VandenBerg D A and Mendel J T 2013 Mon. Not. R. Astron. Soc. 436 122 Mackey A D, Ferguson A M N, Huxor A P, et al. 2019 Mon. Not. R. Astron. Soc. 484 1756 Mayall N U and Eggen O J 1953 Publ. Astron. Soc. Pac. 65 24 McConnachie A W, Ibata R, Martin N, et al. 2018 Astrophys. J. 868 55 McConnachie A W, Irwin M J, Ibata R A, et al. 2009 Nature 461 66 McLaughlin D E and van der Marel R P 2005 Astrophys. J. Suppl. Ser. 161 304 McWilliam A and Bernstein R A 2008 Astrophys. J. 684 326 McWilliam A, Wallerstein G and Mottini M 2013 Astrophys. J. 778 149 Patel E, Besla G and Sohn S T 2017 Mon. Not. R. Astron. Soc. 464 3825 Perina S, Federici L, Bellazzini M, et al. 2009 Astron. Astrophys. 507 1375 Perina S, Galleti S, Fusi Pecci F, et al. 2011 Astron. Astrophys. 531 A155 Pietrinferni A, Cassisi S, Salaris M, et al. 2004 Astrophys. J. 612 168 Piskunov A E, Schilbach E, Kharchenko N V, et al. 2008 Astron. Astrophys. 477 165 Puzia T H, Perrett K M and Bridges T J 2005 Astron. Astrophys. 434 909 Reina-Campos M, Kruijssen J M D, Pfeffer J, et al. 2018 Mon. Not. R. Astron. Soc. 481 2851 Sakari C M, Shetrone M, Venn K, et al. 2013 Mon. Not. R. Astron. Soc. 434 358 Sakari C M, Shetrone M D, Schiavon R P, et al. 2016 Astrophys. J. 829 116

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[45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60]

Sakari C M, Venn K, Shetrone M, et al. 2014 Mon. Not. R. Astron. Soc. 443 2285 Sakari C M, Venn K A, Mackey D, et al. 2015 Mon. Not. R. Astron. Soc. 448 1314 Sakari C M and Wallerstein G 2016 Mon. Not. R. Astron. Soc. 456 831 Sarajedini A, Bedin L R, Chaboyer B, et al. 2007 Astron. J. 133 1658 Schiavon R P 2007 Astrophys. J. Suppl. Ser. 171 146 Schiavon R P, Caldwell N, Conroy C, et al. 2013 Astrophys. J. 776 L7 Schiavon R P, Caldwell N, Morrison H, et al. 2012 Astron. J. 143 14 Schiavon R P, Faber S M, Rose J A, et al. 2002 Astrophys. J. 580 873 Schiavon R P, Rose J A, Courteau S, et al. 2004 Astrophys. J. 608 L33 Searle L and Zinn R 1978 Astrophys. J. 225 357 Sneden C 1973 Astrophys. J. 184 839 Strader J, Caldwell N and Seth A C 2011 Astron. J. 142 8 van der Marel R P, Fardal M A, Sohn S T, et al. 2019 Astrophys. J. 872 24 Williams B F, Dolphin A E, Dalcanton J J, et al. 2017 Astrophys. J. 846 145 Worthey G, Faber S M, Gonzalez J J, et al. 1994 Astrophys. J. Suppl. Ser. 94 687 Worthey G and Ottaviani D L 1997 Astrophys. J. Suppl. Ser. 111 377

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The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 4 The outer halo clusters

Learning goals After completing this chapter, readers will be able to: • Describe the contents of the outer halo of the Andromeda Galaxy (M31). • Summarize some similarities and differences between M31 inner and outer halo globular clusters (GCs). • Outline a possible assembly history for M31, as revealed by its outer halo GC population. • List several open questions that remain about M31’s outer halo.

4.1 The outer halo The outer halo GCs are defined to have R proj > 25 kpc [37]. Chapters 2 and 3 emphasized that the inner and outer regions of a galaxy could have different formation channels. Models suggest that higher-mass dwarfs may be more likely to sink to the central regions of massive galaxies as they are accreted (e.g., [1]). Consequently, the accretion of lower-mass dwarf galaxies should become relatively more important in the outermost regions. Streams from an infalling satellite galaxy can also survive for longer before being disrupted than in the inner regions (as a result of differing dynamical time scales). As a result, intact streams should be more prevalent and bright in the outer halo, as seen in figure 1.2. The shape and location of these streams are also sensitive to the orbit and infall time of the satellites [31]. Unlike the inner regions, the outer halo therefore offers the unique opportunity to link individual GCs to stellar streams, revealing valuable information about the dwarf satellites that are actively building up the outer halo. Observationally, the outer halo GCs offer some advantages over the clusters that are located farther in. The outer halo is a less populated place, devoid of significant gas, dust, or stars. One consequence of this is that there are fewer contaminating M31 field stars than in the inner regions (e.g., compare figure 3.1 to figure 3.4), making it easier to identify low-mass or sparse clusters and to analyze resolved doi:10.1088/2053-2571/ab39dech4

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The Globular Star Clusters of the Andromeda Galaxy

Figure 4.1. A map of the outer regions of M31, based on the image in figure 1.2, from McConnachie et al. [42]. The solid grey line shows the boundaries of the observations and the dashed magenta circles show projected distances of 50, 100, and 150 kpc from the center of M31 and 50 kpc from the center of M33. The black ellipses show the extent and orientation of the disks of M31 and M33. Individual named streams (bright regions with obvious overdensities) are shown in green and the names of these features are given in the legend. The intact satellite dwarf galaxies are shown in blue, with names written next to them (e.g., Andromeda I, or And I, and so on). Finally, the GCs with projected distances Rproj > 2° (27.3 kpc) are shown as red dots. Copyright AAS, reproduced with permission.

color-magnitude diagrams (CMDs) of the brightest cluster stars.1 A consequence of the outer halo’s lower density of M31 field stars is that these regions were not observed in much detail until the 21st century. It took deep imaging programs like PAndAS and its immediate predecessors to discover the wealth of complexity in the outer halo.

4.2 The contents of the outer halo Figure 4.1 shows a map of notable features in the outer halo from McConnachie et al. [42]. Roughly speaking, the stars in M31’s outer halo can be divided into four different groupings. 1 Of course, contamination from foreground Milky Way stars is still a problem that becomes increasingly worse in the northern parts of the outer halo which start to approach the Milky Way disk.

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1. Substructure: visually, the most striking feature of the outer halo is the bright substructure which is labeled in green in figure 4.1. These bright streams of stars are identifiable as discrete structures (e.g., see figure 1.2) and have been named based on their locations relative to the center of M31. The brightest of the streams is the Giant Stellar Stream (GSS), which was first introduced in chapter 1. The named substructure is readily identifiable in optical images, but the majority of the substructure in the outer halo is not clearly associated with a bright stream. McConnachie et al. [42] find that although 69% of the stellar mass in M31’s outer halo is found in substructure, only 10% is obviously associated with the bright named features shown in figure 4.1. The rest (e.g., fainter clumps of stars) is considered ‘amorphous’ substructure.2 These stellar streams are caused by recent accretion events when a lowermass satellite galaxy fell into the larger gravitational potential of M31. The stars in these streams could be from the dwarf galaxies themselves, as the incoming dwarf was ripped apart by the massive galaxy, or they could be from M31’s disk, pulled out by the gravitational influence of the dwarf galaxy. Although the named streams in figure 4.1 appear to be discrete features, they may not be from separate systems (i.e., some of the streams may have been created by the same event). The named streams might also be connected to some of the amorphous substructure. Over time these streams will dissipate, much like low-mass star clusters. The named streams in figure 4.1 must have been created within the last few billion years. There may also be older, fainter, and more diffuse substructure that is not visible in the PAndAS images but could be detected with future observations. 2. A ‘smooth’ component: the outer halo stars that are not obviously part of any substructure are found in the ‘smooth’ halo component. These stars do not exhibit any obvious spatial overdensities that would indicate the presence of a stellar stream, but, as mentioned above, this smooth component could consist of undetectable substructure from older accretion events. McConnachie et al. [42] found that the smooth halo makes up 27% of the stellar mass of the outer halo. According to Ibata et al. [29], the smooth component is predominantly made of metal-poor stars, with [Fe/H] ≲ −1.7. 3. Intact dwarf galaxies: the intact dwarf galaxies (shown in blue in figure 4.1) were briefly introduced in chapter 1. Recall that although M33, NGC 205, and M32 are the dominant satellites, by mass. There are about thirty lower mass satellites throughout the outer region, many of which were discovered by PAndAS. These newly discovered systems are identified by Roman 2 Note that it can be difficult to discover similar streams in the Milky Way, due to the Sun’s location within the Galaxy. In the Milky Way, low surface brightness streams in the outer halo (like those discovered around M31) are obscured by intervening stars, gas, and dust. The entire M31 galaxy can be searched much more quickly and completely than the Milky Way. However, once streams are identified in the Milky Way (see [30] for a recent example) they can be more easily followed-up and characterized. Fainter substructure can also be more easily identified in the Milky Way.

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numerals (e.g., Andromeda I, or And I, etc). M31 also has additional satellites (e.g., IC 10) that have projected radii beyond 150 kpc and that are not visible in the PAndAS images [41]. Ibata et al. [28] have shown that about half of these satellite galaxies are contained in a ‘vast, thin plane’ (see section 1.1.1) whose origin is still debated. The intact dwarf galaxies could be responsible for a small amount of the current substructure in the outer halo. McConnachie et al. [42] show that in the region from 27.3 < R proj < 150 kpc (which excludes M33), intact dwarf galaxies account for only ∼4% of the total outer halo stellar mass. This 4% is dominated by the dwarf ellipticals NGC 147 and NGC 185; the other dwarfs account for only 0.2% of the outer halo mass. Because of their low masses, these outer halo dwarfs are unlikely to have created all of the streams in M31’s outer halo. However, it is worth noting that all of the dwarf satellites have had complicated orbits around M31, and their current locations do not reflect their previous orbital properties. For instance, although M33 is far from the center of M31, it may have had a previous passage closer to M31 that could have created some of the substructure that is present in the outer halo today (see the discussions throughout chapter 3). The tidal tails surrounding M33 (visible in figure 4.1) are one indication that a previous interaction has occurred (e.g., [43]) though many other studies argue that M33 is on its first encounter [55]. The same may be true for NGC 147 and NGC 185 [42]. Similarly, although M32 and NGC 205 are currently located in the inner regions (figure 1.1), they may have disturbed M31’s disk and created stellar streams in the outer halo during their infall. It is therefore possible that the substructure was created by dwarf galaxies that are no longer present in the outer halo. 4. GCs: figure 4.1 also shows the GCs with projected distances greater than 2◦ (about 27.3 kpc) from the center of M31. Mackey et al. [37] found that there are 92 M31 GCs with R proj > 25 kpc , extending as far out as 150 kpc. Although these GCs comprise only 0.1% of the stellar mass of the outer halo [42], they form the primary subject of this chapter. Like in chapter 3, the GCs provide valuable constraints on the ages, masses, and chemical compositions of their host galaxies. Unlike in chapter 3, the GCs that are currently in M31’s outer halo can possibly be directly linked to their birth galaxies. Mackey et al. [37, 39] showed that several of the outer halo GCs lie along stellar streams, in projection, and that this spatial agreement is unlikely to be random. They found that 35%–62% of the outer halo GCs are likely to be associated with the visible substructure, indicating that a significant number originated in a dwarf galaxy and are being accreted along with the field stars. A number of the GCs (and stars) could also have originated in M31’s disk and were ejected due to encounters with dwarf galaxies. Linking the outer halo GCs to their birth galaxies can therefore put valuable constraints on the past assembly of M31’s outer halo.

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Although the outer halo contains a number of stars, there is very little gas. Gas is a valuable tracer of interactions between massive, gas-rich galaxies and provides complementary information to the stellar observations. However, Lewis et al. [35] compared the distribution of cool hydrogen gas to the distribution of stars from PAndAS, finding that most of the gas is not associated with substructure. This lack of gas implies that most of the progenitors of the streams either were not gas-rich or lost their gas early on in the merger. Some gas may be associated with the GSS, but Lewis et al. argued that the majority seems to be associated with M33, suggesting that there may have been a possible interaction in the past [35]. The lack of significant gas also means that there is no ongoing star formation. As a result, there should not be many young stars or GCs in the outer halo. It is important to remember that these PAndAS maps have only been able to detect the brightest stars in M31, which are primarily the evolved giant stars (i.e. the brightest stars in old stellar populations; see figure 3.1). Lower mass galaxies, star clusters, or substructure made of fewer bright stars would be difficult to detect in the PAndAS dataset.

4.3 The outer halo GC system In this section, the outer halo GC system is considered as a whole. Associations with individual streams are discussed in section 4.4. 4.3.1 Locations and brightnesses Mackey et al. [37] provide a summary of the known properties of the outer halo GCs. Of the 92 clusters in their compilation, they found that 32 (35%) have a high likelihood of being associated with substructure, based on their positions and kinematics. In other words, 35% of the GCs are located along a stream, look to be moving with a stream, or look to be moving with other clusters. Another 25 GCs (27%) have an ambiguous classification where it is unclear whether or not they are associated with any stellar streams. Some of these GCs could be associated with the ‘amorphous’ substructure, particularly if there is a high density of stars surrounding the GC. The remaining 35 (38%) GCs that are not associated with any substructure may be associated with the smooth halo component. Mackey et al. also show that all of the outer halo GCs, including those that are associated with substructure, have a similar radial distribution as the more metal-poor field stars ([Fe/H] < −1.1). In other words, the distribution of GCs as a function of projected distance from the center of M31 is similar between the GCs and the more metal-poor field stars. This similarity suggests that many of the outer halo GCs, even those that are associated with substructure, could have originated in the same environment as the more metalpoor field stars. These metal-poor stars are found both in substructure and in the smooth component. Masses have not yet been determined for these outer halo GCs, but the total absolute magnitudes (MV) of the clusters provide a rough indication of cluster mass, where brighter clusters (those with smaller absolute magnitudes) are typically more 4-5

The Globular Star Clusters of the Andromeda Galaxy

Figure 4.2. The total visual magnitudes, MV, of M31 clusters (top) and Milky Way clusters (bottom). The inner halo sample from Caldwell et al. [5, 7] is shown in purple, while the outer halo sample from Mackey et al. [37] is shown in green. The yellow shows the extended clusters (see the text). Note that the Caldwell et al. sample does not include the fainter clusters discovered by the PHAT survey; including those clusters would increase the number of low-mass clusters at the faint end of the sample in the inner regions. The inner regions of M31 contain more of the very bright clusters (in projection), although there is at least one in the outer halo (the massive cluster G1; see chapter 5).

massive.3 Figure 4.2 shows the absolute magnitude distribution of inner and outer halo M31 and Milky Way GCs based on the samples from Caldwell et al. ([5, 7], for the inner M31 GCs), Mackey et al. ([37], for the outer halo M31 GCs), and Harris 3

Note that the age and metallicity of a GC can also affect its MV.

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et al. ([23], for the Milky Way GCs). This comparison highlights several important findings: • There are more GCs in the inner regions than in the outer halo, both in M31 and in the Milky Way. • In M31, there is only one very bright (massive) cluster that is obviously in the outer halo (the cluster G1) while there are several in the inner regions (in projection). • Huxor et al. [25] and Mackey et al. [37] argued that the brightness distribution of the outer halo GCs is bimodal (i.e. double peaked). There is therefore a relative excess of faint clusters in the outer regions. • Although there are many fewer GCs in the outer regions of the Milky Way, the general brightness distribution is similar to the distribution of outer halo GCs in M31 (though the Milky Way does not have a similarly bright G1 in its outer regions). It is also worth remembering that there is an age effect within the magnitude (and mass) distributions of the inner GCs. A comparison of figures 3.7 and 3.13 show that the old GCs in the Caldwell et al. [7] sample are generally more massive than the young GCs [5]. Many of the fainter inner GCs in figure 4.2 are classified as young by Caldwell et al. [5]. This could indicate that the outer halo GCs are similarly young (see below) or it could reflect the different environment of the outer halo, where sparse, low-mass clusters can live longer without being disrupted. It is also worth noting that with the exception of the brightest cluster, G1 (which Mackey et al. classify as a ‘substructure’ GC), the brighter outer halo GCs are typically found in the ‘smooth’ GC group. Figure 4.2 also highlights the magnitude distribution of a fairly new population of clusters known as ‘extended clusters’ that were first identified by Huxor et al. [26]. Although two of the original three extended clusters have R proj < 25 kpc , they may have actual 3D distances from the center that are greater than 25 kpc (see below). These extended clusters have total luminosities typical of GCs (as evident from figure 4.2), and yet they are physically much larger (they have larger radii) and more dispersed than typical GCs. From Hubble Space Telescope CMDs, Mackey et al. [38] showed that four of these GCs look to be old and metal-poor, like typical outer halo GCs. Huxor et al. [26] also demonstrated that these objects would be more easily disrupted than centrally concentrated GCs, and that extended clusters within ∼25 kpc would be more easily destroyed. This could explain why no extended clusters are seen in the innermost regions. The extended clusters thus seem to be very similar to GCs, at least in terms of total mass and their stellar populations, even though they populate the parameter space between classical GCs and galaxies [26]. Their connection with galaxies is still an open question. Mackey et al. [37] also showed that the extended clusters are found both in substructure and in the smooth halo. These objects could therefore be important for understanding galaxy and GC formation. The single, bright, outer halo cluster, G1, deserves more discussion. It seems to possess an iron spread (e.g., [45]) and may be the former nucleus of a now-disrupted 4-7

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dwarf. If G1 was indeed once a nuclear star cluster, its progenitor was likely to have been fairly massive. Based on studies of more distant galaxies, Sánchez-Janssen et al. [52] found that very few low-mass dwarf galaxies (i.e. less massive than the Fornax dwarf spheroidal galaxy) have nuclear star clusters. If G1 is a nuclear star cluster, it must have originated in a fairly massive dwarf galaxy. This will be discussed in more detail in section 5.4.1. 4.3.2 Metallicities and ages Because many of the outer halo GCs have only been discovered in recent years as a result of large dedicated photometric surveys like PAndAS [25], these GCs were not included in the homogeneous sample of Caldwell et al. [5, 7]. Therefore, the results in this section have been compiled from multiple sources, which utilize different observational methods and analysis techniques. The distribution of [Fe/H] ratios from the outer halo GCs is compared to the inner halo GCs in figure 4.3(a). The sources for these [Fe/H] ratios are described below. In the case of overlapping targets, priority is given in the following order. Note that the observational techniques vary between the different samples. 1. Colucci et al. [13] and Sakari et al. [50] determined ages and metallicities for nine GCs from high-resolution, optical spectroscopy. These high-precision [Fe/H] ratios are determined directly from individual Fe lines and are fairly insensitive to GC age. 2. Sakari et al. (in preparation) determined [Fe/H] ratios for nine clusters from near-infrared, moderate-resolution spectra of the metallicity-sensitive calcium triplet lines [2], using an empirical calibration4 [51] to convert line strengths to [Fe/H] ratios. This technique is also relatively insensitive to cluster age for old GCs [51]. 3. Mackey et al. [40] determined metallicities for two low-mass GCs, PAndAS 7 and -8 (hereafter PA-7 and PA-8), from resolved Hubble Space Telescope photometry similar to figure 3.1. Their [Fe/H] determination was based primarily on comparisons with Milky Way GCs. 4. Wang et al. [57] obtained IL photometry of 53 GCs with a wide wavelength coverage and determined ages and metallicities from population synthesis models.5 Wang et al. explain the advantages of such wide wavelength coverage in overcoming degeneracies in age and metallicity. Figure 4.3 includes 33 GCs from this paper. Figure 4.3(a) shows that the outer halo GCs are on average more metal-poor than the inner GCs, although there may still be some fairly metal-rich GCs. Wang et al. [57] found GCs with metallicities up to [Fe/H] ∼ −0.2, several of which are sparse 4

An empirical relation is one that has been determined based on observations of real clusters, rather than one based on theory. 5 Population synthesis modeling involves creating (synthesizing) artificial stellar populations and investigating the behavior of various observables, e.g., line strengths, as a function of cluster parameters like age and metallicity. Population synthesis therefore relies on models of stellar populations.

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Figure 4.3. The same as figures 3.10(a) and 3.11, with the addition of outer halo GCs with measured metallicities. A large, homogeneous sample like that of Caldwell et al. [7] is not available for the outer halo GCs; as a result, these metallicities have been derived with several different methods (see the text), and there are likely unquantified systematic uncertainties between studies. Top: the [Fe/H] distribution of the outer halo GCs is shown in blue on top of the inner halo GCs, which are shown in grey. Bottom: the gradient in [Fe/H]. As in figure 3.11, the points in the bottom plot are colored according to [Fe/H], where red circles show GCs with [Fe/H] ⩾ −0.4 , green circles show GCs with −1.5 ⩽ [Fe/H] < −0.4 , and blue circles show GCs with [Fe/H] < −1.5 (the metallicity groups from Caldwell and Romanowsky [6]). The points with black circles show low-mass, sparse GCs that Wang et al. found to be young and metal-rich from IL photometry; these clusters may be victims of the age-metallicity degeneracy, as discussed in chapter 3. The addition of the outer halo GCs has had a minimal effect on the overall metallicity gradient (black solid line). The dashed black line shows Rproj = 25 kpc , the defined limit between the inner and outer halo.

and low-mass, and therefore may be subject to additional systematic uncertainties. However, GCs with [Fe/H] > −1 are also found in samples from Sakari et al. [50] and Chen et al. [9], indicating that some fairly metal-rich GCs likely do reside in the outer halo. Mackey et al. [37] also showed that several outer halo GCs have very red colors, which could indicate metallicities as high as [Fe/H] ∼ −0.9. 4-9

The Globular Star Clusters of the Andromeda Galaxy

The metallicities are shown as a function of projected distance from the center of M31 in figure 4.3(b). The addition of the outer halo GCs leads to a minimal change in the overall [Fe/H] gradient. There appear to be no significant gradients within the individual [Fe/H] subpopulations identified by Caldwell and Romanowsky ([6]; shown as red, green, and blue points). Instead, the overall gradient looks to be caused by changing relative numbers of GCs in the metallicity subpopulations as a function of distance from the center. Of course, it is difficult to assess the presence of a radial gradient with projected distances; any gradient would be more evident with actual 3D distances, rather than projected values. For the field stars in M31, Gilbert et al. ([21], from SPLASH) and Ibata et al. ([29], from PAndAS) showed that there is a rather sharp metallicity gradient out to a distance of ∼100 kpc; beyond that point, Gilbert et al. found some evidence for a flattening in the gradient. Both papers showed that this gradient was present even when the stellar streams were included. As mentioned in chapter 3, the field stars from Gilbert et al. are on average more metal-rich than the GCs, a trend which continues into the outer halo. This metallicity difference between the field stars and the GCs may be due to the presence of the metal-rich GSS, which dominates the maps of the outer halo [29]. Although it is possible that some of the outer halo GCs were also accreted along with the GSS progenitor (see section 4.4.1), recall that most of the outer halo GCs have a similar radial distribution as the more metal-poor stars. Ultimately, more work needs to be done to assess the presence of a metallicity gradient in the M31 GCs. The ages for these GCs are, in general, not as reliable as those shown in chapter 3 due to the small sample sizes in each paper, potential age/metallicity degeneracies, and the assortment of analysis techniques. Figure 4.4 shows M31’s AMR with the addition of outer halo GCs from the high-resolution spectroscopic studies [13, 50].

Figure 4.4. Ages (in Gyr) versus integrated [Fe/H] for M31 GCs with Rproj ⩽ 25 kpc (purple stars and open grey circles) and outer halo GCs with Rproj > 25 kpc (green stars). The circles show the clusters from Caldwell et al. [7]; the grey points with error bars are actual measurements, while the blue circles without error bars are the clusters whose ages are set to 14 Gyr, either because they are metal-poor ([Fe H] < −0.95) or because the derived ages are older than 14 Gyr. The purple and green stars are from high-resolution optical analyses [12, 13, 49]. The curves for three dwarf galaxies from Leaman et al. [34] are also shown.

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While it is tempting to speculate that the outer halo GCs could be slightly younger than the inner GCs at the same metallicity, it is important to remember that with such small sample sizes the results are highly biased. However, it is worth noting that in a resolved, photometric analysis of 23 M31 GCs, Perina et al. [46] found evidence that several outer halo M31 GCs were ∼1 − 2 Gy r younger than typical Milky Way GCs. Similarly, in their analysis of PA-7 and -8, Mackey et al. [40] argued that those two clusters were likely to be younger than typical Milky Way GCs, based on their horizontal branches. Ultimately, more homogeneous analyses on large samples of outer halo GCs are necessary to truly assess any differences in the AMRs between the inner and outer regions. 4.3.3 Kinematics Veljanoski et al. [56] performed an analysis of the kinematics of a large sample of outer halo GCs. By comparing the measured velocities of individual GCs to the velocity of the main galaxy, they were able to derive relative velocities (see figure 4.5). Veljanoski et al. noted three important findings: Net rotation: in their sample of 78 GCs, Veljanoski et al. found evidence for net rotation in the outer halo, even out to the largest projected distances from M31. In other words, the majority of the GCs are rotating together around the main galaxy. This is somewhat evident in figure 4.5; many of the GCs on M31’s east (left) side are moving toward the Milky Way, while those on the west (right) side are moving away. Furthermore, the rotation profile agrees well with that of the inner GCs [6], suggesting that perhaps the inner and outer halo GCs are not distinct systems. This net rotation is seen both in GCs associated with substructure (i.e. those that have been recently accreted) and those associated with the smooth component. Associations with specific streams: Veljanoski et al. also identify groups of GCs with similar velocities; many of the GCs in these groups also lie along the bright streams that are labeled in figure 4.1 and outlined in figure 4.5. This is convincing evidence that these GCs are associated with each other (since they are moving together) and with the stars in the streams (since it is very unlikely that the GCs would randomly lie along a stream; [37]). The association of individual GCs with specific streams and the properties of the galaxies that created these streams will be discussed in section 4.4. However, it is worth noting that Veljanoski et al. [56] found that many of the GCs associated with specific streams are also rotating around M31. In an accretion scenario, one would naively expect the infalling dwarf satellites to be randomly distributed around the larger galaxy, with different locations, velocities, and orbits—in such a framework, the recently accreted GCs should not show significant rotation. The net rotation of these GCs (and, presumably, their streams) reveals something crucial about their progenitors. Veljanoski et al. suggested that rotation can exist in an accreted GC population if the GCs were brought in from a single, massive galaxy (e.g., [4]) or if the smaller dwarf satellites 4-11

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Figure 4.5. An image from Veljanoski et al. [56] showing the velocities of M31 outer halo GCs. The background image is a metal-poor ([Fe/H] ≲ −1.4 ) stellar density map from PAndAS. Each filled circle is a GC; they are color-coded according to their radial velocities relative to the central galaxy (vM31corr , in km s−1). The colored outlined regions show several stellar streams (or, in the case of Association 2, a clump of GCs). Note that the GSS is not identified; it is the large feature lying to the south of M31 which is even more prominent in maps of metal-rich stars. The white circle shows the And XVII dwarf galaxy. The dashed circles show projected distances of 30 and 100 kpc from the center of M31. Reproduced with permission of Oxford University Press on behalf of the Royal Astronomical Society.

were all brought in from a ‘preferred direction’ (e.g., if they were accreted along a dark matter filament; [36]). No association with plane of satellites: recall that about half of M31’s intact dwarf galaxies lie in a very large, yet thin, plane, which is rotating about M31. Ibata et al. [28] found that such an alignment had a very low chance of occurring randomly. Some possible explanations for this plane are similar to the explanations for rotation in the outer halo GC population, including the idea of accreting the dwarfs along a preferred direction. However, Veljanoski et al. [56] found no evidence that the GCs are associated with this plane— they further noted that most of the galaxies currently on the plane are not massive enough to host significant numbers of GCs. It is still possible that a massive galaxy on the plane was accreted, along with a large number of GCs, but additional work is necessary to test this theory.

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Figure 4.6. Integrated [Ca/Fe] ratios (derived from high-resolution optical spectra) as a function of [Fe/H] in M31 GCs. The Milky Way field stars are shown with grey points for comparison (see figure 2.9 for references). The abundances of inner halo GCs are shown with purple stars, using the data from Colucci et al. [12, 13] and Sakari et al. [49]. The green stars show outer halo GCs (from [13] and [50]). For reference, the GCs from two Milky Way satellites, the LMC and the Fornax spheroidal, are also shown (see figure 2.9 for references). Interesting GCs are labeled. Animation available at https://iopscience.iop.org/book/978-1-64327-750-9.

4.3.4 Calcium abundances Figure 4.6 shows the high-resolution IL abundances of the inner [13, 49] and outer halo [13, 50] M31 GCs, along with the Milky Way field stars and the average abundances from GCs associated with the LMC and the Fornax dwarf spheroidal galaxy. Although the resulting samples are small and biased to the brightest GCs, it is apparent from this figure that the outer halo GCs are not as metal-rich as the inner GCs (also see figure 4.3). This is a natural consequence of the overall metallicity gradient in the M31 halo (figure 4.3). The high [Ca/Fe] ratios of several clusters, especially the metal-rich ones, place lower limits on the mass of their host galaxies— these GCs could have formed in the inner regions of M31, or they could have been accreted from massive dwarfs. The figure also shows at least two GCs (PA-17 and G002) with low [Ca/Fe] compared to other M31 GCs and Milky Way stars at the same [Fe/H]. As discussed in sections 2.3.4 and 3.6.5, the exact location of a star or GC in the [Ca/Fe] versus [Fe/H] plot provides valuable information about the mass of its host galaxy. The low [Ca/Fe] ratios in PA-17 and G002 strongly indicate that these two GCs formed in dwarf satellites that were later accreted into the halo. Since G002 is more metal-poor and has low [Ca/Fe], presumably it formed in a lower-mass galaxy than PA-17. These results will be discussed in more detail in section 4.4, which links individual GCs to specific streams. 4.3.5 Specific frequencies Figure 4.7 shows the specific frequency (the number of GCs normalized to the total brightness of the Galaxy) of the entire M31 outer halo (following [37] and using the 4-13

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Figure 4.7. Specific frequencies of the entire M31 outer halo (the substructure and the smooth components) and the metal-poor substructured and smooth components, compared to other galaxies (see the legend and figure 3.3). The specific frequency for the entire outer halo was calculated assuming that all 92 outer halo GCs belong to M31’s outer halo. The substructured and smooth component specific frequencies have been calculated assuming they are responsible for all 32 GCs associated with substructure and all 35 not associated with substructure, respectively. The large upward errors reflect the range that occurs if the 25 ambiguous GCs are included in each calculation.

magnitude from [29]). In total, the entire M31 outer halo has a similar magnitude as the LMC, but a slightly higher specific frequency. If the magnitude of the outer halo has been underestimated, the point would move further to the lower right. The resulting specific frequency is slightly higher than the LMC.6 Recall that Mackey et al. [37] demonstrated that the GCs trace the properties of the metal-poor halo stars better than the metal-rich halo stars. Figure 4.7 shows 6 Section 3.3 demonstrated that the entire M31 galaxy has a normal specific frequency. The slightly high specific frequency of the outer halo suggests that there is an excess of GCs for the measured brightness of the outer halo. The two results are not inconsistent: the faint features and the 92 GCs in the outer halo have a small impact on the entire galaxy’s specific frequency.

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specific frequencies for the metal-poor substructured and smooth compenents of the outer halo, assuming that all the outer halo GCs belong to one of these two populations and using the total magnitudes from Ibata et al. [29]. The large upper ranges for the substructured and smooth components show the resulting specific frequency if the ‘ambiguous’ GCs [37] are included in those components. Both the substructured and smooth components show an excess of GCs for their luminosity, relative to the galaxies in the Harris et al. [24] sample. This could indicate accretion events from multiple dwarfs (e.g., Mackey et al. argued that the smooth component could be formed from 5 to 6 Fornax-mass galaxies). Alternatively, this could suggest that some GCs are associated with the metal-rich substructured or smooth components, or that these host galaxies were especially prolific at forming GCs.

4.4 Associations with specific streams The stellar streams themselves provide valuable information about the recent accretion of dwarf satellites. However, the individual stars in these streams are often too faint to study spectroscopically (although several groups, e.g., SPLASH, have indeed studied small regions with spectroscopy, primarily for velocities). The GCs are much easier to observe, simply because they are brighter and more centrally concentrated. If the GCs are indeed associated with a specific stream, they provide complementary information to the resolved photometry. As discussed in section 4.3.1, Mackey et al. [37] classified the outer halo GC into three groups: GCs with a high likelihood of being associated with a stellar stream, based on their velocity and their proximity to a stream; GCs that are very unlikely to be associated with any substructure; and ambiguous GCs that look to lie near a bright stream or in a region with a high density of stars. Mackey et al. [37] found that 35% of the outer halo GCs do indeed seem to be associated with bright substructure, implying that they have been recently accreted from a dwarf galaxy. Furthermore, as has been pointed out in section 4.2, the bright, coherent streams that are visible today will eventually dissolve over time, becoming undetectable (at least with current facilities; see chapter 6). It is therefore very possible that the smooth outer halo component identified by Ibata et al. [29] and the GCs that are not associated with substructure [37] were brought in during older accretion events whose streams have since dissolved. The current bright streams and their GCs likely only provide a record of the accretion events that have occurred within the last few Gyr. The shapes of the streams and the abundances of their GCs can provide important constraints on M31’s recent accretion history [31]. This section discusses the individual streams and possible associations with GCs, particularly focusing on photometric observations of the streams, models of the progenitor galaxies’ orbits, and properties of the GCs. 4.4.1 The giant stellar stream According to Ibata et al. [29], the GSS is ‘likely the latest and most significant accretion event that has taken place in the last several (∼2–3) Gyr’. The GSS has already been mentioned several times, including how it may have impacted the inner 4-15

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regions. It is most apparent in images of the outer halo where it dominates the metalrich component of the outer halo ([29]; see figure 1.2), though there are features in the inner halo that may have been caused by the GSS (e.g., [42]). Of the ‘named’ substructure in the outer halo (the features labelled in figure 4.1, i.e., those that are bright and distinct), the GSS represents 93% of the mass, according to McConnachie et al. [42]. However, it is likely that the progenitor galaxy created more streams and features than just the GSS. The contributions of the GSS to the M31 system have been significant, both due to the stars it has brought into M31 and for its gravitational effects on the disk. Several groups have created models of the formation of the GSS, trying to understand the properties of the progenitor galaxy such as its mass and its orbit. Many of these models predict that the GSS progenitor orbited around M31 several times, leading to wraps of the stream around the Galaxy (e.g., [17, 18]). The older wraps (from when the Galaxy first encountered M31) may have dissipated, so that they are no longer detectable as coherent streams; more recent wraps could have been identified as other named streams. Many of the models for the formation of the GSS find that the progenitor must have been a fairly massive galaxy. For example, Fardal et al. [17] quote a progenitor mass of about 109 M⊙, which is comparable to the mass of the LMC. Kirihara et al. [33] argue that the GSS progenitor was a spiral galaxy, similar to the LMC (e.g., [54]), while Hammer et al. [22] state that the the GSS progenitor had ∼25% the mass of M31. The GSS also contains many metal-rich stars [29]. Conn et al. [14] reanalyzed the photometry of the GSS fields, finding metallicities that ranged from [Fe/H] ∼ −0.7 up to −0.2. Recall from sections 2.3.2 and 2.3.4 that very low-mass dwarf galaxies are unlikely to form stars as metal-rich as the Sun, simply because they cannot create enough stars to produce a sufficient amount of iron. The metallicities of the stars in the GSS support the results from the models which say that the dwarf galaxy progenitor of the GSS was likely massive, similar to the LMC. The evidence from the stars therefore suggests that within the last few Gyr, M31 accreted a massive dwarf galaxy, which has deposited a large number of stars into the halo and disrupted the stars that were already present in M31. Such a massive galaxy undoubtedly had a fairly large GC population. However, Mackey et al. [37] only identify one probable GC and two ambiguous candidates that coud be associated with the GSS—this is many fewer than predicted for such a massive galaxy (the LMC has at least 16 GCs; [24]). The paucity of GCs that are currently associated with the GSS suggests that its GCs could have been accreted early on during the progenitor dwarf galaxy’s initial encounters with M31 [39]. This scenario may be plausible, given that many GCs are located in galaxy halos and may be easier to remove than individual stars in disks. However, it is also worth recalling that most of the GCs in the outer halo are more consistent with being associated with the metal-poor halo stars, which may indicate that they are not associated with the more metal-rich GSS. Alternatively, Mackey et al. [37] have suggested that these missing GSS GCs could actually be serendipitously projected into the inner regions. As a result, these missing GCs would have been included in the Caldwell et al. sample ([7]; see chapter 3). 4-16

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Since the GSS is responsible for the bulk of the metal-rich field stars in the outer halo, it is worth considering whether the metal-rich outer halo GCs could have originated in the GSS. Recall that the [Fe/H] ratios of the outer halo GCs have not been derived in a uniform, homogeneous way, which may lead to systematic offsets between individual GCs. However, it is worth noting that most of the GCs that have been identified as metal-rich ([Fe/H] ≳ −1) do have fairly red integrated colors [37], supporting the claim that they are fairly metal-rich. PA-37: this is the sole cluster identified by Mackey et al. [37] as a likely member of the GSS stream. Sakari et al. (in preparation) do indeed find this cluster to be metal-rich, within the expected range for the stars in the GSS [14]. Therefore, PA-37 does seem likely to be a member of the GSS. PA-17: this is the only metal-rich GC that has been spectroscopically analyzed at high-resolution. Sakari et al. [50] found this cluster to have a fairly high metallicity ([Fe/H] ∼ −0.9) coupled with a low Ca abundance ([Ca/Fe] ∼ 0), which is the typical chemical signature of a fairly massive dwarf galaxy (about the mass of the LMC; see figure 4.6). However, Mackey et al. [37] classify this GC as a ‘non-substructure’ cluster, for two reasons: (1) it does not lie along a named stellar stream, and (2) there is a low density of stars surrounding the cluster, which suggests that it is not associated with the ‘amorphous’ substructure in the outer halo. Given that the GSS likely wraps around M31, it is possible that PA–17 was accreted early on, and the resulting stream has since dissipated. Additional observations and modeling are necessary to determine if this is a viable possibility. Association 2: four of the GCs identified by Wang et al. [57] as metal-rich are in ‘Association 2,’ a group of GCs (see figure 4.5; they are located near the ‘G1 clump’ in figure 4.1). Veljanoski et al. [56] showed that these GCs fall into two distinct kinematic sub-groups, both of which host metal-rich GCs. It is still unknown whether this association is connected to the GSS, including if it may be the result of an interaction with the disk. There are several other metal-rich GCs in the outer halo, some of which are not associated with substructure or which have ambiguous associations. Ultimately, however, none yet have convincing links to the GSS. If the GSS was indeed as massive as predicted, one might expect it to have contained a nuclear star cluster or that there may be some existing remnant of the central regions. Several groups have argued that various GCs or existing dwarf galaxies could be the former nucleus of the GSS. Perina et al. [47] suggested that an inner GC, B407, could be the GSS nucleus. B407 is indeed fairly massive and metalrich; Caldwell et al. [7] estimate it to have a metallicity of [Fe/H] ∼ −0.5. Perina et al. [47] also showed that although B407 appears to be an inner halo GC in projection, it likely actually lies in the outer halo, with a 3D distance ∼30 kpc from the center of M31. It also lies near a feature in the inner regions known as the Northwest (NW) Shelf, which Ferguson et al. [19] suggested could be connected with

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the GSS. Indeed, models predict that the remnant of the progenitor could be located in the NW Shelf today [18]. Alternatively, D’Souza and Bell [16] argue that the GSS and several other streams could have been caused by a merger with a much more massive galaxy, where M32 is the surviving nucleus (although [18] rule out this scenario). Indeed, M32’s high metallicity ([Fe/H] ∼ +0.1 to +0.3; [53]) certainly suggests that it must have once been more massive. However, it is still unknown whether it is actually connected with the GSS or the outer halo GCs. Ultimately, more work needs to be done to determine high-quality parameters for both inner and outer halo GCs, to observe the individual stars in the stream, and to model the orbit of the progenitor. 4.4.2 The southwest cloud Several features are most evident in maps of moderately metal-poor stars ([Fe/H] < −1.1). One such feature, the SW Cloud, lies to the southwest of M31, about 100 kpc from the center. The cloud extends over 50 kpc in projection, with 3 GCs lying directly on top in projection [3]. At least one of these GCs has a similar radial velocity to the field stars in the stream, according to SPLASH observations [20]. There may also be an extension of the cloud farther to the southeast, which could be associated with two additional GCs, H10 and H15. Mackey et al. [37] classify both H10 and H15 as having ‘ambiguous’ associations with substructure. From photometric analyses of the SW Cloud, McMonigal et al. [44] concluded that the stream has an average metallicity of [Fe/H] = −1.3 ± 0.1. They further estimate that a galaxy with this metallicity must have been more massive than the current stream indicates. In other words, McMonigal et al. [44] find that the SW Cloud has already lost up to 60% of its stars. With a current stellar mass of 7 × 106 M⊙, this mass estimate implies that the SW Cloud progenitor must have had a mass of around 20 × 106 M⊙. Mackey et al. [37] also show that, with 3–5 GCs, the current brightness of the SW Cloud would indicate that the progenitor galaxy had a very high specific frequency, as shown in figure 4.8. If, as McMonigal et al. [44] argue, the SW Cloud has lost 60% of its mass, the specific frequency would be much lower (see the dashed line in figure 4.8). The high specific frequency would therefore seem to support McMonigal et al.’s assertion that the SW Cloud was created by a much more massive progenitor. However, Mackey et al. also note that if the SW Cloud progenitor lost this much mass, those stars would have to currently reside in another stream or the ‘amorphous’ substructure. The SW Cloud stars are unlikely to reside in the smooth halo, which is generally more metal-poor than the SW Cloud [29]. Instead, it is possible that the SW Cloud progenitor has been responsible for creating multiple stellar streams (see the discussion in [37]). This hypothesis also requires additional modeling and observations. The properties of the SW Cloud GCs are also themselves somewhat unusual. Mackey et al. [40] showed that PA-7 and PA-8, two clusters that lie right along the stream, both have moderate metallicities ([Fe/H] ∼ −1.3) and may be slightly younger than typical MW GCs at the same metallicity. The other GC on the stream, PA-14, appears to be more metal-rich (Sakari et al., in preparation). One of the GCs on the southeast extension, H10, also has a moderate metallicity of 4-18

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Figure 4.8. Specific frequencies of several bright, named streams in M31’s outer halo, compared to other galaxies (see the legend and figures 3.3 and 4.7). For each stream, the range of possible specific frequencies is shown, based on the estimated number of GCs. For example, the E Cloud has 2–3 associated GCs, which leads to SN = 105 − 155. For the E and SW Clouds, the dashed arrows show the effect on the SN if the original progenitor was more massive (using the brightness according to the median metallicity; see [44] and [3], respectively). The color-coding for the streams is roughly the same as in figure 4.5. The E Cloud is shown in orange, the SW Cloud in green, the NW Stream in blue, and Stream C/D in magenta.

[Fe/H] ∼ −1.3 [50]. By Local Group standards, it is unusual for a galaxy to have four moderately metal-poor GCs but none that are more metal-poor. This could indicate that the SW Cloud experienced a significant increase in star formation after the Galaxy had already chemically enriched, possibly as a result of the interaction with M31. Alternatively, it could indicate that the SW Cloud lost its more metalpoor GCs, which are currently located elsewhere in the outer halo. The fact that the SW Cloud has any GCs this metal-rich provides additional evidence that it was once much more massive. Furthermore, H10’s high [Ca/Fe] (see figure 4.6) is similar to that of the inner M31 GCs and typical Milky Way field stars and GCs, indicating that it formed in a fairly massive galaxy (and that the star formation had to have

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occurred before the onset of Type Ia supernovae). Ultimately, the abundances of these GCs indicate that they likely formed in a massive dwarf galaxy. 4.4.3 The eastern cloud This feature is a cloud of stars lying ∼120 kpc east of M31. Similar to the SW Cloud, it has a fairly well-defined main body, tracing out an arc, with two potential extensions to the northwest and southwest [44]. The photometric analysis by McMonigal et al. [44] found a median stellar metallicity of [Fe/H] ∼ −1.2, indicating that the Galaxy must have been much more massive in the past. They estimate that the stream only represents ∼12% of the original galaxy mass. From the current mass of ∼2 × 106 M⊙, this implies an original progenitor mass of over 10 × 106 M⊙ (see [42]). Before it was disturbed, the E Cloud progenitor was likely one of the most massive satellites of M31, similar to the SW Cloud. It is also possible that the two features are from the same progenitor [42]. Mackey et al. [37] classify three GCs (PA-56, PA-57, and PA-58) as being associated with the E Cloud, out of six in the vicinity. Two other clusters, PA-53 and PA-54, were ruled out as E Cloud members because of the low density of stars around one GC, indicating the lack of a stellar stream (PA-53), and because the radial velocity of the other did not agree with the other E Cloud GCs (PA-54). However, Sakari et al. [50] argue that kinematically and chemically, PA-53 is consistent with E Cloud membership. The GCs that are likely members of the E Cloud have a wide range of metallicities. From resolved Hubble Space Telescope photometry, McMonigal et al. [44] found that PA-57 was consistent with being metal-poor ([Fe/H] ∼ −2), while PA-58 was more metal-rich ([Fe/H] ∼ −0.7). From a high-resolution IL spectroscopic analysis, Sakari et al. [50] found PA-56 to have [Fe/H] ∼ −1.7, and a slightly elevated [Ca/Fe] = 0.24 ± 0.05. The presence of such a large metallicity range in the GCs indicates that the E Cloud progenitor had a prolonged period of star formation and chemical evolution, again suggesting that the progenitor galaxy must have been significantly more massive than the current stream implies. Similarly, the E Cloud’s specific frequency for its current total magnitude is quite high (SN = 155 for 3 GCs), which, like the SW Cloud, also suggests that it has lost a considerable amount of mass (see figure 4.8). 4.4.4 The northwest stream This stream of stars lies to the northwest of M31. It may have two components (labeled K1 and K2 in figure 4.1), but McConnachie et al. [42] claim that the two have been created by two separate galaxies. Richardson et al. [48] had previously argued that the streams are connected to the nearby dwarf galaxy, And XXVII, which shows signs that it is being disrupted [11]. While the K1 stream does look to be associated with And XXVII, McConnachie et al. claim that the K2 half of the stream is associated with the NGC 147 and NGC 185 dwarf galaxies, which lie farther to the north. Recall from chapter 1 that these dwarf galaxies may have had a previous interaction with M31, which could indeed have created the K2 stream. 4-20

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For the purposes of this book, what is most remarkable about the NW Stream is the long, thin line of GCs that lie along the K2 portion (see figure 4.1). This stream extends for about 6 ◦ (∼80 kpc; [42]), yet has seven star clusters lying on top, in projection. Six of these clusters have similar kinematics, as shown in figure 4.5. These six GCs therefore have a strong likelihood of being associated with each other and with the K2 stream [56]. Kirihara et al. [32] used the GCs to model the orbit of the progenitor, finding that it must have a mass ≳2.2 × 106 M⊙. The stream has a moderate metallicity (−1.7 ≲ [Fe/H] ≲ −1.1; [29]), while the blue IL colors of the six GCs associated with K2 indicate that they are also moderately metal-poor. According to Kirihara et al. [32], this metallicity range is consistent with a stellar mass of at least 1–100 million M⊙. Similarly, McConnachie et al. [42] argue for a stellar mass of 8 .5 × 106 M⊙. For reference, this implies that the progenitor was probably at least as massive as the Fornax dwarf spheroidal. With six GCs, Mackey et al. [37] show that the NW Stream also has a high specific frequency, SN = 90 − 150. Again, this potentially hints that the progenitor was more massive than the current stream indicates. An association with NGC 147 and NGC 185, two of M31’s brightest satellite galaxies, could explain this high specific frequency. However, more work remains to be done on this stream and its GCs. 4.4.5 Streams C and D These streams, located to the east of M31 and north of the GSS (at R proj ∼ 50 kpc; see figure 4.1) are close together, which makes them difficult to disentangle. The two streams overlap in the north, and both intersect the GSS in the south. Stream D is most obvious in maps of moderately metal-poor stars, while Stream C seems to contain more metal-rich stars [29]. Chapman et al. [8] obtained moderate-resolution spectra of several stars in Stream C and showed that there were two kinematically distinct populations within the stream, one metal-poor ([Fe/H] ∼ −1.3) and the other metal-rich ([Fe/H] ∼ −0.7)—they further showed that these two metallicity/ kinematic groups are also slightly offset in images. Stream C may therefore actually be composed of two completely separate streams, which overlap somewhat. There are nine GCs that lie in the overlapping regions of Streams C and D. It is not obvious which GCs belong to which streams, but Veljanoski et al. [56] note that, like the stars in Stream C, the GCs fall into two velocity subgroups (with the exception of one GC, which Mackey et al. [37] classify as ‘ambiguous’). There are three more GCs that may be projected onto the lower part of Stream C and another three onto Stream D.7 Metallicity estimates exist for several of these GCs, from the IL photometry of Wang et al. [57], the moderate-resolution spectroscopy of Chen et al. [9] and Sakari et al. (in preparation), and the high-resolution spectroscopy of Sakari et al. [50]. Most of these clusters are metal-poor ([Fe/H] ≲ −1.5), even one that is suspected to be associated with the metal-rich component of Stream C. One GC that lies along Stream D, H23, was in the high-resolution analysis of Sakari et al. 7 Note that the dwarf galaxy And I also seems to lie at the end of Stream D, but it is not yet known if the two are related [42].

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[50]. At [Fe/H] = −1.1, H23 is more metal-rich than the majority of the Stream D stars [29], while its high [Ca/Fe] ratio further suggests that it formed in a fairly massive galaxy. It is still unclear if H23 is associated with Stream D or either of the Stream C components. For both of these streams, Ibata et al. [27] estimate that the progenitors were more massive than the Fornax dwarf galaxy. The total specific frequency for the combined streams is SN = 40 − 55, still on the relatively high end for dwarf galaxies, which could indicate that the progenitor galaxies were even more massive. However, disentangling these streams, understanding their stellar populations, and revealing their connections with the GCs requires additional follow-up observations and models. 4.4.6 The GCs without streams The streams that have been discussed so far are the bright, prominent ‘named’ features in the outer halo that have been linked to GCs. There are several remaining features that do not appear to have GCs—however, there are also 35 clusters that do not seem to be associated with any detectable streams, and another 25 whose link to streams is ambiguous [37]. As mentioned in section 4.3, these GCs look to share some of the same properties as the field stars in the smooth, metal-poor halo. However, several of these GCs have very compelling evidence to suggest that they were accreted from dwarf galaxies. For example, PA-17 and G002 both have low [Ca/Fe] for their metallicity (see section 4.3.4), suggesting that they likely originated in a low-mass galaxy. Because of its high metallicity, [Fe/H] ∼ −0.9 [50], PA-17 has already been discussed as a possible GSS GC. At a projected distance from M31 of R proj = 53.9 kpc [37], PA-17 is more metal-rich than other GCs at that distance. Its [Ca/Fe] ratio suggests that it originated in a fairly massive dwarf galaxy. Since there is no detectable stellar stream near PA-17, it could have been accreted early on, so that the streams have since dissipated. G002 is more metal-poor, at [Fe/H] ∼ −1.6 , again with a roughly Solar [Ca/Fe] [13]. These abundance ratios that G002’s host galaxy had a mass comparable to the Fornax dwarf spheroidal. Mackey et al. [37] classify G002 as an ‘ambiguous’ cluster based on its proximity to ‘Association 2,’ the group of GCs discussed in section 4.4.1. However, kinematically it does not agree with either of the two sub-groups identified by Veljanoski et al. [56]. Instead, it is kinematically and spatially more similar to the massive cluster G1.8 However, G1 is more metal-rich (at [Fe/H] ∼ −1) and has a higher [Ca/Fe] ratio. Since G002 is more metal-poor than G1 and yet al. ready shows signs of enhancement by Type Ia supernovae (based on its low [Ca/Fe]), it is unlikely that the two clusters originated in the same environment. Figure 4.7 shows the specific frequency of the smooth halo [29], assuming that it contains all 35 GCs classified as non-substructured [37]. This specific frequency agrees with typical dwarf spheroidal galaxies like Fornax. Mackey et al. [37] suggest 8 Note that Mackey et al. [37] classify G1 as a ‘substructure’ GC, although there are no signs of stellar streams near the cluster.

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that the accretion of 5–6 Fornax-mass galaxies could easily lead to the observed brightness and specific frequency of the smooth halo. However, recall that several metal-poor streams are predicted to have lost stars that are no longer in visible stellar streams. Those lost stars could currently reside in the smooth halo. If those stars are added to the current streams (leading to the lower specific frequencies in figure 4.8), stars would be removed from the smooth halo, increasing its total magnitude and specific frequency. Overall, there seems to be an excess of GCs in at least one component of M31’s outer halo. 4.4.7 M33 and its GCs Figure 4.1 shows that M33 has several GCs, some of which lie along tidal streams surrounding the Galaxy [37]. McConnachie et al. [42] discuss previous results showing that M33 seems to be missing its own outer halo GCs [10]; they suggest that some of these GCs could have been accreted into M31 during a previous passage. Although van der Marel et al. [55] argue, based on kinematics, that M33 could not have previously passed by M31, such an encounter could explain the high specific frequency of GCs in M31’s outer halo.

4.5 Summary: the nature of the outer halo Ultimately, the outer halo GCs reveal that the recent assembly of M31’s outer region has been very active. The outer halo is dominated by the metal-rich GSS, which seems to currently have very few GCs. The properties of most of the GCs seem to be more consistent with the moderately metal-poor outer halo stars (including those that are part of other streams). While the GSS seems to be missing GCs, these metalpoor streams seem to have a very high specific frequency, that is, they have too many GCs for their current brightness. This high specific frequency could indicate that the progenitor galaxies were especially prolific at making massive clusters, potentially as a result of the interaction between the progenitor galaxies and M31. However, other observational evidence (particularly the metallicities of the field stars in the streams) and models suggest that the current streams represent only a fraction of the original progenitor galaxies’ mass. In other words, the streams that are observed today represent only a small part of the original galaxies. Adding stars to the streams would increase the total brightness of the progenitor galaxy, decreasing the specific frequency as a result. These missing stars could reside in other named streams, in the ‘amorphous’ substructure, or in the smooth component. However, removing stars from the smooth halo would drive up its specific frequency and give it a greater excess of GCs for its total brightness. The outer halo is expected to form primarily through the accretion of smaller dwarf satellites (e.g., [31]). There is evidence that many of the outer halo GCs did originate in dwarf galaxies. Several GCs have properties that are consistent with origins in a fairly massive dwarf, comparable to the LMC. There are several high metallicity GCs, including PA-37 and several GCs in Association 2, whose high metallicities require that they formed in a fairly massive galaxy that could sustain 4-23

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ongoing star formation. There are a handful more whose combination of [Fe/H] and [Ca/Fe] ratios place further limits on the mass of their host galaxy, demonstrating that several originated in a galaxy that was at least as massive as the LMC. This list includes H10 (possibly associated with the SW Cloud), H23 (potentially associated with Stream C/D), and G1 (thought to be the former nucleus of a dwarf galaxy). All of these enriched GCs had to have formed in a fairly massive galaxy; it is still unknown whether they formed in an LMC-mass dwarf, were somehow pulled out of M31’s inner disk/halo, or formed during a merger. PA-17’s low [Ca/Fe] and high [Fe/H] is the most compelling evidence that it originated in an LMC-mass galaxy. However, PA-17 is not currently associated with any substructure, suggesting it may have been accreted long ago. The more metal-poor GCs could have originated in a massive or low-mass galaxy; their metallicities and (for a handful of GCs) [Ca/Fe] ratios do not reveal anything significant about the masses of their host galaxies, other than that they must have been massive enough to form GCs. Only G002 has a combination of [Fe/H] and [Ca/Fe] that suggest it formed in a Fornax-mass dwarf galaxy. Ultimately, the mass estimates from observational and modeling constraints suggest that the GSS, Streams C/D, the NW Stream, and the SW and E Clouds all came from fairly massive dwarf satellites. The existence of these streams suggests that these accretions all happened fairly recently, within the last few Gyr; otherwise, the streams would have dissolved. McConnachie et al. [42] propose a ‘best-guess’ accretion for M31 based on the PAndAS observations. They argue that the smooth halo, which accounts for about 25% of the stars, was accreted at early times from one or more dwarf galaxies. These accretion events presumably brought in a number of GCs, possibly including PA-17 and G002—however, their disparate [Ca/Fe] abundances suggest two separate accretion events. PA-17 and G002 cannot have been accreted too early: from simulations of Milky Way-mass galaxies, Johnston et al. [31] show that star formation within the dwarfs is likely to stop after the dwarf galaxy is accreted. For PA-17 and G002 to have low [Ca/Fe] ratios, their dwarf galaxy hosts must have had enough time for chemical evolution to proceed normally in those galaxies before they were accreted into M31. McConnachie et al. [42] then propose that M33 could have had a close passage by M31 about 3 Gyr ago, although they do note the evidence against a past interaction [55]. If M33 did pass by M31, the gravitational interaction could have stripped M33 of its outer halo, including its GCs. This could potentially explain M31’s apparent excess of GCs, if it happened to accrete a large number of M33’s GCs. At least two subsequent accretion events then took place, according to McConnachie et al. [42]. One of the events involved the NGC 147 and NGC 185 dwarf galaxies, possibly producing the K2 portion of the NW Stream. The other involved the And XXVII galaxy, producing the K1 portion of the NW Stream. These galaxies may have brought in a handful of GCs, but the 6–7 on the NW K2 Stream are the most evident. This number of GCs implies that a roughly Fornaxmass galaxy created the K2 stream. However, NGC 147 and NGC 185 have their own, bound GCs. It is unclear if the K2 Stream and its GCs were created by stripping NGC 147, if there was another galaxy involved that was completely 4-24

The Globular Star Clusters of the Andromeda Galaxy

destroyed, or if the NW Stream is completely unrelated to NGC 147 and NGC 185. Still, McConnachie et al. argue that the K2 component is completely unrelated to And XXVII and the K1 Stream. Presumably another massive dwarf galaxy also fell in around this time, creating the SW and E Clouds. Finally, about 1 Gyr ago the LMC-mass GSS fell in, bringing in its metal-rich stars and severely disrupting the existing M31 disk. Presumably the majority of the metal-rich stars in the outer halo are currently there as a result of this interaction. The GSS almost certainly had more than three GCs (the number identified by Mackey et al. [37] as likely or ambiguous members of the GSS), but it is unclear where these other GCs currently reside. Some of the metal-rich outer halo GCs could have been associated with the GSS itself (if they were accreted early on in the interaction). Alternatively, several of the GSS’s GCs could now be in the inner regions (in projection), including B407, which Perina et al. [47] suggest is the remnant nucleus of the GSS. Some of the outer halo GCs could also be the result of the disruption of M31’s disk by the GSS, which could have ejected several clusters from the disk into the outer halo. The interaction with the GSS could also explain the presence of the young massive clusters in M31’s disk, because the resulting interaction could have triggered intense star formation. Dorman et al. [15] investigated the photometry and kinematics of stars in the inner regions of M31, concluding that ‘M31 has had a more violent accretion history than the [Milky Way] in the recent past’. It is possible that the GSS is the galaxy responsible for this recent accretion signature. There are many open questions surrounding M31’s assembly history. As McConnachie et al. [42] point out, it is not clear how M32 fits into this ‘best-guess’ accretion history. If D’Souza and Bell [16] are correct, and M32 is actually the former core of the GSS, then the progenitor galaxy was likely much more massive than the LMC. Increasing the mass of the GSS progenitor increases the number of predicted GCs that should have originated in that galaxy, but again, only three GCs can be tentatively linked to the GSS. Similarly, it is still debated if M33 has had a previous interaction with M31. If it has not, then there is no convincing explanation for its lack of outer halo GCs or its tidal streams. The SW and E Clouds both look to have been associated with massive galaxies, yet it is unknown if they were caused by a single galaxy or by two separate, lower-mass galaxies. The presence of the massive GC, G1, which may be the former nucleus of a fairly massive dwarf galaxy, remains puzzling, since it has no discernible substructure or other associated GCs. Finally, connections between the inner and outer halos remain uncertain. Ultimately, however, it is clear that M31 is currently accreting multiple dwarf satellites, and that it has had a more active recent accretion history than the Milky Way. All of these open questions can be answered with continued modeling and observations. Deeper photometry (to fainter magnitudes) may be able to detect fainter substructure from lower-mass dwarf galaxies and older accretion events and to determine better ages and distances for the outer halo GCs. More spectroscopic observations in the inner and outer regions will characterize the kinematic and chemical properties of GCs and stars, linking them together more concretely and providing additional constraints for the models. Finally, the dynamical models will be essential for understanding the masses and orbits of the progenitor galaxies that 4-25

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have created the current streams. All of this is essential work for unraveling the cosmological assembly of M31 and its GC system.

References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42]

Amorisco N C 2017 Mon. Not. R. Astron. Soc. 464 2882 Armandroff T E and Zinn R 1988 Astron. J. 96 92 Bate N F, Conn A R, McMonigal B, et al. 2014 Mon. Not. R. Astron. Soc. 437 3362 Bekki K 2010 Mon. Not. R. Astron. Soc. 401 L58 Caldwell N, Harding P, Morrison H, et al. 2009 Astron. J. 137 94 Caldwell N and Romanowsky A J 2016 Astrophys. J. 824 42 Caldwell N, Schiavon R, Morrison H, et al. 2011 Astron. J. 141 61 Chapman S C, Ibata R, Irwin M, et al. 2008 Mon. Not. R. Astron. Soc. 390 1437 Chen B, Liu X, Xiang M, et al. 2016 Astron. J. 152 45 Cockcroft R, Harris W E, Ferguson A M N, et al. 2011 Astrophys. J. 730 112 Collins M L M, Chapman S C, Rich R M, et al. 2013 Astrophys. J. 768 172 Colucci J E, Bernstein R A, Cameron S, et al. 2009 Astrophys. J. 704 385 Colucci J E, Bernstein R A and Cohen J G 2014 Astrophys. J. 797 116 Conn A R, McMonigal B, Bate N F, et al. 2016 Mon. Not. R. Astron. Soc. 458 3282 Dorman C E, Guhathakurta P, Seth A C, et al. 2015 Astrophys. J. 803 24 D’Souza R and Bell E F 2018 Nature Astronomy 2 737 Fardal M A, Babul A, Geehan J J, et al. 2006 Mon. Not. R. Astron. Soc. 366 1012 Fardal M A, Weinberg M D, Babul A, et al. 2013 Mon. Not. R. Astron. Soc. 434 2779 Ferguson A M N, Johnson R A, Faria D C, et al. 2005 Astrophys. J. Letters 622 L109 Gilbert K M, Guhathakurta P, Beaton R L, et al. 2012 Astrophys. J. 760 76 Gilbert K M, Kalirai J S, Guhathakurta P, et al. 2014 Astrophys. J. 796 76 Hammer F, Yang Y B, Wang J L, et al. 2018 Mon. Not. R. Astron. Soc. 475 2754 Harris W E 1996 2010 edition Astron. J. 112 1487 Harris W E, Harris G L H and Alessi M 2013 Astrophys. J. 772 82 Huxor A P, Mackey A D, Ferguson A M N, et al. 2014 Mon. Not. R. Astron. Soc. 442 2165 Huxor A P, Tanvir N R, Irwin M J, et al. 2005 Mon. Not. R. Astron. Soc. 360 1007 Ibata R, Martin N F, Irwin M, et al. 2007 Astrophys. J. 671 1591 Ibata R A, Lewis G F, Conn A R, et al. 2013 Nature 493 62 Ibata R A, Lewis G F, McConnachie A W, et al. 2014 Astrophys. J. 780 128 Ibata R A, Malhan K and Martin N F 2019 Astrophys. J. 872 152 Johnston K V, Bullock J S, Sharma S, et al. 2008 Astrophys. J. 689 936 Kirihara T, Miki Y and Mori M 2017 Mon. Not. R. Astron. Soc. 469 3390 Kirihara T, Miki Y, Mori M, et al. 2017 Mon. Not. R. Astron. Soc. 464 3509 Leaman R, VandenBerg D A and Mendel J T 2013 Mon. Not. R. Astron. Soc. 436 122 Lewis G F, Braun R, McConnachie A W, et al. 2013 Astrophys. J. 763 4 Libeskind N I, Frenk C S, Cole S, et al. 2005 Mon. Not. R. Astron. Soc. 363 146 Mackey A D, Ferguson A M N, Huxor A P, et al. 2019 Mon. Not. R. Astron. Soc. 484 1756 Mackey A D, Huxor A, Ferguson A M N, et al. 2006 Astrophys. J. Letters 653 L105 Mackey A D, Huxor A P, Ferguson A M N, et al. 2010 Astrophys. J. 717 L11 Mackey A D, Huxor A P, Ferguson A M N, et al. 2013 Mon. Not. R. Astron. Soc. 429 281 McConnachie A W 2012 Astron. J. 144 4 McConnachie A W, Ibata R, Martin N, et al. 2018 Astrophys. J. 868 55

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[43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57]

McConnachie A W, Irwin M J, Ibata R A, et al. 2009 Nature 461 66 McMonigal B, Bate N F, Conn A R, et al. 2016 Mon. Not. R. Astron. Soc. 456 405 Meylan G, Sarajedini A, Jablonka P, et al. 2001 Astron. J. 122 830 Perina S, Bellazzini M, Buzzoni A, et al. 2012 Astronomy & Astrophysics 546 A31 Perina S, Federici L, Bellazzini M, et al. 2009 Astronomy & Astrophysics 507 1375 Richardson J C, Irwin M J, McConnachie A W, et al. 2011 Astrophys. J. 732 76 Sakari C M, Shetrone M D, Schiavon R P, et al. 2016 Astrophys. J. 829 116 Sakari C M, Venn K A, Mackey D, et al. 2015 Mon. Not. R. Astron. Soc. 448 1314 Sakari C M and Wallerstein G 2016 Mon. Not. R. Astron. Soc. 456 831 Sánchez-Janssen R, Côté P, Ferrarese L, et al. 2019 Astrophys. J. 878 18 Schiavon R P, Caldwell N and Rose J A 2004 Astron. J. 127 1513 van der Marel R P 2001 Astron. J. 122 1827 van der Marel R P, Fardal M A, Sohn S T, et al. 2019 Astrophys. J. 872 24 Veljanoski J, Mackey A D, Ferguson A M N, et al. 2014 Mon. Not. R. Astron. Soc. 442 2929 Wang S, Ma J and Liu J 2019 Astron. Astrophys. 623 A65

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IOP Concise Physics

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 5 Multiple populations in M31 GCs

Learning goals After completing this chapter, readers will be able to: • Provide several definitions of the phrase ‘multiple populations’ and explain why the definition can vary. • Give several examples of observations that indicate that the Andromeda Galaxy (M31) globular clusters (GCs) host multiple populations. • Discuss what observations of M31 GCs have revealed about the source of multiple populations. • Summarize what is known about the iron-complex GCs in M31, and how these clusters can provide insight into the multiple populations phenomenon in GCs.

5.1 Multiple populations Thus far the M31 GCs have been primarily utilized for understanding the assembly history of the larger galaxy rather than cluster formation itself. Section 3.4 discussed the work of Johnson et al. [23], who used clusters from the PHAT survey to study the the distribution of cluster masses in M31. Johnson et al. found that the maximum cluster mass is closely related to the host galaxy’s star formation rate, meaning that massive globular-like clusters only form during periods of intense star formation. GCs are therefore intimately connected with the field star population—it is precisely this quality which makes them useful tracers of a galaxy’s assembly history. However, GCs do not always share the chemical properties of the field stars. Section 2.3.5 briefly introduced the concept of ‘multiple populations’, the presence of stellar chemical composition variations within classical GCs. These light-element abundance spreads seem to be unique to GCs; the few field stars with the same abundance variations have been suggested to come from stripped or dissolved GCs [31, 53]. As shown below, these composition variations are a signature of the GC formation process. doi:10.1088/2053-2571/ab39dech5

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ª Morgan & Claypool Publishers 2019

The Globular Star Clusters of the Andromeda Galaxy

This chapter summarizes what M31 GCs have revealed about multiple populations and GC formation. The discussion begins (section 5.2) with a brief review of the abundance variations within GCs in the Milky Way and its nearest satellites and a summary of the proposed scenarios for the formation of multiple populations. Subsequent sections (section 5.3) focus on light element variations in M31 GCs, trends with cluster properties, and implications for the theories of multiple populations. Finally, the potential ‘iron-complex’ GCs in M31, including G1, are discussed in section 5.4.

5.2 Lessons and theory from resolved GCs 5.2.1 A definition of ‘multiple populations’ from observations The meaning of ‘multiple populations’ can vary between studies. Generally speaking, the name implies that there are light element abundance variations within a single GC, i.e., that two stars within the same cluster can have different abundances of light-elements. ‘Multiple populations’ are identified observationally, when abundance spreads are detected, but the confusion lies in which elements constitute the signature of these abundance variations. The elements that commonly vary within GCs are He, C, N, O, and Na, but occasionally Mg, Al, Si, and other elements may also vary. One major complication that prevents converging on a definition is that spreads in some elements (He, C, N) can be detected photometrically, while others (Na, Mg, or Al) require spectroscopy. The difference in detectability means that some element spreads can be more easily categorized than others. Another factor is that these elements do not all form in the same way: He, N, Na, and Al can all be created during hydrogen fusion, but in separate processes at different temperatures. As a result, the individual elements may exhibit different variations between clusters. In other words, the abundance variations within each GC are somewhat unique. Altogether, these factors mean that the term ‘multiple populations’ is not well-defined. Below, some of the various definitions are summarized. One way that the term ‘multiple populations’ is used is with resolved photometry, where He, C, and N spreads can be detected. Figure 5.1 shows two color-magnitude diagrams (CMDs) of the Milky Way GC, NGC 2808. The V, V−I CMD in figure 5.1(a) shows a relatively normal-looking GC (similar to figures 2.2 and 3.1), with a narrow red giant branch (RGB). With filters in the ultraviolet, however, the same cluster (figure 5.1(b)) has multiple, distinct RGBs and a broad main sequence [37, 42], which are likely due to significant star-to-star variations in He, C, and N (e.g., [30]). Some groups refer to these CMD splits as ‘multiple populations’, since the splits reveal the presence of He, C, and N spreads within the cluster. The advantage of photometric detections is that many stars can be observed at one time. The major disadvantage of a photometric approach is that detecting RGB and main sequence splits may require ultraviolet space-based observations, which are very competitive. A large Hubble Space Telescope program, the HST UV Globular Cluster Survey [37, 42] has observed many Milky Way GCs, but this type of observation is not yet possible in distant, faint GCs. NGC 2808 is also a rather 5-2

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Figure 5.1. Hubble Space Telescope CMDs of a Milky Way GC, NGC 2808. This cluster is moderately metalpoor, with [Fe/H] = −1.14 [18]. Left: a V, V−I CMD from the ACS Survey of Galactic Globular Clusters [50], showing a typical optical CMD of a resolved GC, as described in section 2.2.1. The main sequence, RGB, and horizontal branch are all relatively thin and well-defined. Right: a CMD showing two ultraviolet Hubble Space Telescope filters (F275W versus F275W–F336W) from the UV Legacy Survey of Galactic Globular Clusters [37, 42]. In this ultraviolet CMD the horizontal branch is bright and extended, the RGB is split into multiple sequences, and the main sequence is broad. The splits in the CMD are due to the effects of C, N, and He variations (e.g., [30]).

extreme case; spreads in other GCs may not be as obvious in ultraviolet CMDs. A cluster like 47 Tuc, for example, shows less extreme effects, particularly on the RGB. The lack of obvious splits in a CMD do not rule out the presence of small spreads in He, C, or N, or even large spreads in Na. Other definitions of ‘multiple populations’ require spectroscopy. Some groups refer to spectroscopically-confirmed C and N variations as ‘multiple populations’. These variations have been seen in all Milky Way GCs, and in intermediate-age clusters in the Large and Small Magellanic Clouds (e.g., [19, 33]). From a nucleosynthetic point of view, it is relatively easy to create variations in C and N, since N can be created at lower temperatures than Na or Al.1 Creating elements like Na and Mg, on the other hand, requires higher temperatures. Because of this temperature difference, C and N variations may not always be accompanied by Na and O variations. However, the advantage of using C and N is that they can be 1 For example, recall that C and N abundances vary in RGB stellar atmospheres purely as a result of stellar evolution.

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Figure 5.2. The [Na/Fe] and [O/Fe] ratios of individual stars in Milky Way GCs, from Carretta et al. [7]. Each point in this plot is an individual star, color-coded according to its [Fe/H] ratio. The circles show detections, while the sidewise triangles show upper limits in [O/Fe]. Carretta et al. [7] also divide this plot into three regions: the P stars show a ‘primordial’ chemical signature, i.e., they look like typical Milky Way field stars; the E stars show the most ‘extreme’ abundance variations; and the I stars are ‘intermediate’ between the two populations. The dashed lines show the distinctions between these populations. Note that the defining line between the P and I populations is different for each cluster; the grey bar shows a typical range for this dividing line.

determined from low-resolution spectroscopy, while Na and O typically require high-resolution spectra. This means that C and N can be measured in more stars within a single GC, and can be detected in more distant clusters whose stars are too faint for high-resolution. Other groups reserve the term ‘multiple populations’ for clusters that show detectable variations in O and Na. The anticorrelation between Na and O requires hot H-burning, a specific chemical signature that seems to have only been preserved in GC stars; the presence of Na and O spreads therefore indicates that He, C, and N variations should also be present within a cluster. Carretta et al. [6] and several subsequent papers have established that a Na–O anticorrelation is found in every classical (i.e. massive) GC in the Milky Way (see figure 5.2), while several other GCs, primarily the most massive, metal-poor ones, show a Mg–Al anticorrelation. Consequently, Gratton et al. [17] proposed that the Na and O variations are a necessary criterion for a cluster to be considered a GC. Many groups have searched for signatures of Na and O spreads in the lower-mass, intermediate-age Milky Way clusters (e.g., [48]), but they have not yet been found. The masses and ages of clusters that can host enhancements in Na and Al (which require a source of hot H-burning) are important for testing theories for the formation of multiple populations. The extent of the Na–O anticorrelation is also important for testing theories for the creation of multiple populations. Figure 5.2 shows the Na and O abundances for a compilation of Milky Way GCs by Carretta et al. [6], where each point is an individual star, color-coded by cluster [Fe/H]. Carretta et al. define three regions of 5-4

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this plot: the primordial (P) stars have the [Na/Fe] and [O/Fe] ratios of typical Milky Way field stars, implying that this is the chemical signature the GC would have had if there were no multiple populations; the extreme (E) stars have very high [Na/Fe] and low [O/Fe], the unique signature of hot H-burning; and the intermediate (I) stars fall between these two cases. The dividing lines between the P and I groups change from cluster to cluster (as shown by the grey band in figure 5.2). The scenarios listed below provide slightly different predictions for how stars should populate this plot. Finally, some people define ‘multiple populations’ as groups with different iron abundances (the ‘iron-complex’ GCs described in section 2.3.5). Although these clusters are rarer than typical GCs, they are among the brightest and most massive clusters. The leading explanation for these GCs is that they are former ‘nuclear star clusters’, the cores of dwarf galaxies whose field stars have been stripped. The cause of the iron spreads is different from the source of the light element variations, and they are discussed separately (section 5.4). However, it is worth noting that in some iron-complex GCs, e.g., ω Cen, there are Na–O variations within the sub-populations with different [Fe/H] ratios—the formation mechanism of these clusters is therefore somehow connected with the classical GCs. One additional factor to consider: the term ‘multiple populations’ does not necessarily imply multiple generations. In other words, there is no observational evidence to suggest that one population formed before the other. This is a fundamental point: the abundance spreads that define the multiple populations are observationally identified and defined, whereas the concept of multiple generations is a prediction from various scenarios that explain the presence of abundance variations. Some groups use the terms interchangeably, referring to the primordial ‘P’ population as the ‘first generation’ and implying that the I and E populations formed later out of material created by the P population. While this is a common theoretical scenario (see below), it is important to remember that there is not yet observational evidence to support this framework. Here, the term ‘multiple populations’ will be used to refer to ‘light element variations.’ This term is agnostic in that it does not pre-suppose a specific scenario to explain the observations. However, it is also a rather vague observational term that lumps together different observational techniques and different elements. Although all of the light element abundance variations are grouped together under this terminology, it is important to remember that the elements may not always vary together, as mentioned above. This generic term may also link clusters together which may require different scenarios to explain the abundance spreads. Ultimately, it may not be possible to explain all of the various observations with a single scenario, although that is the general goal for the theories of ‘multiple populations’ formation. With that in mind, the most popular scenarios to explain GC multiple populations are summarized below. 5.2.2 The proposed formation scenarios for multiple populations As mentioned in section 5.2.1, the physical processes that create the light elements are actually reasonably well-understood. He, N, Na, and Al can be created during H-burning, which subsequently depletes H, C, O, and Mg. The process for creating 5-5

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each of these elements requires a slightly different temperature. The difficulty is finding a star that can activate the necessary hot H-burning cycles and transport the material into the interstellar medium, where a star cluster with the necessary abundance variations can form. For example, although typical main sequence stars like the Sun create He and small amounts of N in their cores, Na and Al require such high temperatures that they cannot be created during H fusion in typical Sun-like stars. The enriched products of hot H fusion also have to be ejected from the star, something which is not easy for a main sequence, Sun-like star. Therefore, multiple populations cannot be created by stars like the Sun. This section outlines the scenarios that have been proposed to explain the light element abundance variations within GCs, specifically the types of stars that can create high N and Na and depleted C and O, and how these products of H fusion can be incorporated into GCs. In order for a theoretical scenario to be considered successful, it must meet several observational criteria: • Any scenario should reproduce the appropriate abundance spreads within GCs, including the anticorrelations in C–N, Na–O, and (in some clusters) Mg–Al. The extent of these variations cannot be the same in all GCs, since some clusters have larger spreads than others. • The phenomenon that creates abundance variations should only happen in massive star clusters (though a specific mass limit is still undefined) because these abundance variations are not seen in lower-mass open clusters or in the field. • The site of the abundance variations should be common enough to occur in all sufficiently massive clusters, since C, N, O, and Na variations have been observed in all classical GCs. Any formation scenario therefore should not require very rare nucleosynthetic sites. • A formation scenario has to produce abundance variations without creating substantial amounts of iron or other heavy elements, since these elements generally do not vary within GCs. This requirement seems to hold even for clusters with Fe spreads, like ω Cen, because the light element variations are not correlated with the Fe variations. Since supernovae generally produce lots of Fe, multiple populations formation scenarios must avoid contamination from supernovae. With these criteria in mind,2 the three most popular scenarios are summarized briefly below. This is not meant to be a comprehensive, detailed review; instead see Bastian and Lardo [3] for a more thorough discussion of these scenarios. All three of these scenarios require that a cluster forms with a uniform chemical composition (the composition of the P population); a certain type of star then evolves and deposits the products of hot H-burning into the cluster. It is generally assumed that a single site is responsible for all the observed abundance variations.3 The scenarios differ slightly 2

There are additional criteria that are not discussed here, including restrictions on the final C+N+O ratio and the abundance of lithium; see the Bastian and Lardo [3] review for more information. 3 Although see Johnson et al. [20] for a hybrid model.

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on what occurs next. Somehow, this enriched gas mixes with some amount of primordial gas, cools, and forms stars that are enriched in the H-burning products. The key differences in these scenarios are the mass and evolutionary state of the star that is responsible for contributing the H-burning products. As a result, the timescale for the formation of multiple populations is also different between the scenarios. None of these models can reproduce all of the observations, and all require some amount of fine-tuning, as Bastian and Lardo [3] explain. There are also several large scale problems with these models, as explained in section 5.2.3. 1. Very massive stars (∼1000–10 000 M⊙ ): this scenario, proposed by Denissenkov and Hartwick [12] and Gieles et al. [15], suggests that the source of the H-burning products is a very massive star. Such a star could form at the center of a cluster as a result of collisions between massive stars. In theory, a very massive star should reach very high temperatures in its interior which could produce all of the required elements. The creation of a very massive star could happen fairly quickly (∼3 Myr; [3]), possibly before the lower-mass primordial stars have completely formed. Such a massive star should also have strong stellar winds, which would quickly eject the H-burning products into the cluster before any core-collapse supernovae have exploded. The main weakness of this model is that such stars have never been observed. The formation and evolution of very massive stars is purely theoretical, and it is completely unknown whether such stars can exist, much less what would happen to such a star at the end of its short life (e.g., whether it would fragment or explode). 2. Rapidly rotating massive stars (≳15 M⊙ ): high-mass stars above ∼15 M⊙ should be able to reach high enough temperatures to activate hot H-burning, creating He, N, and Na [29]. If these high-mass stars are rapidly rotating they should lose mass through stellar winds, forming a disk that could cool and form a new generation of stars (e.g., [11]). This scenario requires that the new generation of stars forms before any core-collapse supernovae explode, to avoid iron spreads and the disruption of star formation. There are a number of weaknesses to this model, including the mass budget problem (see section 5.2.3) and the fact that it is difficult to produce Al [11]. An advantage of this scenario is that high-mass stars are known to exist in open clusters (i.e., they are not theoretical, like very-massive stars), they are expected to produce most of the necessary elements, and the enrichment of a new generation should happen relatively quickly. Ultimately, however, several aspects of this scenario need to be very finelytuned to reproduce the observed correlations (see [3]). 3. Intermediate-mass asymptotic giant branch stars (∼5–6.5 M⊙ ): another potential site for hot H-burning is intermediate-mass Asymptotic Giant Branch (AGB) stars [56]. An AGB star represents the end stages of intermediate- and low-mass stars, after they have exhausted H and He in their cores, but before they have ejected their outer layers in a planetary

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The Globular Star Clusters of the Andromeda Galaxy

nebula to reveal the central white dwarf. The more frequent low-mass AGB stars are not responsible for creating multiple populations because they cannot reproduce the observed abundance trends (e.g., they would create too much C). The mass range of AGB stars that can create the abundance signatures is limited to 5–6.5 M⊙ [3]. Although these stars have already fused all the H in their cores (while they were on the main sequence), they have H-burning shells farther from the center, which can reach high enough temperatures to activate the necessary chains. These stars also experience periodic ‘dredge up’ episodes, when convection brings the H-fusion products up to the surface. These elements can then be released into the cluster as the AGB star loses mass, and a new generation of stars can form from the ejecta (e.g., [13]). The progenitors of AGB stars have lower masses than the rapidly-rotating massive stars in Scenario 2. As a result, the AGB stars take longer to evolve to this phase and should not produce multiple populations until after core-collapse supernovae have exploded (but before the Type Ia supernovae explode), avoiding the issue of potential Fe spreads within the clusters. Like the fast-rotating massive star scenario above, this model uses a fairly common type of star that is expected to exist in all GCs. However, it also requires considerable fine-tuning to reproduce the observations. This model suffers from a mass budget problem (see section 5.2.3) and cannot explain all of the known abundance variations. Together, these three scenarios provide the leading explanations for the source of abundance variations within GCs. The first scenario is only theoretical, as verymassive stars have never been observed. While the latter two scenarios invoke known types of stars that are expected to exist in young clusters, the models cannot reproduce all of the observed abundance variations without significant fine tuning (see the discussion in [3]). Note that there is a fundamental difference between possible nucleosynthetic sites to create the necessary elements and the scenarios to explain the formation of multiple populations. The former term describes the types of processes, the conditions, and, ultimately, the type of star that could create the elements. The latter would describe how the elements could travel from the nucleosynthetic site to the intercluster medium, how new stars would form, and whether this scenario can match the observed trends. The individual nucleosynthetic sites themselves could be used in different scenarios, or various sites could be combined in one scenario. The three scenarios presented above assume that a single site creates all of the nucleosynthetic products of hot H-burning and suggest possible mechanisms to explain how that site could produce all the observed abundance variations. Note that there could be additional sites and scenarios (e.g., [20]). Below, three main problems with these scenarios are discussed, based on observations of GCs in the Milky Way and its dwarf satellites.

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The Globular Star Clusters of the Andromeda Galaxy

5.2.3 Open problems with the multiple populations scenarios There are many problems with the three scenarios listed above, most of which are beyond the scope of this book. This section examines three general problems that can be addressed with observations of M31 GCs. Age spreads: at least two of the above scenarios (the latter two) require distinct bursts of star formation, i.e., two distinct generations of stars, where the ‘extreme’ population forms out of material from the ‘primordial’ population. These scenarios therefore predict age spreads within all GCs, where each generation has distinct C, N, O, and Na (and possibly Mg and Al) abundances.4 The age difference between the generations would depend on the nucleosynethic source of the abundance spreads. Under Scenario 2 (the fast-rotating massive stars) the age spread would be ∼10–20 Myr; under Scenario 3 (AGB stars) it would be slightly larger, ∼30 Myr. Since Scenario 1 is theoretical, it is unknown if there would be a significant age difference between the populations. These small age differences are virtually undetectable in an old GC. However, an age spread would be easier to detect in young clusters, since the changes to the main sequence occur very rapidly (see figure 3.4). Various groups have claimed to detect age spreads in young, massive LMC clusters (e.g., [41]), but these detections are sensitive to effects like stellar rotation ([27], although also see [16]). It is still not known if these apparent age spreads are real, or, if they are real, whether they are a common feature of all massive star clusters. It is also unknown if these young, currently massive clusters are truly the analogues of old, classical GCs. Several intermediate-age GCs with ages ≳2 Gyr have been shown to host variations in C and N (e.g., [19, 33]), but it is not yet known if they host Na and O variations as well. Similarly, it is not yet known if the young massive clusters host any abundance spreads. From observations of intermediateage Magellanic Cloud clusters, Martocchia et al. [32] found evidence that the extent of N spreads was dependent on the cluster age, with older GCs exhibiting larger spreads. This result suggests that any spreads in younger clusters could be small. It is unclear how these findings fit into the above three scenarios, or if they also apply to Na and O. If these younger massive clusters do not host a Na–O anticorrelation, then they have not experienced exactly the same formation mechanism as the older GCs. More observations of young and intermediate-age GCs are needed to assess both the prevalence of multiple populations and the presence of any age spreads. Cluster-to-cluster variations: even in old GCs with multiple populations, the nature of the abundance variations is not the same in all clusters. Some GCs have more extreme (E) stars than others, while some have a greater range in the E populations. Both of these properties are correlated with the GC mass (e.g., [8]), meaning that more massive clusters have larger abundance spreads. Establishing these trends with cluster properties requires that the populations within the GCs have been evenly

4

It is not obvious how the intermediate stars fit into these scenarios. Presumably they could form from a mixture of primordial and enriched gas, as an intermediate generation between the P and E populations; or they could require a much more complex formation scenario (e.g., [20]).

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The Globular Star Clusters of the Andromeda Galaxy

sampled, so that there is no bias. For example, observations of only ten stars would be very unlikely to sample the full extent of an abundance spread, or to quantify the relative number of stars in the P, I, and E subpopulations. Therefore, understanding the nature of the abundance spreads within GCs requires large spectroscopic observing campaigns, which have been conducted for many Milky Way GCs (e.g., [6]). This observational trend of increasing extreme stars with cluster mass may be difficult to reconcile with the three scenarios in section 5.2.2, especially given the problem below. Observations of more massive GCs could help test the theories for the formation of multiple populations. The mass budget problem: one of the most problematic issues confronting models of multiple populations concerns the number of stars in the enriched and primordial GC populations, specifically the mass in these populations. Bastian and Lardo [3] divide this issue into internal and external problems. The internal problem concerns the relative numbers of P, I, and E stars. Specifically, GCs have too many enriched I and E stars relative to the current number of primordial P stars. All three of the scenarios in section 5.2.2 require that the I and E populations form out of material from stars in the P population. However, only a small number of stars (a narrow mass range) from the P population can produce the necessary elements because the predicted sources of multiple populations (the massive and intermediate-mass stars) only make up a fraction of the total stellar population.5 Furthermore, of that small number of stars, the ejecta lost in stellar winds and incorporated into a new generation of stars is only a small fraction of the total stellar mass. If these scenarios are correct, the number of second generation (E) stars should therefore be much smaller than the number of first generation (P) stars. This is not what is observed—the number of I and E stars is often equal to or greater than the number of P stars. To remedy this problem, Scenarios 2 and 3 require that GCs lose as much as 95% of their first generation (P) stars in order to increase their nucleosynthetic contributions and explain the subsequent dominance of the I and E stars (see [3]). Indeed, GCs are expected to lose some mass through tidal effects as they orbit through the Milky Way. However, Kruijssen [24] shows that massive GCs are unlikely to lose as much mass as required for Scenarios 2 and 3. Additionally, multiple populations are also observed in GCs that are associated with low-mass dwarf galaxies (e.g., [36]), where tidal effects (and subsequent mass loss) should be much weaker. Therefore, there is no observational evidence to suggest that GCs have lost this many P stars, and the internal mass budget problem remains a challenge for multiple populations scenarios. The external mass budget concerns the total number of P stars in a GC system relative to its host galaxy. If a GC loses 95% of its P stars, those stars would be accreted into the host galaxy, appearing as field stars today. Through observations 5

The stellar initial mass function (IMF) dictates that there should be many more low-mass stars than massive stars. It is possible that the IMF could have been more ‘top-heavy’ in GCs (i.e. that there could have been more massive stars than expected). Even with this adjustment, however, the low-mass stars should dominate the cluster. While it is possible that GCs experienced a unique form of star formation that leads to a very topheavy IMF (e.g., the creation of very massive stars), this has never been observed.

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The Globular Star Clusters of the Andromeda Galaxy

of the Fornax dwarf spheroidal galaxy, Larsen et al. [26] compared the metal-poor field stars (with [Fe/H] < −2) to the four most metal-poor GCs. They found that the GCs accounted for 20%–25% of all the metal-poor stars in Fornax. In other words, the total metal-poor halo of Fornax is only 4–5 times larger than the GCs. If all of those field stars had originated in the 4 GCs, then at most the GCs could only have ever been 4–5 times more massive. There are simply not enough metal-poor stars in Fornax to account for 95% of each GC’s missing P stars. It therefore seems unlikely the Fornax GCs could have lost enough P stars to match Scenarios 2 and 3. In addition to the age spreads, cluster-to-cluster variations, and mass budget problems, there are a number of potential issues with the three simple scenarios for multiple populations. It is unclear whether the scenarios need to be fine-tuned, whether another nucleosynthetic site is needed, or whether a more complex scenario would be more successful. Additional observations could help provide more tests of theoretical scenarios. 5.2.4 The role of M31 GCs in understanding multiple populations Most of the observational knowledge of multiple populations has come from GCs in the Milky Way and its nearby satellites, which can be observed in exquisite detail. Deep photometric observations have revealed split features in CMDs and assessed the presence of age spreads, while spectroscopy has characterized the star-to-star abundance variations in C, N, O, Na, and more. Ultimately, however, open questions remain. The M31 GCs provide a supplementary data set for tests of multiple populations scenarios. Chapters 3 and 4 have demonstrated that M31 contains more GCs than the Milky Way, including GCs with higher masses and massive clusters with younger ages. The caveat for M31 observations, of course, is that the individual stars within the GCs cannot be easily studied. Limited photometry of only the brightest stars makes it difficult to detect any CMD splits (though see section 5.4). Spectroscopically, only integrated light (IL) abundances are available for M31 GCs, meaning that only a single abundance is available for an entire cluster. As a result, abundance spreads in M31 GCs must be inferred from IL photometry or spectroscopy, rather than directly detected. Below, the observational signatures of multiple populations in M31 GCs are discussed in detail.

5.3 Multiple populations in M31 GCs 5.3.1 Inferring the presence of multiple populations from IL The presence of multiple-populations in M31 GCs can be inferred simply by comparing the IL spectra to those of Milky Way GCs. Schiavon et al. [52] found no significant differences between the optical spectra of Milky Way and M31 GCs with the same mass and metallicity.6 Since the Milky Way GCs have multiple 6 Earlier observations had suggested that the M31 GCs had stronger CN features than corresponding Milky Way GCs (e.g., [43]), which indicated higher [N/Fe] and, possibly, a more extreme N spread or a greater number of N-enhanced stars. However, Schiavon et al [52] showed that this offset was likely due to calibration issues with the spectra.

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The Globular Star Clusters of the Andromeda Galaxy

Figure 5.3. [Na/Fe] ratios as a function of [Fe/H] in Milky Way field stars (grey points, from [44, 45, 55]) and M31 GCs (maroon circles, from [10, 47, 49]). Many of the M31 GCs have integrated [Na/Fe] ratios that are higher than typical field stars.

populations and the M31 GCs have similar spectra, it is therefore likely that the M31 GCs also host abundance spreads (at least in C and N, which can be detected in these lower-resolution spectra). The derived IL abundances also indicate that the M31 GCs likely host multiple populations. Schiavon et al. [51] found that many GCs have higher [N/Fe] ratios than typical field stars. Similarly, Colucci et al. [9, 10] and Sakari et al. [47, 49] found elevated IL [Na/Fe] ratios, as shown in figure 5.3, which were generally higher than the values for field stars and could not be explained by systematic uncertainties. Even the massive cluster, G1, shows signs of Na enhancement (Sakari et al., in preparation). They suggested that the high IL [Na/Fe] ratios were caused by multiple populations, a claim which is bolstered by IL observations of Milky Way GCs, which have similarly elevated [Na/Fe] ratios and are known to host Na variations [10, 46].7 Colucci et al. [9, 10] also found deficient Mg and enhanced Al in several M31 GCs. The M31 GCs also show photometric evidence for He enhancement based on resolved and IL ultraviolet photometry ([39] and [38], respectively). The addition of high-resolution infrared spectra allows IL [O/Fe] abundances to be derived (the optical lines are typically too weak for IL spectroscopy). Sakari et al. [47] showed that the combination of infrared [O/Fe] ratios and optical [Na/Fe] ratios places most of the clusters in the I region of the Carretta et al. [6] plot, as shown in figure 5.4. IL spectra reflect the average abundance of the cluster, weighted by the brightness of the stars. The location of the M31 GCs in the I regions suggests that the majority of the M31 GCs host P, I, and E stars, just like Milky Way GCs. These observations are indirect, though compelling, evidence that multiple populations are also present in M31 GCs. An alternative explanation would be 7 Sakari et al. [46] showed that the derived IL abundances for several Milky Way GCs fell within the range of abundances from individual stars.

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The Globular Star Clusters of the Andromeda Galaxy

Figure 5.4. Integrated light [Na/Fe] versus [O/Fe] ratios for M31 GCs (from [10] and [47]). The P, I, and E designations from Carretta et al. [7] are shown (see figure 5.2). Most of the GCs fall into the I range, suggesting that they have multiple populations. The points are color-coded by [Fe/H].

that the primordial populations in the M31 GCs are themselves enhanced in He, N, and Na and deficient in C and O. However, the similarity of the spectra between Milky Way and M31 GCs suggests that the underlying populations are similar. It therefore seems very likely that the multiple populations phenomenon is also found in M31’s GCs. 5.3.2 Trends with cluster properties M31 contains GCs that are unlike the Milky Way GCs, including GCs at higher masses and GCs with younger ages. In IL, the cluster stars are observed all at once in a single spectrum. Though this is a disadvantage for characterizing abundance spreads, it is an advantage for assessing the relative contributions of each population within a GC. For reasonably massive, well-populated, ‘classical’ GCs, a cluster’s position in figure 5.4 reveals whether P or E stars dominate the IL. A cluster with a dominant P population should lie closer to the P region, while a cluster with a dominant E population should lie closer to the E region. A GC in the I region could have a dominant I population, or a blend of P and E populations. This means that the IL [Na/Fe] and [O/Fe] ratios are sensitive to the number of I and E stars within a cluster.8 The trends in IL abundances as a function of cluster parameters like age and mass are therefore valuable for testing multiple population formation scenarios. 8

Interpreting IL abundances is not actually this simple. Each spectral line may have different sensitivities to the two populations, particularly in the optical versus the infrared. IL spectra are also more sensitive to the brighter cluster stars; if one population happens to have brighter stars, that population will appear to be dominant. This issue is more likely to affect low-mass clusters, which have fewer stars. Brighter clusters are less likely to have these sampling issues.

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The Globular Star Clusters of the Andromeda Galaxy

Figure 5.5. Integrated [N/Fe] abundance ratios (from [51]) as a function of cluster age (in Gyr). The points are color-coded according to [Fe/H]; note the different range from figure 5.4, because the Schivaon et al. sample is limited to clusters with [Fe/H] > −0.9 5. There is not a clear trend with age, although there are no highly N-enhanced GCs with ages ≲10 Gy r .

Unfortunately, none of the young GCs identified by Caldwell et al. [4] have yet been analyzed for chemical abundance studies. A handful of intermediate-age GCs from Caldwell et al. [5], with ages as low as ∼6 Gyr, were analyzed by Schiavon et al. [51]. Figure 5.5 shows the IL [N/Fe] ratios versus cluster age. Recall that the signature of multiple populations is enhanced [N/Fe]. Although there is no clear trend in [N/Fe] with cluster age in figure 5.5 (since the old GCs exhibit a large scatter in [N/Fe]), none of the GCs with ages below 10 Gyr have highly enhanced [N/Fe] ratios. As there are only a handful of GCs in this age range, this result is not very significant. However, if this result is confirmed with additional GCs, it would seem to agree with Martocchia et al. [32], who found that the C and N spreads in intermediate-age Magellanic Cloud clusters were less severe than in the older GCs (i.e., the intermediate-age GCs do not have stars that are as enhanced in [N/Fe] as the most extreme stars in old GCs). It is evident from figure 5.5 that there is also a metallicity effect, where the highest [Fe/H] clusters have the highest [N/Fe]. Ultimately, more observations of young, intermediate-age, and old GCs are needed to assess differences with cluster age. Some of the spread in [N/Fe] amongst the old GCs in figure 5.5 occurs because there is a significant trend in integrated [N/Fe] with cluster mass [51]. Figure 5.6 shows the IL [N/Fe] ratio versus cluster mass, demonstrating that the highest-mass GCs have enhanced [N/Fe] ratios. As in figure 5.5 there is a metallicity dependence, where the most metal-rich are more N-enhanced than the more metal-poor GCs. Within a specific metallicity range, Schiavon et al. [51] showed that there is a strong correlation between cluster mass and [N/Fe], indicating that the massive GCs have more N-enriched stars (and more E stars, if the N enhancement is coupled with Na). Note that there is not a strong trend in [C/Fe] with mass [51]. This N enhancement 5-14

The Globular Star Clusters of the Andromeda Galaxy

Figure 5.6. Integrated [N/Fe] abundance ratios (from [51]) as a function of cluster mass (from [54] or [51]), based on a similar figure from Schiavon et al. [51]. The points are color-coded according to [Fe/H], as in figure 5.5. There is a trend with increasing mass/decreasing total absolute magnitude, where the most massive and brightest clusters have higher integrated [N/Fe]. There is also a strong trend with [Fe/H].

Figure 5.7. Integrated [Na/Fe] abundance ratios (from [10, 47, 49], and Sakari et al., in preparation) as a function of cluster velocity dispersion (top; a proxy for mass) and total V-band magnitude (bottom; from [54]). The points are color-coded by [Fe/H]. There appears to be a trend with mass, where the more massive, brighter clusters have higher integrated [Na/Fe].

may be coupled with He enhancement; in their IL photometric analysis, Peacock et al. [38] also found that the ultraviolet ‘excess’ (a possible proxy for He enrichment) was correlated with cluster mass. Figure 5.7 then shows the IL [Na/Fe] ratios as a function of the total absolute magnitude, a proxy for cluster mass (since some of the clusters do not yet have mass estimates). The [Na/Fe] ratios are from high-resolution IL spectra ([10, 47, 49], 5-15

The Globular Star Clusters of the Andromeda Galaxy

Sakari et al., in preparation). Although there are many fewer GCs with [Na/Fe] ratios than [N/Fe] ratios, there is still a trend with cluster mass (also see [10]). Once again, these results indicate that more massive GCs have larger abundance spreads or a greater fraction of stars that are enhanced in the products of hot H-burning, like He, N and Na. It is not straightforward to incorporate these abundance correlations with cluster mass into the scenarios from section 5.2.2. Although more massive clusters should have more rapidly rotating massive stars (Scenario 2) and intermediate-mass AGB stars (Scenario 3), overall, they should also have more P stars, reducing the relative impact of the E population. Bastian and Lardo [3] noted that the very massive stars (Scenario 1) may produce more I and E populations in massive clusters, but again, this is speculative. Trends in Mg and Al with cluster mass are not as clear-cut, which is to be expected given that the Mg–Al anticorrelation is not observed in all GCs. In the Milky Way, Mg and Al variations are more commonly found in massive, metalpoor GCs. Colucci et al. [10] only determined [Al/Fe] for metal-rich GCs (because the lines are too weak in metal-poor clusters), but they did find evidence for a weak correlation with cluster magnitude. Al abundances are easier to derive in the infrared; from the infrared IL spectra, Sakari et al. [47] found a weak decreasing trend in [Mg/Al] with cluster mass, which possibly steepens when only metal-poor GCs are used. Ultimately, more work needs to be done to understand the presence of the Mg–Al anticorrelation and any trends with cluster properties. 5.3.3 Perspectives on the mass budget problem Finally, it is worth revisiting the mass budget problem with the perspective from the M31 GCs. In particular, the M31 GCs provide the possibility to investigate trends in IL [Na/Fe] relative to potential birth sites. With a relatively small sample, Colucci et al. [10] found no trends in IL [Na/Fe] as a function of the projected distance from the center, in agreement with the Milky Way GCs. In other words, the variations in [Na/Fe] cannot be explained by differences in the projected distance from M31. This suggests that the relative dominance of the P versus the E population is not dependent on distance from the center of the galaxy, which further indicates that tidal stripping by M31 likely did not play an important role in removing P stars. Sakari et al. [49] also found enhanced Na in several GCs that may be associated with stellar streams (including H10; see chapter 4), which suggests that the relative dominance of the I and E populations is also found in dwarf galaxy GCs, where stripping is expected to be less efficient. Unfortunately, very few outer halo GCs have been targeted for abundance analyses. Additional observations would help to further tease out any possible differences in N or Na as a function of a GC’s location in M31. Recall from chapter 4 that M31’s outer halo has a high specific frequency, i.e. a high number of GCs for its brightness. This is true both for the GCs associated with the smooth component and those associated with substructure. Mackey et al. [28] showed that the majority of the outer halo GCs appear to be associated with the metal-poor smooth halo component. If these GCs lost 95% of their P stars, then 5-16

The Globular Star Clusters of the Andromeda Galaxy

presumably those stars would now be in the smooth halo. However, removing those stars from the smooth halo would increase its specific frequency even more. Therefore, it would seem that, like Fornax, M31’s GCs likely could not have lost 95% of their primordial stars. 5.3.4 Summary: light element spreads in M31 GCs Observations of multiple populations in M31 GCs have been limited, for a variety of reasons. First, [N/Fe] measurements from low-resolution optical spectra are currently only limited to the more metal-rich GCs [51]. Second, [Na/Fe] measurements require high-resolution spectroscopy, which is limited to the brightest GCs [10, 49]. Similarly, [O/Fe] ratios require infrared, high-resolution spectroscopy, which has thus far been limited to 25 bright GCs [47]. Additionally, He spreads can be inferred from IL photometry in the ultraviolet [38], but only for GCs with large He spreads. Finally, because IL spectra provide a single abundance of an element for each cluster, these abundance variations are inferred, rather than detected. Despite these limitations, the IL observations of M31 GCs have confirmed and, in some cases, expanded the results from Milky Way GCs, including signs of enhanced He, N, Na, and Al; trends in [N/Fe], [Na/Fe], and [Na/O] with cluster mass; possible changes in [N/Fe] with age; and additional mass budget problems. Ultimately, these results do not yet shed light on a viable formation scenario for multiple populations. Additional observations and models will be essential for unraveling the nature of multiple populations.

5.4 The iron-complex GCs This chapter now turns to a rare type of GC: the ‘iron-complex’ GCs, which have star-to-star Fe spreads that are often discernible in CMDs. The source of the Fe spreads is distinct from the source of the light-element variations. However, these clusters may be important for understanding scenarios for the creation of multiple populations, as well as for unraveling the assembly history of M31. These clusters are thought to have been nuclear star clusters at the centers of galaxies. The two main formation channels for nuclear star clusters involve a) star formation in the central regions as a result of gas infall or b) mergers of existing GCs, though in reality both channels are likely to occur (see, e.g., [1]). Observations of Milky Way GCs suggest that these iron-complex clusters are intimately connected with GCs. For example, the massive cluster ω Cen has multiple populations (C, N, Na, and O variations) within its individual [Fe/H] sub-populations [22]. The iron-complex Milky Way clusters are among the most massive GCs (e.g., [21]). This therefore suggests that the extremely massive GCs in M31 (several of which are more massive than ω Cen) may also host Fe spreads. This section briefly discusses those GCs. As with the light-element spreads, it is difficult to obtain spectroscopic observations of individual stars in the suspected iron-complex M31 GCs. The Fe spreads are therefore either a) detected through resolved photometry of the brightest stars or b) inferred from IL spectra. In the latter case, IL spectra can indicate the presence of Fe spreads because various spectral lines have slightly 5-17

The Globular Star Clusters of the Andromeda Galaxy

different sensitivities to the metallicity sub-populations. In the former case, resolved photometry can directly reveal the presence of metallicity spreads because the slope of the RGB is sensitive to [Fe/H] (e.g., see [49]). However, although resolved photometry can provide a detection of Fe spreads, there are several caveats to this approach. First, the Fe spreads must be large enough to create RGB splits that are greater than the photometric errors; small metallicity spreads would not be detectable with the current CMDs. Second, the detection of an Fe spread can be sensitive to field star contamination, particularly for GCs that are located in the disk or bulge regions or those embedded in a stellar stream. Finally, resolved photometry is currently only limited to the stars in the outermost regions, because of issues with crowding in the centers. This observational limitation reduces the number of stars in a CMD; these observations could also miss Fe spreads if the metallicity subpopulations have different radial distributions. 5.4.1 Suspected iron-complex M31 GCs With these caveats in mind, the candidate iron-complex GCs in M31 are discussed below: B023, B158, and B225: these three massive clusters were identified by FuentesCarrera et al. [14] as candidate iron-complex GCs, based on broad RGBs detected in resolved photometry. Although all three are projected into the inner halo, Perina et al. [39] found that two are likely outer halo GCs (B023 and B225, at RM31 = 54.5 kpc and 47.5 kpc, respectively). All three appear to be moderately metal-rich, with [Fe/H] ∼ −0.6 to −0.9; Fuentes-Carrera et al. [14] suggested they have spreads in [Fe/H] that are as large as ∼1 dex. Intriguingly, Sakari et al. [47] and Larsen et al. [25] both compared the optical and infrared spectra of B225 to assess whether a metallicity spread could be detected spectroscopically. They found negligible offsets in the integrated [Fe/H] between the optical and the infrared, which are smaller than predicted for such a large metallicity spread. B088: B088 is a more metal-poor ([Fe/H] ∼ −1.7; [47]), bright (MV = −10.6; [54]) GC with a fairly elliptical shape [2]. The resolved CMD may hint at a [Fe/H] spread, but the cluster is located near the disk in a very crowded region where it is difficult to remove the field stars [40]. Sakari et al. [47] found similar [Fe/H] ratios between the optical and infrared, although they did find a large offset in [Mg/Fe]. They argued that this offset was unlikely to be caused by a Mg spread but instead could be the result of variations in [Fe/H]. More research needs to be done to investigate this result. G1: G1 has already been discussed in chapter 4. It is a massive, outer halo cluster that has long been suspected to be the former nuclear star cluster of a now-disrupted dwarf galaxy, although it does not seem to be associated with any detectable substructure [28]. Meylan et al. [35] first identified a broad RGB, from resolved photometry, which indicated an Fe spread. This has

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since been confirmed by follow-up work [37]. This cluster is moderately metal-poor ([Fe/H] ∼ −1; Sakari et al., in preparation). Other massive GCs: there are at least five additional clusters in M31 that appear to be more massive than ω Cen [54], none of which yet have evidence for Fe spreads. However, all five are located in the crowded inner disk and bulge regions, making it difficult to remove field star contamination from the CMDs. None have been targeted for high-resolution spectroscopic analysis. 5.4.2 Comparisons with Milky Way GCs The most massive GC in the Milky Way, ω Cen, has been well-studied in the last few decades. In particular, Johnson and Pilachowski [22] analyzed high-resolution spectra of 855 giant stars in ω Cen. Their resulting metallicity distribution for these 855 stars has five peaks at [Fe/H] ∼ −1.75, −1.50, −1.15, −1.05, and −0.75, although the most metal-poor stars dominate the cluster. The mean metallicity of the Johnson and Pilachowski sample is 〈[Fe/H]〉 = −1.65. Other Milky Way iron-complex GCs also appear to be dominated by metal-poor stars (e.g., [21]). One exception is the GC Terzan 5, which currently resides in or near the Milky Way bulge. Even though Terzan 5 is not currently as massive as ω Cen, its stars are more metal-rich. Massari et al. [34] found three peaks in the metallicity distribution, at [Fe/H] ∼ −0.8, −0.3, and +0.25; due to its high metallicity, they argued that Terzan 5 was likely much more massive in the past. Most of the massive M31 GCs look to have metallicities similar to Terzan 5, based on their IL spectra. Of the five clusters discussed above with [Fe/H] measurements, only B088 seems to be as metal-poor as ω Cen, with an integrated [Fe/H] ∼ −1.7. The metallicity of the stars within these candidate iron-complex GCs is an important indicator of the environment in which these clusters formed and the mechanism through which Fe spreads were created. The prevalence of massive metal-rich GCs may suggest that M31 accreted more massive nucleated dwarfs than the Milky Way. There may also be undetected iron spreads in the GCs that are slightly less massive than ω Cen. 5.4.3 Multiple populations in M31 iron-complex GCs Most of the clusters discussed above have elevated [N/Fe] ([51]; B088 and G1 are not included in the Schivon et al. sample). Two of these candidate iron-complex GCs, B225 [25] and G1 (Sakari et al., in preparation), have been targeted for highresolution IL spectroscopy; both show signs of elevated [Na/Fe] ratios. G1 may also have He variations (e.g., [39]). Taken together, these abundance ratios indicate that these massive, candidate iron-complex GCs also host multiple populations, which suggests that even though they likely host Fe spreads, they have also been enriched by the same nucleosynthetic source found in typical GCs. These clusters also extend the trends in mass, showing that the most massive clusters are among the most Naand N-enriched.

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5.4.4 Summary: M31 iron-complex GCs M31 contains a number of massive clusters which could be iron-complex GCs. Several, including G1, have direct observational evidence to support the presence of Fe spreads. A handful also have elevated [Na/Fe] ratios that suggest that they host multiple populations. These objects are suspected to be former nuclear star clusters from accreted dwarf satellites, where the Fe spreads occur as a result of ongoing star formation or GC mergers. The presence of high [Na/Fe] indicates that these objects must be intimately connected to GCs. Continued observations, including observations of more GCs, deeper photometry, and IL spectroscopy of more targets at different wavelengths and resolutions, will help assess the properties of these candidate iron-complex M31 GCs and the relationship of Fe spreads to multiple populations. Because these clusters are suspected to be the former cores of satellite galaxies, such observations will also be crucial for understanding the assembly history of M31.

References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29]

Antonini F, Barausse E and Silk J 2015 Astrophys. J. 812 72 Barmby P, McLaughlin D E, Harris W E, et al. 2007 Astron. J. 133 2764 Bastian N and Lardo C 2018 Annu. Rev. Astron. Astrophys. 56 83 Caldwell N, Harding P, Morrison H, et al. 2009 Astron. J. 137 94 Caldwell N, Schiavon R, Morrison H, et al. 2011 Astron. J. 141 61 Carretta E, Bragaglia A, Gratton R, et al. 2009 Astron. Astrophys. 505 139 Carretta E, Bragaglia A, Gratton R G, et al. 2009 Astron. Astrophys. 505 117 Carretta E, Bragaglia A, Gratton R G, et al. 2010 Astron. Astrophys. 516 A55 Colucci J E, Bernstein R A, Cameron S, et al. 2009 Astrophys. J. 704 385 Colucci J E, Bernstein R A and Cohen J G 2014 Astrophys. J. 797 116 Decressin T, Meynet G, Charbonnel C, et al. 2007 Astron. Astrophys. 464 1029 Denissenkov P A and Hartwick F D A 2014 Mon. Not. R. Astron. Soc. 437 L21 D’Ercole A, Vesperini E, D’Antona F, et al. 2008 Mon. Not. R. Astron. Soc. 391 825 Fuentes-Carrera I, Jablonka P, Sarajedini A, et al. 2008 Astron. Astrophys. 483 769 Gieles M, Charbonnel C, Krause M G H, et al. 2018 Mon. Not. R. Astron. Soc. 478 2461 Goudfrooij P, Girardi L, Bellini A, et al. 2018 Astrophys. J Lett. 864 L3 Gratton R G, Carretta E and Bragaglia A 2012 Astron. Astrophys. Rev. 20 50 Harris W E 1996 2010 edition Astron. J. 112 1487 Hollyhead K, Kacharov N, Lardo C, et al. 2017 Mon. Not. R. Astron. Soc. 465 L39 Johnson C I, Caldwell N, Michael Rich R, et al. 2019 Mon. Not. R. Astron. Soc. 485 4311 Johnson C I, Caldwell N, Rich R M, et al. 2017 Astrophys. J. 836 168 Johnson C I and Pilachowski C A 2010 Astrophys. J. 722 1373 Johnson L C, Seth A C, Dalcanton J J, et al. 2017 Astrophys. J. 839 78 Kruijssen J M D 2015 Mon. Not. R. Astron. Soc. 454 1658 Larsen S S, Pugliese G and Brodie J P 2018 Astron. Astrophys. 617 A119 Larsen S S, Strader J and Brodie J P 2012 Astron. Astrophys. 544 L14 Li C, Sun W, de Grijs R, et al. 2019 Astrophys. J. 876 65 Mackey A D, Ferguson A M N, Huxor A P, et al. 2019 Mon. Not. R. Astron. Soc. 484 1756 Maeder A and Meynet G 2006 Astron. Astrophys. 448 L37

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[30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56]

Marino A F, Milone A P, Renzini A, et al. 2019 Mon. Not. R. Astron. Soc. 487 3815 Martell S L, Shetrone M D, Lucatello S, et al. 2016 Astrophys. J. 825 146 Martocchia S, Dalessandro E, Lardo C, et al. 2019 Mon. Not. R. Astron. Soc. 487 5324–34 Martocchia S, Niederhofer F, Dalessandro E, et al. 2018 Mon. Not. R. Astron. Soc. 477 4696 Massari D, Mucciarelli A, Ferraro F R, et al. 2014 Astrophys. J. 795 22 Meylan G, Sarajedini A, Jablonka P, et al. 2001 Astron. J. 122 830 Mucciarelli A, Origlia L and Ferraro F R 2010 Astrophys. J. 717 277 Nardiello D, Libralato M, Piotto G, et al. 2018 Mon. Not. R. Astron. Soc. 481 3382 Peacock M B, Zepf S E, Maccarone T J, et al. 2018 Mon. Not. R. Astron. Soc. 481 3313 Perina S, Bellazzini M, Buzzoni A, et al. 2012 Astron. Astrophys. 546 A31 Perina S, Federici L, Bellazzini M, et al. 2009 Astron. Astrophys. 507 1375 Piatti A E and Cole A 2017 Mon. Not. R. Astron. Soc. 470 L77 Piotto G, Milone A P, Bedin L R, et al. 2015 Astron. J. 149 91 Puzia T H, Perrett K M and Bridges T J 2005 Astron. Astrophys. 434 909 Reddy B E, Lambert D L and Allende Prieto C 2006 Mon. Not. R. Astron. Soc. 367 1329 Sakari C M, Placco V M, Farrell E M, et al. 2018 Astrophys. J. 868 110 Sakari C M, Shetrone M, Venn K, et al. 2013 Mon. Not. R. Astron. Soc. 434 358 Sakari C M, Shetrone M D, Schiavon R P, et al. 2016 Astrophys. J. 829 116 Sakari C M, Venn K A, Irwin M, et al. 2011 Astrophys. J. 740 106 Sakari C M, Venn K A, Mackey D, et al. 2015 Mon. Not. R. Astron. Soc. 448 1314 Sarajedini A, Bedin L R, Chaboyer B, et al. 2007 Astron. J. 133 1658 Schiavon R P, Caldwell N, Conroy C, et al. 2013 Astrophys. J. 776 L7 Schiavon R P, Caldwell N, Morrison H, et al. 2012 Astron. J. 143 14 Schiavon R P, Zamora O, Carrera R, et al. 2017 Mon. Not. R. Astron. Soc. 465 501 Strader J, Caldwell N and Seth A C 2011 Astron. J. 142 8 Venn K A, Irwin M, Shetrone M D, et al. 2004 Astron. J. 128 1177 Ventura P, D’Antona F, Mazzitelli I, et al. 2001 Astrophys. J Lett. 550 L65

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IOP Concise Physics

The Globular Star Clusters of the Andromeda Galaxy Charli M Sakari

Chapter 6 M31 and beyond

Learning goals After completing this chapter, readers will be able to: • Summarize the properties of the Andromeda Galaxy (M31)’s globular cluster (GC) system and what the GCs have revealed about M31’s assembly history. • Discuss several remaining open questions concerning M31’s ongoing formation. • Describe several ways that future observations and facilities will help studies of M31.

6.1 Important results from M31 clusters This book has provided an overview of the known properties of M31’s massive star clusters, with the aim of understanding cluster formation (chapter 5) and the assembly history of the M31 galaxy (chapters 3 and 4). Much of this analysis was based on comparisons with the GCs in the Milky Way, where observations are of a much higher quality (chapter 2), or with the field stars in M31 and its satellite galaxies (chapter 1). This book also sought to discuss the nature of GCs, including possible distinctions from open clusters or galaxies (chapter 2); the nature of chemical abundance variations within GCs and dependences on cluster age or mass (chapter 5); and the difficulties in observing distant GCs (chapters 3 and 5). Three main results from this book are summarized below. 1. M31 has more massive star clusters than the Milky Way, both in the inner and outer regions: these GCs could have originated in satellite galaxies, indicating that M31 has accreted more massive satellites than the Milky Way—note that M31 also has more intact satellites and more massive satellites than the Milky Way. Alternatively, these clusters could have originated in M31’s disk and were subsequently ejected into the halo; this scenario would imply that

doi:10.1088/2053-2571/ab39dech6

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M31 has had higher rates of star formation than the Milky Way, allowing it to form more clusters. There is evidence to support both channels. 2. There is evidence that (at least) several of M31’s GCs have been accreted from dwarf galaxies: several of the outer halo GCs are likely to have originated in dwarf galaxies based on their associations with stellar streams. Additionally, a handful of all the M31 GCs have been found to have chemical abundances consistent with low-mass galaxies, while others have chemical abundances typical of higher mass dwarfs. Since many of the GCs are rotating about M31, it is possible that a large fraction of the M31 GC system was brought in by 1–2 massive satellites. Similarly, 1–2 massive satellites could have been responsible for creating many of the streams in the outer halo. 3. M31 has populations of clusters that are unlike those in the Milky Way: M31 has younger clusters, more metal-rich GCs, and more massive GCs than the Milky Way. The young massive clusters in M31 (which are similar to those in the Large Magellanic Cloud) suggest that a period of intense star formation was triggered ∼2 Gyr ago, possibly due to an interaction with another galaxy. The surplus of old, metal-rich GCs could indicate that early GC formation lasted longer than in the Milky Way, or that early enrichment was more rapid. If the massive GCs formed in M31, they could indicate that M31 experienced higher rates of star formation than the Milky Way, allowing it to form massive GCs. However, these massive objects could also be the former nuclear star clusters of accreted galaxies. M31’s excess of these massive clusters could indicate that it has accreted multiple massive, dwarf satellites that once had nuclear star clusters. Despite these differences with the Milky Way GCs, it is worth noting that the old GCs show many similarities to the Milky Way GCs. Both galaxies have GCs that cover a wide range of metallicities. With a few exceptions, the two galaxies’ GC systems show similar chemical evolution in [Ca/Fe] as a function of [Fe/H]. The AMRs appear to be similar, though the uncertainties in the ages of the M31 GCs are quite large. These similarities suggest that the bulk of M31’s GCs had to originate in fairly massive galaxies, and that the different accretion histories have not heavily impacted the chemical evolution of the galaxies. The inferred presence of multiple populations in M31’s GCs also hints that the cluster formation process is similar between the two galaxies. Many open questions remain, particularly concerning M31’s previous interactions with M32 and M33, the nature of the galaxies that have created stellar streams and distorted M31’s disk, and possible connections between the inner and outer regions. A considerable amount of work remains to be done to answer these questions and to refine the analyses of M31 GCs. Observationally, more GCs could be targeted for high-resolution observations, enabling abundances of Ca, Na, and many other elements to be determined throughout M31. Photometry of more GCs could provide metallicities, distances, and horizontal branch morphologies; reveal 6-2

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the presence of iron spreads; and place constraints on ages. Spectroscopic observations of field stars (especially those in streams) could allow GCs to be more definitively linked to substructure, and would provide additional constraints for models. Additional proper motion measurements from surveys like Gaia will also continue to refine the orbital parameters for GCs and satellites of M31 (including M33 and M32), which will further constrain the past orbits of dwarf satellites and GCs. On the modeling side, additional work to investigate the mass and orbits of dwarf galaxies that have created steallar streams will be valuable for understanding the build-up of the halo and how such interactions could have shaped M31’s disk.

6.2 Connections with other galaxies Though they cannot be studied at the same level of detail as M31, the GC systems of even more distant galaxies have been studied extensively (see Brodie and Strader [1] for a review). Such studies, which are important for understanding how galaxy properties change with, e.g., mass or environment, help place M31 in a more universal context. For example, observations of color distributions of large samples of GCs have shown that more massive galaxies tend to have more red (and, presumably, more metal-rich) GCs than lower mass galaxies [6]; M31’s relative excess of metal-rich GCs could therefore indicate that it is more massive than the Milky Way. However, more massive galaxies are also expected to exhibit different chemical evolution—specifically, the ‘knee’ in the [Ca/Fe] plot is expected to move to higher metallicities in higher-mass galaxies (see section 2.3.4). For one galaxy, Colucci et al. [3] found evidence that suggested the [Ca/Fe] knee could be located at a higher [Fe/H], but only with a handful of clusters. A galaxy’s environment will also shape how it evolves. Galaxies in crowded galaxy clusters, especially those that are located closer to massive galaxies, may have different star formation efficiencies than those in isolation, which could affect, e.g., specific frequency. For example, Peng et al. [7] found that dwarf galaxies with high numbers of GCs were found closer to massive galaxies, suggesting that the gravitational interactions would trigger star and cluster formation. Ultimately, GC formation is intimately linked with a galaxy’s assembly history (see simulations by, e.g., [8]). Observations of distant GC systems can also shed light on the nature of cluster formation, particularly nuclear star cluster formation. While nuclear star clusters in intact galaxies are relatively rare in the Local Group, they are quite prevalent in some distant galaxies. Observations of these systems can help to understand connections between these nuclear star clusters, the field stars in their host galaxies, and other GCs that are associated with the Galaxy (e.g., [9]). Discoveries of new types of galaxies, such as ultra-diffuse galaxies [12], are also challenging the typical relationships between galaxies and GC systems. Such observations will be essential for interpreting the disrupted systems that are observed in M31. Currently, observations of GCs beyond the Local Group are generally limited to integrated light (IL) photometry or low-resolution IL spectroscopy (with a few exceptions; e.g., [3]). Advances in technology over the next few decades will enable distant galaxies to be studied at the same level of detail that M31 is now. 6-3

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6.3 The future Over the next few decades, studies of M31 will expand greatly due to the development of new telescopes and instrumentation. Several of the open questions surrounding M31’s GCs will benefit greatly from these new facilities. The development of extremely large telescopes (ELTs) will provide more photoncollecting power, enabling fainter objects to be observed with higher spatial resolution (e.g., [13]). The capabilities of ELTs could improve detections of metallicity spreads within M31 GCs, because resolved photometry could reach further into GC centers. Fainter substructure in the inner and outer regions could be detected, revealing more diffuse streams from older accretion events. Spectroscopically, individual stars will be easier to observe, both at low- and high-resolution (e.g., [4, 10]). ELTs will therefore enable detailed abundances and kinematics to be determined for stars in streams, the smooth halo, the disk, dwarf galaxies, and GCs. Larger telescopes in space could also make it easier to obtain color-magnitude diagrams of M31 GCs down to the main sequence (e.g., [2]).1 It will also become easier to observe individual stars with dedicated multi-object, spectroscopic telescopes like the Maunakea Spectroscopic Explorer (MSE; [5, 11]). Multi-object capabilities mean that a telescope can observe many stars simultaneously, which significanly reduces the total observing time. Telescopes like MSE could observe large numbers of M31 stars at low-resolution, providing radial velocities and metallicities for individual stars in M31’s streams, dwarf galaxies, and GCs. Finally, studies of M31 will greatly benefit from additional observations of extragalactic systems. ELTs will enable similar surveys like PAndAS to be carried out around distant galaxies, revealing the wealth of substructure surrounding these systems and connecting the GCs to possible birth sites. IL photometry and spectroscopy of GCs, aided by continuing advances in modeling stellar populations, will enable characterizations of the chemical evolution and assembly history of even more systems, providing results that can be compared with cosmological simulations and chemical evolution models. This ongoing work will be essential for understanding M31 in a cosmological context.

References [1] [2] [3] [4] [5] [6] [7] [8]

Brodie J P and Strader J 2006 Ann. Rev. of Astron. & Astr. 44 193 Brown T M, Ferguson H C, Smith E, et al. 2004 Astrophys. J. Lett. 613 L125 Colucci J E, Fernanda Durán M, Bernstein R A, et al. 2013 Astrophys. J. Lett. 773 L36 Evans C, Puech M, Afonso J, et al. 2015 arXiv e-prints, arXiv:1501.04726 McConnachie A, Babusiaux C, Balogh M, et al. 2016 arXiv e-prints, arXiv:1606.00043 Peng E W, Jordán A, Côté P, et al. 2006 Astrophys. J. 639 95 Peng E W, Jordán A, Côté P, et al. 2008 Astrophys. J. 681 197 Pfeffer J, Kruijssen J M D, Crain R A, et al. 2018 Mon. Not. R. Astron. Soc. 475 4309

1 Also see the James Webb Space Telescope white paper by T Brown, at http://sci.esa.int/jwst/47521-brown-t-etal-2008/.

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[9] Sánchez-Janssen R, Côté P, Ferrarese L, et al. 2019 Astrophys. J. 878 18 [10] Szentgyorgyi A, Baldwin D, Barnes S, et al. 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) Conf. Series Proc. of the SPIE 10702 107021R [11] Babusiaux C, Bergemann M, et al. 2019 The MSE Science Team arXiv e-prints, arXiv:1904.04907 [12] van Dokkum P G, Abraham R, Merritt A, et al. 2015 Astrophys. J. Lett. 798 L45 [13] Wright S A, Walth G, Do T, et al. 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) Conf. Series Proc. of the SPIE 9909 990905

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