unveiling the globular cluster systems of early-type ... · spectroscopic data from the keck ii...

Unveiling the globular cluster systems ofearly-type galaxies using wide-field imaging

Sreeja Sudarsanan Kartha

Presented in fulfillment of the requirements

of the degree of Doctor of Philosophy

February 2016

Faculty of Science, Engineering and Technology

Swinburne University of Technology

i

AbstractGlobular cluster (GC) systems can be used as powerful tools to investigate the evolutionary

history of early-type galaxies. In this thesis, we study the GC systems of five early-type

galaxies using wide-field imaging data. We obtained the data from the Subaru telescope,

the Canada-France-Hawaii telescope and the Hubble Space Telescope. Complementary

spectroscopic data from the Keck II telescope were also utilised for this thesis.

We present a wide-field imaging study of GC systems in three early-type galaxies –

NGC 720, NGC 1023 and NGC 2768 – to determine their GC system properties. This

work is the first investigation of the GC system in NGC 720 and NGC 2768 to very

large galactocentric radius (∼ 100 kpc). The three galaxies have clear blue and red GC

subpopulations. The radial surface densities of the GC systems are fitted with Sersic

profiles, and detected out to 15, 8 and 10 galaxy effective radii respectively. The total

number of GCs and specific frequency are determined for each GC system. The ellipticity

of the red subpopulation is in better agreement with the host galaxy properties than is

the blue subpopulation, supporting the traditional view that metal-rich GCs are closely

associated with the bulk of their host galaxies’ field stars, while metal-poor GCs reflect a

distinct stellar halo.

Also, we present an investigation of the GC systems of NGC 3607 and NGC 3608.

In this study, we analyse the radial density, colour and azimuthal distributions of the

GC systems for both galaxies. Our results show that the GC systems of NGC 3607

and NGC 3608 have a detectable spatial extent of ∼ 15, and 13 galaxy effective radii,

respectively. Both GC systems show a clear bimodal colour distribution. We detect a

significant radial colour gradient for the GC subpopulations in both galaxies. NGC 3607

exhibits an overabundance of red GCs on the galaxy minor axis and NGC 3608 shows a

misalignment in the position angles of the GC subpopulations with respect to the galaxy

stellar component. With the complementary kinematic data obtained from the Keck II

telescope, we present the radial velocities of a total of 81 GCs, combined sample from both

galaxies.

With the aid of literature data, we present a new correlation of GC system extent

with host galaxy effective radius. We find a dependence of the relative fraction of blue

to red GCs with host galaxy environmental density for lenticular galaxies (but not for

elliptical or spiral galaxies). We propose that tidal interactions between galaxies in cluster

environments might be the reason behind the observed trend for lenticular galaxies. A

one-to-one relation between the ellipticities of red GCs and the galaxy stellar light em-

phasises the evolutionary similarities between them. In our sample of four slowly rotating

ii

galaxies with kinematically decoupled cores, we observe a higher ellipticity for the blue

GC subpopulation than their red counterparts. An explanation for this observation is that

the galaxies might have experienced multiple minor mergers in the recent past without

any major merger. Also, we investigate the relationship between the colour gradients of

GC subpopulations and the host galaxy stellar mass. We notice the flattening of nega-

tive colour gradients for the blue GC subpopulations with increasing galaxy stellar mass.

Finally, we discuss the formation scenarios associated with the blue GC subpopulation.

iii

Acknowledgements

On this page of the thesis, my heart overpowers the brain to express my happiness.

I know that all the people I met, all the laughter I had, all the tears I shed and even

the nature has contributed or helped me in finishing up my thesis. I am indebted to

the warmth and happiness you all showed towards me. First and foremost, I express my

utmost ’nanni’ (malayalam word meaning thank you) to my supervisor Duncan Forbes. I

still remember our first meeting on Saturday 19th March 2011, when you and Anna came

to my hotel and took me out for lunch. Since then, you were a great guidance for me. I

am thankful to you for your patience, enthusiasm and faith in me throughout the PhD

period. Also, you were always open for chats and discussions, sometimes foolishness, and

always guided me to achieve the best out of my research. I should also thank Anna for

her time and effort to make me settle with the living in Melbourne.

I express my sincere thanks to my co-supervisor, Alister Graham. Happy to mention

here that you offered helping hand many times without even asking for that and also you

guided me whenever Duncan was out of Melbourne. I offer my heartfelt appreciation to

Lee Spitler, who helped me with learning the levels of data reduction. You were always

open to questions and provided me with proper assistance at all difficult situations. I also

thank other staff members at CAS for their support and encouragement during my PhD,

especially from Michael Murphy, Chris Blake, Virginia Kilborn, Sarah Maddison and Liz

Thackray. The successful completion of this thesis is accomplished with the assistance

and suggestions from my PhD review panel members: Jeremy Mould, Emma Ryan-Weber

and Chris Fluke. Also, I acknowledge the genuine help from the Swinburne research staff

especially during the final stage of thesis submission.

I greatly enjoyed the scientific atmosphere in CAS and I thank all the CAS members.

Also, my research has largely benefited from the Tuesday group meetings. Thanks to all

and special note of thanks to Caroline Foster, Christina Blom, Vincenzo Pota, Nicola Pa-

storello, Christopher Usher, Busola Alabi, Joachim Janz and Sabine Bellstedt. I express

my thanks to the SLUGGS survey team with special thanks to Jean Brodie, Aaron Ro-

manowsky and Jay Strader for your valuable comments on my work. Also, I enjoyed the

times I attended various conferences and meetings with Anna Sippel, Georgios Vernardos,

Helga Denes, Shuvo Uddin, Bililign Dullo, Elisa Boera, George Bekiaris and Guido Lyola.

I express my deep gratitude to Annapurni Subramaniam, for introducing me to the

field of research and making my eyes wide open for the night sky magic. Also, I extend

my special thanks to R. Ramesh and Aruna Goswami, for giving further opportunities to

iv

continue in the same field and enjoying the intricacies of astronomy research. My sincere

gratitude also goes to my teachers at school and colleges namely: Sindhu Jose and Mary

Thomas (Mount Carmel GHSS), Jacob Varghese, Sunnykutty K John and Lilly Varghese

(K. G. College), K Indulekha and Nandakumar K (SPAP, MGU).

I also enjoyed the company of friends during my college days and later during research

life in Bangalore. A special note of thanks to Remyachechi for teaching me the basics

of imaging data reduction, Vigeshettan for introducing me to LaTeX, Nagu for IDL fun-

das, Bharatbhayya for your echelle reduction, Koshy for making me learn about elliptical

galaxies and Uday for sharing your passion with Apple laptops. More than learning one or

the other from you people, I greatly enjoyed my life with you all. Also, I express my thanks

to Drisya, Madhu, Anantha, Smitha, Bhavya, Indu, Sindhuja, Arun, Vineeth, Suresh and

Sajal. Here, I also extend my sincere thanks to the smart buddies at Ahmedabad: Nita,

Ranjith, Lekshmi, Midhun, Chitrabhanu, Bhavya and Swapna, for the love and care you

still offering. A very special mention to Sreejith, Veena, Preeja, Fini, Ummru, Sreekutty,

Emily, Deepthi and Vani, for the friendship and smiles we had in our college days.

I express my thanks to the lively city Melbourne and the wonderful people I met here. I

can only start and end this Melbourne life with Priya’s company. More than a friend, she is

a next door kin who is there when you are in need of help. Thanks a lot for your company.

My special thanks to Smithachechi, Pappachan and Appose, for inviting and comforting

me in your home as mine. Also, I offer my gratitude to Remya, Nevin and Joe, for sharing

the pleasant evenings in parks. A special note of thanks to Prince & Raji, Dennichen

& Renjuchechi, Bobo and Poppy, for the healthy debates and tasty dining I parted with

you all. I greatly value the friendship of Akhila, Litty, Athira, Sneha & Ranjith, James,

Manojachan, Byju & Jinu, Kesavan & Anu, Moncy & Gini, Vijay, Cynthia, Shalini and

Sarath, with whom I cherished my life during this PhD.

Finally, it is the time to express my gratitude to the lovely human beings who shaped

and motivated me. With great respect, I treasure the love and belief shown by my

Achamma and Mattemma. Even though they don’t know what I exactly do, they al-

ways supported me. Next I like to extend my sincere thanks to Pappa and Mummy. They

stood beside and backed up me in all crucial situations. Kochacha, I greatly admire the

enthusiasm and care you are giving me through these years. I express my sincere grati-

tude to Jeeson and Neetha, for your encouragement and all the lovely moments we shared

during this journey. I couldn’t move further without mentioning about our angel, Jenie.

Lots of sweet hugs and kisses to you dear. A special note of thanks to all my relatives

and cousins, especially Babukuttan and Manuvettan. My brother Kannan with whom I

v

grown up, fought and shared moments of laughter, is still a naughty pie. Even though we

still fight these days, without asking for help or support, he surely provides me with what

he can. Next my heartfelt thanks goes to Achen and Amma, who every time believe that

I am on the right path and able to win the best out of this life.

Thanks to Kunjoos for allowing me to be away from you during most of the daytime, for

many days. During these last two years, I was getting an added energy that you imparted

and it motivated me for a timely finish. It’s going to be ten years, I met my soulmate

Bless. Words couldn’t express my gratitude and respect to you. I got the spark of doing

PhD from the conversations we had and I confirm that you are the greatest motivator one

can get to attain the same. I also know very well that even if I am submitting this thesis,

you are going to be the happiest person. I am happy and proud that I’ve an inspirational,

supportive and caring partner, with whom I can sail this life with maximum happiness

and contentment. Lastly, I believe in the magical conspiracy of the Universe that always

strengthen my life.

vii

Declaration

The work presented in this thesis has been carried out in the Centre for Astrophysics &

Supercomputing at Swinburne University of Technology between 2011 and 2016. This

thesis contains no material that has been accepted for the award of any other degree

or diploma. To the best of my knowledge, this thesis contains no material previously

published or written by another author, except where due reference is made in the text

of the thesis. All the work presented here is primarily that of the author except the

measurement of radial velocities of Leo II GCs (Section 2.4.4) which are the work of the

collaborator Abusola Alabi. The content of the chapters listed below has appeared in

refereed journals. Minor alterations have been made to the published papers in order to

maintain argument continuity and consistency of spelling and style.

• Chapter 3 has been published as:

Kartha, S. S., Forbes, D. A., Spitler, L. R., Romanowsky, A. J., Arnold, J. A.,

Brodie, J. P., “The SLUGGS survey: The globular cluster systems of three early-

type galaxies using wide-field imaging”, 2014, MNRAS, 437, 273

• Chapter 4, Appendix A and B have been accepted for publication in MNRAS as:

Kartha, S. S., Forbes, D. A., Alabi, A. B., Brodie, J. P., Romanowsky, A. J., Strader,

J., Spitler, L. R., Jennings, Z. G., Roediger, J. C., “The SLUGGS survey: Exploring

the globular cluster systems of the Leo II group and their global relationships”, 2016,

MNRAS (accepted), arXiv:1602.01838

• Chapter 2 and Chapter 5 have sections from both the above publications.

Contributions to the papers from coauthors are included in this work for clarity and

continuity.

Sreeja Sudarsanan Kartha

Melbourne, Victoria, Australia

February 1, 2016

ix

To my Vava and Kunjoos,

for the unfailing support and the disarming smiles.

xi

Life is not easy for any of us, but what of that? We must

have perseverance and above all confidence in ourselves.

We must believe that we are gifted in something, and that

this thing, at whatever cost, must be attained.

–Marie Sklodowska-Curie, French Physicist

Contents

Abstract i

Acknowledgements iii

Declaration vi

List of Figures xv

List of Tables xviii

1 Introduction 1

1.1 Star clusters: Open and Globular . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Globular cluster systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Bimodal nature of GC systems . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3.1 GC system formation scenarios . . . . . . . . . . . . . . . . . . . . . 5

1.3.2 Galaxy and GC formation from cosmological simulations . . . . . . 7

1.4 Early-type galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

1.5 Importance of wide-field imaging study . . . . . . . . . . . . . . . . . . . . . 9

1.5.1 Radial density distribution . . . . . . . . . . . . . . . . . . . . . . . 10

1.5.2 Specific frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.5.3 Azimuthal distribution . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.5.4 Radial colour distribution . . . . . . . . . . . . . . . . . . . . . . . . 12

1.6 Purpose of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.7 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2 Galaxy selection and data acquisition 15

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.2 The SLUGGS survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3 Sample Galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3.1 NGC 720 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3.2 NGC 1023 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.3.3 NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.3.4 NGC 3607 and NGC 3608 . . . . . . . . . . . . . . . . . . . . . . . . 19

2.4 Observations and reduction techniques . . . . . . . . . . . . . . . . . . . . . 20

2.4.1 NGC 720 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.4.2 NGC 1023 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

xiii

xiv Contents

2.4.3 NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.4.4 NGC 3607 & NGC 3608 . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3 Globular cluster systems in three early-type galaxies 29

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.2 Photometry and selection of GC systems . . . . . . . . . . . . . . . . . . . . 30

3.2.1 HST/WFPC2 GC catalogue for NGC 1023 . . . . . . . . . . . . . . 31

3.2.2 Photometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.2.3 Globular cluster selection . . . . . . . . . . . . . . . . . . . . . . . . 33

3.3 Analysis of GC systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.3.1 Surface density profiles . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.3.2 Colour magnitude diagrams . . . . . . . . . . . . . . . . . . . . . . . 39

3.3.3 GC bimodality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.3.4 GC subpopulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.3.5 Radial colour distribution . . . . . . . . . . . . . . . . . . . . . . . . 48

3.3.6 Azimuthal distribution . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.3.7 Specific frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

3.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

4 Globular cluster systems of the Leo II group 63

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.2 Photometry and GC selection . . . . . . . . . . . . . . . . . . . . . . . . . . 64

4.2.1 Photometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

4.2.2 Globular cluster selection . . . . . . . . . . . . . . . . . . . . . . . . 65

4.3 Defining the GC systems of each galaxy . . . . . . . . . . . . . . . . . . . . 66

4.3.1 Surface brightness method . . . . . . . . . . . . . . . . . . . . . . . . 66

4.3.2 Major axis method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

4.3.3 Analysis of kinematic data . . . . . . . . . . . . . . . . . . . . . . . 68

4.4 Analysis of photometric data . . . . . . . . . . . . . . . . . . . . . . . . . . 73

4.4.1 GC system of NGC 3607 . . . . . . . . . . . . . . . . . . . . . . . . . 73

4.4.2 GC system of NGC 3608 . . . . . . . . . . . . . . . . . . . . . . . . . 83

4.5 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

4.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Contents xv

5 Global properties of GC systems 95

5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

5.2 Global relations of GC systems . . . . . . . . . . . . . . . . . . . . . . . . . 96

5.2.1 GC system extent versus galaxy stellar mass . . . . . . . . . . . . . 96

5.2.2 GC extent versus galaxy effective radius . . . . . . . . . . . . . . . . 103

5.2.3 GC system effective radius versus galaxy effective radius . . . . . . . 105

5.2.4 Ratio of blue to red GC number as a function of host galaxy density 107

5.2.5 Ratio of blue to red GC number as a function of host galaxy stellar

mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

5.2.6 GC ellipticity versus galaxy stellar light ellipticity . . . . . . . . . . 111

5.2.7 GC metallicity gradients and galaxy stellar mass . . . . . . . . . . . 116

5.3 GC system formation scenarios . . . . . . . . . . . . . . . . . . . . . . . . . 120

5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

6 Conclusions 125

6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

6.2 Future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

Bibliography 140

A Confirmed GCs around the Leo II group 141

A.1 List of spectroscopically confirmed objects around the Leo II group . . . . . 141

B Mass to light ratio estimations 149

B.1 M/L ratio calculation using Bell et al. (2003) . . . . . . . . . . . . . . . . . 149

Publications 150

List of Figures

1.1 Hubble sequence of galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Bimodal colour distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3 Evolution of the Universe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1 Wide-field image of NGC 720 . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2.2 Wide-field image of NGC 1023 . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.3 Mosaic image of NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.4 Mosaic image of the Leo II galaxy group . . . . . . . . . . . . . . . . . . . . 27

3.1 Transformation of NGC 1023 GC magnitudes from HST to CFHT photo-

metric system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

3.2 Surface density profile for the GC system of NGC 720 . . . . . . . . . . . . 35



3.5 Colour magnitude diagrams for the selected GC candidates using wide-field

data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

3.6 Globular cluster luminosity function for individual galaxies in i band filter . 42

3.7 Colour histograms of GCs after the correction for background contamination 43

3.8 Two dimensional sky images of three galaxies: NGC 720, NGC 1023 and

NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.9 GC subpopulations of NGC 720 . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.10 GC subpopulations of NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . 48

3.11 Colour distribution of NGC 720 GC system with galactocentric radius . . . 50

3.12 Colour distribution of NGC 1023 GC system with galactocentric radius . . 51

3.13 Colour distribution of NGC 2768 GC system with galactocentric radius . . 52

3.14 Azimuthal distribution of NGC 720 GCs . . . . . . . . . . . . . . . . . . . . 54

3.15 Azimuthal distribution of NGC 1023 GCs . . . . . . . . . . . . . . . . . . . 55

3.16 Azimuthal distribution of NGC 2768 GCs . . . . . . . . . . . . . . . . . . . 56

4.1 Surface brightness profiles for galaxies NGC 3607 and NGC 3608 . . . . . . 67

4.2 Spectroscopically confirmed GCs of NGC 3607 and NGC 3608 . . . . . . . . 70

4.3 Velocity distribution of spectroscopically confirmed GCs as a function of

radius with respect to NGC 3608 . . . . . . . . . . . . . . . . . . . . . . . . 71

4.4 GC subpopulations for the spectroscopically confirmed GC systems of NGC

3607 and NGC 3608 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

xvii

xviii List of Figures

4.5 Surface density distribution for the GC system of NGC 3607 . . . . . . . . 74

4.6 Colour magnitude diagram for NGC 3607 . . . . . . . . . . . . . . . . . . . 76

4.7 Radial density distributions of GC subpopulations for NGC 3607 . . . . . . 78

4.8 Azimuthal distribution for the GC system of NGC 3607 . . . . . . . . . . . 80

4.9 Radial colour distribution for the GC system of NGC 3607 . . . . . . . . . 82

4.10 Surface density distribution for the GC system of NGC 3608 . . . . . . . . 84

4.11 Colour magnitude diagram for NGC 3608 . . . . . . . . . . . . . . . . . . . 85

4.12 Radial density distributions of NGC 3608 GC subpopulations . . . . . . . . 86

4.13 Azimuthal distribution for the GC system of NGC 3608 . . . . . . . . . . . 88

4.14 Radial colour distribution for the GC system of NGC 3608 . . . . . . . . . 90

5.1 Radial extent of GC system versus log galaxy mass . . . . . . . . . . . . . . 98

5.2 Radial extent of GC system versus galaxy effective radius for ETGs . . . . 104

5.3 GC system effective radius versus galaxy effective radius . . . . . . . . . . . 106

5.4 Ratio of blue to red GCs versus density of environment . . . . . . . . . . . 109

5.5 Ratio of blue to red GCs versus galaxy stellar mass . . . . . . . . . . . . . . 112

5.6 GC ellipticity versus galaxy stellar light ellipticity . . . . . . . . . . . . . . 114

5.7 Metallicity gradients of GC subpopulations versus galaxy stellar mass . . . 119

List of Tables

2.1 Basic data for the target galaxies . . . . . . . . . . . . . . . . . . . . . . . . 17

2.2 Log of imaging observations . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

3.1 Fitted parameters for the surface density of NGC 720, NGC 1023 and NGC

2768 GC systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.2 The peak values of colour for the blue and red GC subpopulations derived

from GMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.3 Fitted parameters for the surface density of blue and red GC subpopulations

of NGC 720 and NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

3.4 Position angle and ellipticity for the GC systems of NGC 720, NGC 1023

and NGC 2768 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

4.1 Fitted parameters for the surface density profile of the NGC 3607 GC system 75

4.2 Fitted parameters for the surface density profile of NGC 3607 and NGC

3608 GC subpopulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

4.3 Position angle and ellipticity for the GC systems of NGC 3607 and NGC

3608 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

4.4 Fitted parameters for the surface density of NGC 3608 GC system . . . . . 86

5.1 Properties of our galaxy sample for GC system global property study . . . 100



5.2 Effective radius of GC systems from a Sersic fit and their host galaxy . . . 107

5.3 Ellipticity values for GC subpopulations and their respective galaxy stellar

light for the six galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

5.4 List of twelve galaxies observed with metallicity gradients for GC subpop-

ulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 142






xix

1Introduction

My goal is simple. It is a complete understanding

of the Universe, why it is as it is and why it exists

at all. We see the Universe the way it is because if

it were different, we would not be here to observe it.

—Stephen Hawking, Lucasian Professor of Mathematics

Our Universe is comprised of billions of galaxies and they are known as the basic

building blocks. These galaxies were mentioned in Charles Messier’s and John Herschel’s

catalogue as nebulae. In early 1900’s astronomers were puzzled by the spectacular nebulae

or fuzzy blobs seen in the night sky. Later, with the advancement of the 100- inch tele-

scope, the Hooker telescope, Edwin Hubble revealed the true nature of these fuzzy blobs

and found that there are “island universes” of stars outside our Milky Way galaxy. Till

that time, astronomers believed that the extent of the Universe was the extent of Milky

Way galaxy observed by Harlow Shapley (Shapley, 1918). Then, the distance estimations

towards Cepheid variables in so called nebulae resulted in the first ever confirmation of

an extragalactic object, NGC 6822 (Hubble, 1925), followed by M33 (Hubble, 1926a) and

M31 (Hubble, 1929). These discoveries changed the view about our Universe by bringing

forth prepositions such as, 1. there exist other galaxies like our Galaxy and 2. the Universe

is expanding.

Edwin Hubble defined a scheme for understanding galaxy morphologies, for which he

proposed the tuning fork diagram (Hubble, 1926b). Figure 1.1 represents the Hubble

sequence appended with galaxy images. The right of tuning fork diagram is occupied by

barred and unbarred spiral galaxies. Spiral galaxies (Sa–c and SBa–c) or late-type galaxies,

are fast rotating and star forming with spiral arms composed of stars, gas and dust. On

the other hand, the left portion of the tuning fork is covered by early-type galaxies. Early-

1

2 Chapter 1. Introduction

Figure 1.1 Hubble sequence or tuning fork diagram. This diagram shows the morphologicalclassification of galaxies. The handle of the tuning fork is covered by elliptical galaxies(E0–7 implying spherical to completely elliptical morphology, E7 is not shown here), whilethe arms of the tuning fork is occupied by normal or barred spiral galaxies (Sa–c or SBa–c). The joint between the handle and the arms is populated by lenticular galaxies (S0or SB0). The galaxies which do not belong to any of the former categories are namedirregular galaxies (Irr, placed at the extreme right of tuning fork). [Image credit: Galaxyzoo project]

type galaxies include elliptical (E0–7) and lenticular (S0 and SB0) galaxies. Elliptical

galaxies are old, mostly fast rotating galaxies with less, or no, active star formation, while

lenticular galaxies are intermediate between ellipticals and spirals (see Section 1.4 for more

details).

To determine the size and shape of our own Galaxy, Harlow Shapley utilised the

technique of mapping variable stars in 69 groups of stars called globular clusters. Globular

clusters are spherical group of stars containing nearly hundreds of thousand stars in small

area (i.e., thousands of stars in one parsec). He observed the Cepheid Type II variables

and determined the distances towards their host globular clusters. From this study, he

established that the Milky Way spans around 30 kpc in sky and the Sun is situated around

20 kpc distance towards one side of the Galaxy and not at the centre (Shapley, 1918).

As the title emphasis, this thesis studies three major themes: globular cluster sys-

tems, early-type galaxies and wide-field imaging. In the forthcoming sections, we show

that globular cluster systems are among the best tracers to explore the early-type galaxy

1.1. Star clusters: Open and Globular 3

evolutionary history and why we use wide-field imaging.

1.1 Star clusters: Open and Globular

Almost all massive galaxies nurture a rich star cluster system. Star clusters are formed

in every star formation event along with the field stellar component. They are groups

of stars which formed together from the same chemical composition. Hence, the stars

in clusters have same age and origin. Star clusters can either be gravitationally weak,

open clusters, or gravitationally bound, globular clusters. Open clusters usually consist

of hundreds to thousands of stars with varying masses (≤ 103 M�; Portegies Zwart et al.

2010) and reside in the galactic plane of galaxies. As they are gravitationally weak systems,

during the period of their life, they loose stars due to gravitational interactions. They also

experience multiple star formation events as they are always associated with their nebular

clouds and thus consist of stars of very young age (∼ 100 Myr). Due to this, they are

not expected to preserve the formation histories and hence are less useful in studying the

evolution of their host galaxies.

On the other hand, globular clusters (herafter GCs) are gravitationally bound systems

with tens to hundreds of thousands of stars with masses from 104 – 106 M� and mostly

found in the galactic halo, disk and bulge. Hence, GCs are mostly old (∼10 Gyr, Strader

et al. 2005), luminous (≥ 105 L�, Brodie et al. 2011) and compact (∼ 3pc, Harris 1991)

star clusters. GCs of the Milky Way also have similar properties (Harris, 2010a; Katz &

Ricotti, 2014). As they are very compact objects, they are able to withstand the powerful

events of galaxy evolution. They are expected to form during the initial proto-galactic

collapse and in gas-rich merging events; as a consequence they trace the field stars that

form along with them (Brodie & Huchra, 1991; Forbes et al., 1996; Cote et al., 1998).

Thus, GCs can be used as trace particles for host galaxy property studies (Brodie &

Strader, 2006). The luminosity and compact size of GCs make them the brightest and

most easily identifiable individual objects out to large (∼ 200 kpc) galactocentric radii

around galaxies (Richtler et al., 2011; Spitler et al., 2012). This makes them a convenient

probe to study galaxy formation at large radii where the surface brightness of the host

galaxy stars rapidly drops with increasing radius.

1.2 Globular cluster systems

The collection of GCs in each galaxy is called its GC system. Rather than exploring

the properties of individual GCs, we can extract better and reliable information when


we investigate them as groups in distant galaxies. Also, GC systems contribute a better

statistical platform to study the halo cluster properties, where in fact galactic halo regions

are the “fossil records” of the host galaxy. Major photometric studies of GC systems

outside our Galaxy started in 1960’s by the study of Large Magellanic Cloud and Fornax

dwarf (Hodge, 1959, 1961). With the advent of space based telescopes, GC system studies

in large samples of galaxies became more accurate in measurements (Larsen & Brodie,

2000; Kundu & Whitmore, 2001b,a). In the forthcoming sections, we discuss the recent

developments in GC system research.

A major breakthrough in the study of GC systems that motivated for further advance-

ment was the detection of bimodality in colour distributions (Zinn, 1985; Zepf & Ashman,

1993; Ostrov et al., 1993). This implies that each GC system is a combination of two GC

subpopulations. Later, with the aid of the Hubble Space Telescope (HST) multiple photo-

metric studies (Gebhardt & Kissler-Patig, 1999; Larsen et al., 2001; Kundu & Whitmore,

2001a,b) confirmed the existence of bimodality in GC systems.

1.3 Bimodal nature of GC systems

Bimodality indicates two subpopulations in a galaxy (Brodie et al., 2012). Colour bimodal-

ity can be associated with both metallicity and age, which is known as the age-metallicity

degeneracy (Worthey et al., 1995). Spectroscopic line strength studies established an av-

erage age > 8 Gyrs for GCs in ETGs (Puzia et al., 2005; Strader et al., 2005; Beasley

et al., 2008; Woodley et al., 2010). The most recent study by Forbes et al. (2015) explores

the mass-metallicity relation along with the GC subpopulation metallicities in 11 galaxies,

to derive their mean formation epochs. They found an age greater than 11 Gyrs for both

the GC subpopulations (see Figure 1.3 for a diagrammatic representation of their finding).

Since both GC subpopulations are older than 10 Gyr, the bimodality in colour distribution

can be attributed to metallicity bimodality. However, Richtler (2006), Yoon et al. (2006,

2011), Blakeslee et al. (2012) showed that non-linearities in colour-metallicity relation can

produce colour bimodality even though the metallicity distribution is unimodal.

Transforming colours to metallicity connects this bimodality with two stages of GC

formation. The colour/metallicity distribution peaks (refer Figure 1.2 for details) are

represented by blue/metal-poor and red/metal-rich GC subpopulations (Brodie et al.,

2012). The blue GC subpopulations show a range in colour, i.e. 0.6 < (g−i) < 1.0, and also

varies in metallicity, i.e. [Z/H] ranges between −1.95 and −0.55 dex. In contrast, the red

GC subpopulations occupy the colour range from 1.0 < (g−i) < 1.35 and correspondingly

in metallicity from −0.55 to +0.70 dex. Other properties of the two subpopulations differ

1.3. Bimodal nature of GC systems 5

ANRV284-AA44-06 ARI 28 July 2006 14:1

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Figure 1V − I color histogram of globular clusters in the Virgo giant elliptical M87, showing clearbimodality (Larsen et al. 2001; figure from data courtesy of S. Larsen).

slope suggests a close connection between the physical processes responsible for theformation of both GCs and galaxies. Subsequently, a correlation between the colorof just the metal-rich GCs and host galaxy luminosity was found by Forbes, Brodie& Grillmair (1997), Larsen et al. (2001), and Forbes & Forte (2001). The slope ofthis relation was again found to be similar to that of the color-magnitude relationfor early-type galaxies (V − I ∝ −0.018MV ), suggesting that metal-rich GCs formedalong with the bulk of the field stars in their parent galaxies.

With the exception of Larsen et al. (2001), little or no correlation between thecolor of themetal-poorGCs and host galaxy luminosity was reported in these studies,although Burgarella, Kissler-Patig&Buat (2001) and Lotz,Miller&Ferguson (2004)suggested such a relationmight be present, but only for the dwarf galaxies. Larsen andcolleagues found a shallow relation for themetal-poorGCs in their sample of 17mas-sive early-type galaxies, albeit at moderate (3σ ) statistical significance. Strader, Brodie& Forbes (2004b) compiled and reanalyzed high-quality data from the literature andfound a significant (>5σ ) correlation for metal-poorGCs, extending frommassive Esto dwarfs over ∼10 magnitudes in galaxy luminosity. The relation is indeed relativelyshallow (V − I ∝ −0.009MV , or Z ∼ L0.15), making it difficult to detect, especiallyin heterogeneous data sets. This same slope was confirmed by J. Strader, J.P. Brodie,L. Spitler & M.A. Beasley (submitted) and Peng et al. (2006a) for early-type galaxiesin Virgo. Figure 2 shows [Fe/H] versus MB for both subpopulations; the GC peaksare taken from Strader, Brodie & Forbes (2004b) and J. Strader, J.P. Brodie, L. Spitler& M.A. Beasley (submitted) and have been converted from V − I and g − z usingthe relations of Barmby et al. (2000) and Peng et al. (2006a), respectively. These data,together with ancillary information about the GC systems, are compiled in Table 1.The true scatter at fixed MB is unclear, because the observational errors vary amonggalaxies, and there may be an additional component due to small differences between

www.annualreviews.org • Extragalactic Globular Clusters 197

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Figure 1.2 Colour histogram of M87 GC system. Two colour peaks at 0.95 and 1.2 in the(V-I) colour are clearly detectable and are named as blue and red GC subpopulations,respectively. [Image credit: Brodie & Strader (2006), Data credit: Larsen et al. (2001)]

such as azimuthal distribution (Park & Lee, 2013; Wang et al., 2013), spatial distribution

(Bassino et al., 2006b; Strader et al., 2011), radial colour distribution (Forte et al., 2001;

Harris, 2009a; Forbes et al., 2011) and also kinematics (Arnold et al., 2011; Foster et al.,

2011; Pota et al., 2013). For example, the red subpopulations are generally concentrated

in the host galaxy centre, while the blue GC subpopulations are detected out to larger

galactocentric radii (see Section 1.5 for further examples in GC subpopulation studies).

With the aid of accurate photometry techniques, bimodal colour distribution is iden-

tified in more galaxy samples (Peng et al., 2006; Tamura et al., 2006; Spitler et al., 2008;

Harris, 2009a; Sinnott et al., 2010; Liu et al., 2011). In some cases, the colour distribu-

tion is even found to be trimodal, e.g. in the case of NGC 4365 (Blom et al., 2012) and

NGC 4382 (Peng et al., 2006). To better understand these multimodal distributions, three

“classic” scenarios of GC system formation were proposed.

1.3.1 GC system formation scenarios

Explaining the colour bimodality distribution in the context of host galaxy formation,

three broad scenarios were put forward. In 1992, elaborating on the work of Toomre &


Figure 1.3 Cosmic timeline from Big Bang to the present day Universe. This picture showsthe evolution of the Universe from the Big Bang event, the age of the Universe. It alsoshows that the blue and red GCs are ∼ 12.5 and 11.5 Gyr old stellar systems formed alongwith the host galaxies. [Image credit: NASA/CXC/SAO and Aaron J. Romanowsky]

Toomre (1972), Ashman & Zepf (1992) first proposed that the colour bimodality is the

result of a gas-rich merger of disk galaxies. They suggested that the blue GCs are intrinsic

to the spiral galaxies, while red GCs are formed during the merger. A major observable

out of this scenario is luminosity weighted GC number (SN , see Section 1.5.2 for more

details). With the observations from Harris (1991), it is found that SN for elliptical

galaxies are higher than spiral galaxies. Forbes et al. (1997) suggested that the GCs

have an in-situ mode of formation. According to this scenario, the blue GCs are formed

first in the initial collapse with limited field star formation. A quiescent period follows,

then red GCs are formed in a metal-rich environment along with the bulk of the stars in

the galaxy. Accretion of blue GCs may also contribute. Later, Santos (2003) suggested

cosmic reionization as the cause for truncation of blue GC formation. A third scenario

was proposed by Cote et al. (1998, 2000, 2002) in which the red GCs are inherent to the

host galaxy (similar to Forbes et al. 1997) while the blue GCs are accreted via mergers or

tidal stripping. Regarding this scenario, we expect metal poor stars to be accreted along

with GCs.

1.3. Bimodal nature of GC systems 7

Strader et al. (2004, 2005) carried out studies on massive elliptical galaxies to check

the feasibility of above mentioned scenarios of GC formation. They suggested an in-situ

plus accretion origin for the blue GC subpopulations. Massive galaxies created blue GCs

early in their formation (in-situ) and also accreted blue GCs from dwarf galaxies residing

in high dense regions. These two processes shaped the blue GC subpopulation from in-situ

plus accretion scenarios. Later, as in Forbes et al. (1997) scenario, a period of quiescent

phase follows and then the formation of red GCs and field stars. When evaluating the

acceptance of these different formation scenarios, from an angle of hierarchical galaxy

formation, we suspect that all the above scenarios are feasible in individual or combined

form.

Many arguments for and against these scenarios can be found in the literature and the

current understanding is that all galaxies have undergone at least one merger/accretion

phase of evolution. Signatures of different stages of galaxy evolution are best preserved

in galaxy outer halos rather than in the complex inner regions. As outer halo regions

have long dynamical times, they are helpful in providing information about the initial

conditions of host galaxies. Outer halos in nearby galaxies extend to wide fields of view

(nearly tens of arcminutes on the sky). Investigation of GCs in outer halos gives a unique

opportunity to trace the formation and evolution of host galaxies.

1.3.2 Galaxy and GC formation from cosmological simulations

In the last 15 years, many theoretical studies involving the formation of GC subpopula-

tions and their host galaxies were published. Here, we present a recap of the major studies.

Using a semianalytic model of galaxy formation, Beasley et al. (2002) reproduced the GC

bimodality in colour, where blue and red GCs formed in protogalactic discs and gaseous

mergers, respectively. They proposed that red GCs trace the galaxy properties as they are

associated with a galaxy merger. Based on dissipationless galaxy merger numerical simu-

lations, Bekki et al. (2005) investigated the kinematic properties of GC systems in merged

galaxies. They proposed that the resultant GC system will be more flattened and rotate

at large radius if it was a major merger. In contrast, GC systems of spherical structure

with less rotation at large radius are expected in the case of minor or unequal mergers.

Using N-body cosmological simulations, Bekki et al. (2008) investigated the structural,

chemical and kinematical properties of GC systems in early-type galaxies. Their simula-

tions proposed that the majority of halo GCs originated from low-mass galaxies. They

also proposed that the number fraction of red GCs is independent of bulge formation.


Muratov & Gnedin (2010) presented a cosmological model of GC formation semi-

analytically. They proposed that early mergers of small galaxies result in blue GC forma-

tion and late mergers of massive galaxies create both blue and red GCs. In their model,

GC bimodality is naturally generated rather than the model presented by Beasley et al.

(2002). Tonini (2013) has constructed a theoretical model to investigate GC bimodality.

She predicts that the GC bimodality is a direct outcome of hierarchical galaxy assem-

bly. Also, she predicted that a larger fraction of blue GCs can be found in early-type

galaxies residing in higher density environments. Another study by Katz & Ricotti (2013)

predicted the origin of blue GCs from dwarf galaxies that later assembled into a massive

galaxy. This model thus supports Strader et al. (2004, 2005). Recently, Trenti et al. (2015)

proposed another scenario by which GCs are formed from a gas-rich merger of two or more

dark matter minihalos and is capable of reproducing GC system properties such as ages,

spatial distribution, bimodal distribution etc.

Using cosmological simulations, Oser et al. (2010) modelled a multiphase galaxy evo-

lution. For massive galaxies (1.4 - 2.6 x 1011 M�) generated by these simulations, the

accreted stellar mass accounts for up to 87% of the final stellar mass. But for low mass

galaxies (0.3 - 0.7 x 1011 M�), 67% of the stellar mass comes from the in-situ formation.

According to the simulations, galaxies produce stellar mass from in-situ formation in the

inner region while the accreted mass will be deposited in the outskirts. The region of

differentiation between in-situ and accreted mass is termed as the transition region. This

work predicted an increase in the transition radius with galaxy mass. Naab et al. (2009)

and Oser et al. (2010, 2012) have shown that the accreted stellar systems settle into the

outer regions of the host galaxies. These simulations suggested a build up of an envelope

over time and an increase in size. Forbes et al. (2011) detected inner colour gradients

for blue and red GC subpopulations of NGC 1407 till the galactocentric radii of 8.5 Re

and a null gradient further out. They explained that the inner gradient is due to in-situ

produced mass and the null gradient might have resulted from the accretion of mass to

the galaxy outskirts.

1.4 Early-type galaxies

Considering the two major galaxy morphologies, early-type galaxies (hereafter ETGs)

enclose larger GC systems than late-type galaxies (hereafter LTGs) due to their mass

content. In addition, ETGs are observed to have low star formation rates and thus have

minor photometric dust extinction corrections when compared to dust filled LTGs. To

better understand the formation of ETGs, it is useful to study their oldest stellar compo-

1.5. Importance of wide-field imaging study 9

nents such as GCs. As GCs are expected to form in every major star formation episode,

they trace the formation and evolution of host galaxies (Ashman & Zepf, 2001; Brodie &

Strader, 2006; Harris, 2010b). Additionally, the majority of them retain their properties

even after the violent merger or interaction events in their neighbourhood and hence, we

are availed with a good statistics in most galaxies. Thus, establishing connections be-

tween the properties of GC systems and their host galaxies can help in understanding the

formation of GC systems and their parent galaxies. Other than GCs, planetary nebulae

can also be used to trace the properties of galaxies (Romanowsky et al., 2003; Coccato

et al., 2009; Napolitano et al., 2009; Cortesi et al., 2013). In this thesis, we explore the

GC systems of five ETGs in which four galaxies have their first investigation of GCs to >

100 kpc from the centre.

1.5 Importance of wide-field imaging study

The introduction of the space based telescope, HST, made improvements in the extra-

galactic GC research by enabling proper classification of GCs and background galaxies. It

also expanded the literature with the availability of larger samples of GC systems studied

(Kundu & Whitmore, 2001a,b; Peng et al., 2006). Even though high resolution HST im-

ages result in minimum contamination, multiple pointing imaging is required to cover the

total GC system of massive galaxies. Thus, to investigate galaxy halos out to ∼ 100 kpc

radii, wide-field multi-filter images from the 8- or 10- meter class ground based telescopes

are a better option.

The field of extragalactic GC research is emerging with the advancement in the wide-

field imaging and multi-object spectroscopy. With the introduction of multi-object spec-

troscopy, multiple studies e.g., GC kinematics (Pota et al., 2013), GC stellar popula-

tions (Usher et al., 2012), GC subpopulation age (Forbes et al., 2015), dark matter (Ro-

manowsky et al., 2009), etc. of ETGs have been published recently. In the study of

extragalactic GCs, wide-field imaging can be hundreds of times more efficient than spec-

troscopy, but it provides little direct information about stellar populations (i.e. metallicity,

kinematics). However, we can generate indirect metallicity measurements from different

colour combinations (Peng et al., 2006; Faifer et al., 2011; Usher et al., 2013). To detect

the GCs in the galaxy outskirts of massive galaxies, multi-object spectroscopy needs mul-

tiple observations and hence is an expensive task. On the other hand, wide-field imaging

is less cost effective, but is given with less number of direct parameters such as magnitude,

colour etc. However, the data from wide-field imaging studies are the basis for further

study such as multi-object spectroscopy.


With the aid of accurate wide-field imaging data, the global properties of globular

cluster systems can be properly explored. The global properties of globular cluster systems

include their radial density, colour and azimuthal distributions, total number of globular

clusters, specific frequency etc. A brief description about the different global properties

of GC systems is given in the following sections.

1.5.1 Radial density distribution

Radial density distribution provides an estimation of the total GC system extent or the

galactocentric radius at which GCs can be detected above the background. The full

radial extent of large GC systems can only be investigated with wide-field imaging data.

From the radial density distributions of individual GC subpopulations (blue and red), the

characteristics of the subpopulations such as their extent and concentration (centrally or

extended) can be investigated. Most previous studies were carried out using four meter

class telescopes (e.g. Rhode & Zepf 2003; Rhode et al. 2007, 2010; Young et al. 2012),

which sometimes failed to find GC subpopulations. Multiple wide-field imaging studies

(Bassino et al., 2006b; Faifer et al., 2011; Strader et al., 2011; Forbes et al., 2012a) found

a similar slope between host galaxy starlight and red GC density distribution suggesting

a coeval formation. Also, it is observed that the halo component of a galaxy is associated

with the blue GC subpopulation (Forte et al., 2005, 2012; Forbes et al., 2012a; Escudero

et al., 2015). Forbes et al. (2012a) found a good agreement between galaxy diffuse X-ray

emission and the surface density of the blue GCs for nine ellipticals.

The radially extended blue GC subpopulation residing in galaxy haloes suggests that

they are a very old stellar component formed early, or accreted later, into the galaxy out-

skirts. The similarity of red GCs with the galaxy stellar light supports a coeval formation,

but their origin (from the enriched gas of a parent galaxy or accreted gas) is not clear.

Hence, to associate the formation of different GC subpopulations with galaxy formation

events, we have to extract the (dis)similarity between their properties and a complete

estimation is aided with wide-field imaging data.

1.5.2 Specific frequency

Another global property that can be measured with wide-field imaging data is the total

number of GCs weighted by the host galaxy luminosity and can only be estimated from the

radial density distribution (note here that the turnover magnitude from the GC luminosity

distribution is required). The specific frequency (SN ) of a GC system is the total number

of GCs in a galaxy per unit host galaxy luminosity. The specific frequency of GCs was

1.5. Importance of wide-field imaging study 11

introduced as a measure of the richness of the GC system. The value of SN is defined by

the relation of Harris & van den Bergh (1981):

SN = NGC 100.4(MTV +15) (1.1)

where NGC (the total number of GCs) is determined from the radial density distribu-

tion. An advantage of wide-field imaging is the accurate determination of specific frequency

with reduced errors. For example, the SN for NGC 4365 varies from 3.86 ± 0.71 (Peng

et al., 2008) with the small field of view of HST imaging to 7.75 ± 0.13 (Blom et al., 2012)

with wide-field Subaru data.

1.5.3 Azimuthal distribution

The two dimensional spatial distribution of GC systems can be constructed with imaging

data. Estimation of position angle, ellipticities and two dimensional sub-structures can

be carried out. Most previous studies carried out using smaller telescopes (e.g. Rhode

et al. 2010; Young et al. 2012), are unable to probe very far down the GC luminosity

function and thus yield too few GCs to properly separate the system in red and blue

subpopulations. Literature studies of galaxies like NGC 4636 (Dirsch et al., 2005) and

NGC 1316 (Gomez et al., 2001), show that the azimuthal distribution of red GCs closely

matches that of the spheroid/bulge of the host galaxy. Such observations support the idea

that the bulk of galaxy stars have a coeval origin with the red GC subpopulation.

Park & Lee (2013) studied the azimuthal distribution of GC systems in 23 ETGs

using the data from the Advanced Camera for Surveys (ACS) mounted on the HST.

They found that the ellipticities of the red GC subpopulation match with the galaxy

stellar light ellipticities with a one-to-one correspondence. They also found that blue

GC subpopulations show a similar but less tight relation. Wang et al. (2013) using the

ETGs, from the ACS Virgo Cluster Survey (VCS), concluded that both red and blue GC

subpopulations significantly align in position angle with the galaxy stellar light, although

in a weaker way for blue GC subpopulations. Several single galaxy studies concluded

that the galaxy stellar light is mimicked by red GC subpopulation in position angle and

ellipticity, but the blue GC subpopulation is differently distributed (e.g. NGC 720, NGC

1023: Kartha et al. 2014, NGC 4365: Blom et al. 2012, NGC 5813: Hargis & Rhode 2014).


1.5.4 Radial colour distribution

Another significant feature to investigate in GC systems is the colour gradient of the two

subpopulations. The decreasing mean colour of GC subpopulations with increasing galac-

tocentric radius is a key recent observation (Bassino et al., 2006a; Harris, 2009b; Arnold

et al., 2011; Faifer et al., 2011; Forbes et al., 2011; Blom et al., 2012; Usher et al., 2013;

Hargis & Rhode, 2014). More specifically, the steepness of the radial colour profile points

towards two different formation processes, dissipation and accretion/merger (Tortora et al.,

2010). Harris (2009b) studied the GC system of M87 and found a colour gradient for blue

and red subpopulations out to 8 Re. He found a constant colour gradient for the blue GCs

and a null detection of red subpopulations beyond 8 Re. Recently, Forbes et al. (2011)

studied the colour gradient for NGC 1407 GC subpopulations and found that both GC

subpopulations have a steep negative gradient within ∼ 8.5 Re and a constant colour to

larger radii. They explained this colour trend as being compatible with two-phase galaxy

formation (Oser et al., 2010). This implies that the inner GCs are formed during a dissi-

pative collapse phase, whereas the outer GCs are acquired during late accretion/merger.

Also, later accretions/mergers can wash out the pre-enriched gradient completely. Thus,

exploring the radial colour distribution can retrieve clues about formation events that

happened in the host galaxy’s history.

1.6 Purpose of the Thesis

In this thesis, we study the GC systems of ETGs using wide-field imaging techniques. We

explore the GC systems of five intermediate mass (11 < log(M?) < 11.5 M�) ETGs (in con-

trast earlier wide-field studies carried out mostly on massive ETGs, or intermediate mass

ETGs studied only for the central region) residing in field or small group environments. We

investigate their major properties such as radial density distribution, colour distribution,

azimuthal distribution, total number of globular clusters and specific frequency, which can

only be accurately analysed with radially extended multi-filter photometric data. Most of

the literature studies of GC systems extended only out to a galactocentric radius of 5 Re.

Using the wide-field imaging data from the Subaru/Suprime-Cam, we go out to ∼ 15 Re

from the centre. In this work we also aim to examine the global properties of individual

(red and blue) subpopulations and analyse their connection with host galaxy stellar light

(e.g., ellipticity, effective radius, etc.). By investigating the global properties of globular

cluster subpopulations and the connection with host galaxy properties, we plan to add in-

formation about the formation histories of globular cluster subpopulations and their host

1.7. Thesis outline 13

galaxies.

1.7 Thesis outline

This thesis is organised in six chapters, including this introduction Chapter. In Chapter

1 we explore the importance of GC system study in the formation and evolution of early-

type galaxies. We discuss, in this chapter, the different scenarios associated with multiple

GC subpopulations in early-type galaxies and the significance of wide-field imaging. Using

the wide-field imaging data, we unveil the different properties such as radial density, radial

colour and azimuthal distributions to large extents of galactocentric radii. We also explore

how these properties give clues to better understand host galaxy formation.

In this thesis, we investigate the GC systems of five early-type galaxies and the criteria

for galaxy selection is presented in Chapter 2. Also, we review the literature for the current

understanding of each galaxy. We explain the acquisition and reduction of data for the

target galaxies. Chapter 3 presents the study of GC systems of three field galaxies using

Subaru and HST imaging data. We discuss the selection methods for the GC systems

and analysis of different properties. Exploration of GC system subpopulations is carried

out for the three galaxies, and their (dis)similarities with host galaxy properties are also

investigated.

The GC systems of Leo II group are studied in Chapter 4. In this Chapter, we explore

different methods to separate the GC systems of three galaxies. The various distributions

of GC systems in the two galaxies are analysed. Also, we examine the GC subpopulations

and study their characteristics with the host galaxy. Based on the results from the different

GC distributions, we investigate the chance of interaction between them.

In Chapter 5, we explore the correlations of global properties of GC systems (including

GC systems of other well studied early-type galaxies) with host galaxy mass, galaxy effec-

tive radius and local environment density. For this study, we made use of literature studied

galaxies (∼ 40) in addition to the five galaxies. Chapter 6 summarises the results from

the preceded Chapters. This Chapter discusses the implications of the wide-field imaging

data to better evaluate the GC system properties and hence their formation scenarios.

Finally, we provide suggestions for future directions.

2Galaxy selection and data acquisition

2.1 Introduction

Even though early-type galaxies (ETGs) look simple in morphological structures, they

are among the most complex systems in the Universe. The diverse characteristics of

ETGs include misalignments in photometric and kinematic features (Krajnovic et al.,

2011; Barrera-Ballesteros et al., 2015), gradients in age and metallicity (Spolaor et al.,

2010; Tortora et al., 2010; Hirschmann et al., 2015), presence of substructures (Duc et al.,

2015) etc. In order to interpret these characteristics, we need to understand the formation

mechanisms that created them and the evolutionary transformations that shaped them.

To better comprehend the ETG assemblies, the discrete tracers such as GC systems can be

used as a powerful tool since the formation of GC systems and host galaxies are strongly

linked.

In this thesis, we study the characteristics of GC systems in five ETGs using the

wide-field imaging data. Here, we focus on five nearby ETGs: NGC 720, NGC 1023,

NGC 2768, NGC 3607 and NGC 3608, that are part of the ongoing SLUGGS1 survey. Of

these five galaxies, four galaxies are main targets and NGC 3607 is counted as a bonus

galaxy in the survey. We select these five galaxies based on two criteria: luminosity and

environment. They all belong to intermediate mass luminosity range of galaxies (see Table

2.1 for details). Another criterion is the galaxy environment, in which NGC 720 is a field

galaxy, NGC 1023 and NGC 2768 are the brightest members of two small groups while

NGC 3607 and NGC 3608 are two brightest central members of the Leo II group. Hence,

we include a sample that are located in diverse environments, but with similar mass and

luminosity values. In addition, NGC 720, NGC 1023 and NGC 2768 are among the most

elongated galaxies in the survey. We aim to study the GC system distributions of these

1http://sluggs.swin.edu.au/

15

16 Chapter 2. Galaxy selection and data acquisition

galaxies and examine how these distributions correlate with the host galaxy properties.

This Chapter is organised as follows. Section 2.2 gives an overview of the SLUGGS

survey. In Section 2.3, we present a brief literature review about our five galaxies. The de-

tails about observations and the reduction techniques are described in Section 2.4. Finally,

we summarise the Chapter in Section 2.5.

2.2 The SLUGGS survey

The SAGES Legacy Unifying Globulars and GalaxieS (SLUGGS) survey (Brodie et al.,

2014) is the vital part of the SAGES (Study of the Astrophysics of Globular Clusters

in Extragalactic Systems) network2. The SLUGGS survey is a wide-field study of 25

nearby ETGs (plus 3 bonus galaxies) using imaging and spectroscopy techniques. The

observational findings are interpreted with the knowledge availed from the different galaxy

formation models. The survey include galaxies within a distance of 30 Mpc that are located

in diverse galaxy environments, covering a wide range of galaxy properties.

For the SLUGGS survey, the imaging data were mainly obtained from the Subaru

Prime Focus Camera (Suprime-Cam, Miyazaki et al. 2002) instrument mounted on the 8-

m Subaru telescope. The observations of wide-field multi-colour images from the Suprime-

Cam instrument are mostly aided with the sub-arcsecond seeing on Mauna Kea. In certain

cases, we utilized the archival data from the MegaCam (Boulade et al., 2003) instrument

on the Canada France Hawaii Telescope (CFHT). Also, the survey made use of the com-

plementary images from the Hubble Legacy Archive (HLA3). All the spectroscopic data

for the survey galaxies were obtained from the DEep Imaging Multi-Object Spectrograph

(DEIMOS, Faber et al. 2003) installed on Keck II telescope.

2.3 Sample Galaxies

We present the GC system study of five ETGs as part of this thesis and their basic

properties are recorded in Table 2.1. In this Section, we briefly overview the five sample

galaxies.

2.3.1 NGC 720

NGC 720 is an X-ray bright, relatively isolated elliptical galaxy. The morphological clas-

sification is an E5 (de Vaucouleurs et al., 1991). NGC 720 has been well studied in X-rays

2http://sages.ucolick.org/index.html3http://hla.stsci.edu/

2.3. Sample Galaxies 17

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by Buote & Canizares (1994, 1996, 1997) and Buote et al. (2002). The X-ray studies

showed an isophotal twist which is absent at optical wavelengths. NGC 720 is found to be

a strong X-ray source with filaments extending from the nucleus of the galaxy and curving

towards the south (Buote & Canizares, 1996). Kissler-Patig et al. (1996) studied the GC

system of NGC 720 out to a galactocentric distance of 4.37 arcmin (30 kpc). They did not

study the properties of GC subpopulations, only the total system. They found the GC

system to resemble the host galaxy light distribution in terms of ellipticity, position angle

and surface density. In contrast, the properties of the GC system did not match those of

the X-rays. Forbes et al. (2012a) found a similar slope for the X-ray surface brightness

profile and the surface density of the blue GC subpopulation of NGC 720.

2.3.2 NGC 1023

NGC 1023 is a nearby S0 galaxy at a distance of 11.1 Mpc (Cappellari et al., 2011) An

interesting aspect of this lenticular galaxy is its bluer eastern companion, NGC 1023A.

HI maps of NGC 1023 show a high concentration of neutral hydrogen gas around NGC

1023A (Sancisi et al., 1984). Capaccioli et al. (1986) did not detect any traces of emission

lines in the spectrum of NGC 1023, indicating no current star formation. Larsen & Brodie

(2000) studied the central GCs of NGC 1023 using HST/Wide-Field Planetary Camera

2 (WFPC2) imaging. They found 221 GCs and a bimodal colour distribution. They

also found the presence of red extended (effective radii > 7 pc) GCs, naming them ‘faint

fuzzies’(FFs). Cortesi et al. (2011) used the planetary nebulae (PNe) to analyze the

kinematics of NGC 1023. They found that the kinematics of the galaxy resembles a spiral

galaxy, supporting the theory of transformation of S0 galaxies from spiral galaxies. Young

et al. (2012) studied the GC system of NGC 1023 using imaging data from the 3.5-meter

WIYN telescope and estimated the total number of GCs to be 490 ± 30, with SN = 1.7

± 0.3. They also found a statistically significant bimodal colour distribution for the GC

system. Forbes et al. (2014) detected 81 red and 27 blue FFs using the HST/Advance

Camera for Surveys (ACS) data. They found that half of the blue FFs are associated with

the companion galaxy NGC 1023A which may be originated from a recent interaction

between NGC 1023 and NGC 1023A.

2.3.3 NGC 2768

NGC 2768 is catalogued as a lenticular galaxy in the Carnegie Atlas of Galaxies (Sandage

& Bedke, 1994) and an elliptical E6 in the Third Reference Catalogue of Bright Galaxies

(RC3, de Vaucouleurs et al. 1991). Crocker et al. (2008) traced the interstellar medium

2.3. Sample Galaxies 19

of NGC 2768 from CO emission, finding a molecular polar disc, which suggests a merger

history for NGC 2768. Kundu & Whitmore (2001b) studied the GC system of NGC 2768

using single HST/WFPC2 pointing and found a statistically significant bimodal colour

distribution. Pota et al. (2013) did a kinematic study of the GC systems of 12 early-type

galaxies including NGC 2768. They found GC bimodality in (Rc−z) colour. They also

found that the rotation velocity of red GCs matches the galaxy stars, supporting coeval

formation.

Usher et al. (2012) carried out a study of CaT metallicity distribution of NGC 2768

GCs, but did not find bimodality in the CaT metallicity for the GCs. The available

photometry for the galaxy was poor and they obtained spectra only for a few GCs, which

they propose as the reason for not detecting bimodality in metallicity. Forbes et al. (2012b)

analyzed the kinematics, combining PNe, GCs and galaxy starlight. They found similarity

in the radial density distribution between red GCs, galaxy bulge PNe and galaxy starlight,

strengthening the idea of coeval evolution. Kinematic studies of these three components

up to 4 Re showed a good agreement between them.

2.3.4 NGC 3607 and NGC 3608

NGC 3607 and NGC 3608 are the brightest ETGs in the Leo II group. NGC 3607 is a near

face-on lenticular galaxy while NGC 3608 is an E1−2 elliptical galaxy. In the same system

there is a third galaxy, NGC 3605, which is a low mass galaxy of E4−5 morphology. Table

2.1 presents the main characteristics of the three galaxies with NGC 3607 as the central

galaxy in the group. NGC 3608 and NGC 3605 are situated at a distance of 6 arcmin north-

east and 2 arcmin south-west from NGC 3607. Kundu & Whitmore (2001a,b) investigated

the GC systems of 57 ETGs including NGC 3607 and NGC 3608 using HST/WFPC2 data

in V and I filters. For these galaxies they detected 130 and 370 GCs, respectively, from

single pointing imaging. They did not find a sign of a bimodal colour distribution in either

galaxy.

With the same HST/WFPC2 data, Lauer et al. (2005) investigated the surface bright-

ness profiles of NGC 3607 and NGC 3608. They mentioned that NGC 3607 contains a

symmetric, old and tightly wrapped outer dusty disk to which a second disk is settling

in a perpendicular direction. They explained this observation as an infall of gas directly

to the centre of galaxy with no interaction with the outer disk. They also detected the

remnants of a pre-existing dusty disk in NGC 3608. Terlevich & Forbes (2002) derived

the ages of 150 galaxies using the spectral line indices and found 5.8, 3.6 and 10 Gyr ages

for NGC 3605, NGC 3607 and NGC 3608 respectively. Afanasiev & Silchenko (2007) car-


Table 2.2 Log of imaging observations.Galaxy Filter Obs. date Seeing Telescope Exp. timeNGC HST∗ (”) (s)

720g 2008 Nov. 28 0.88 Subaru 1770i 2008 Nov. 28 0.98 1370

1023g 2004 Sep. 10 0.71 CFHT 1232i 2004 Sep. 11 0.73 1100

2768g 2011 Jan. 03 0.95 Subaru 4320r 2011 Jan. 04 0.77 1860i 2011 Jan. 04 0.75 1296

3607/3608g 2011 Jan. 03 0.81 Subaru 3743r 2011 Jan. 04 0.80 1560i 2011 Jan. 04 0.80 1200

∗ Hawaii-Aleutian Standard Time

ried out a kinematic and structural analysis for the central regions of these galaxies using

integral-field spectroscopy. They confirmed kinematically decoupled cores (KDCs) with

enhanced magnesium indices, but the KDCs had a similar age to that of outer regions.

Later, Rickes et al. (2009) investigated the metallicity distribution, stellar population

and ionised gas in NGC 3607 using long-slit spectroscopy. They found stellar components

ranging in age from 1 to 13 Gyr between the centre and a 30 arcsec radius of the galaxy’s

centre. As part of the ATLAS3D survey, McDermid et al. (2015) determined the mass-

weighted ages for NGC 3605, NGC 3607 and NGC 3608 as 8.1 ± 0.8, 13.5 ± 0.7 and 13.0

± 0.7 Gyr respectively. Also, from the ATLAS3D survey Duc et al. (2015) studied these

galaxies using the deep multi-band images from the Canada France Hawaii Telescope.

They mentioned that NGC 3607 and NGC 3608 are interacting galaxies with the presence

of weak dust lanes and ripples.

Based on the ROSAT data, two peaks were detected in diffuse hot X-rays on NGC

3607 and NGC 3608 (Mulchaey et al., 2003). They proposed that the two galaxies are

undergoing a merger. Later, Forbes et al. (2006b) detected an extended diffuse X-ray

emission around the Leo II group.

2.4 Observations and reduction techniques

2.4.1 NGC 720

Photometric data for NGC 720 were obtained using the Suprime-Cam instrument mounted

on the 8-m Subaru telescope. The Suprime-Cam imager consists of ten CCDs with indi-

2.4. Observations and reduction techniques 21

vidual sizes of 2048 x 4096 pixels and a pixel scale of 0.202 arcsec, covering a maximum

sky area of 34 x 27 square arcmin. The sky conditions were good with an average seeing

of ∼ 0.93 arcsec for g and i filters. Multiple exposures in a dithered pattern were taken

to fill the gaps between individual CCDs. The observation log is tabulated in Table 2.4.

Figure 2.1 displays the wide-field image obtained from the Suprime-Cam imager.

The Suprime-Cam Deep Field Reduction package 2, SDFRED2 (Ouchi et al., 2004)

is utilised to carry out the pre-processing of the Suprime-Cam data. The pipeline in-

cludes scripts for flat fielding, distortion and atmospheric dispersion corrections. The

pre-processed images were aligned and combined to form the mosaic image using a combi-

nation of softwares SExtractor (Bertin & Arnouts, 1996), Scamp (Bertin, 2006) and Swarp

(Bertin et al., 2002)4. The SExtractor run on the individual CCD images selects point

sources with a three sigma threshold above the background level. The relative positions

between the selected objects were matched with an astrometric reference catalogue (USNO

or SDSS) using the Scamp software to generate the astrometric solution. Using the Swarp

software and the astrometric solution, the multiple CCD images were aligned and stacked

to produce the mosaic image. There are no significant gradients detected on the mosaic

images in the region of GC system extent.

We also acquired the central GC radial surface density distributions for NGC 720 from

Escudero et al. (2015, in prep.). This data set was observed in g, r, i filters using the

Gemini Multi-Object Spectrographs (GMOS, Hook et al. 2004). NGC 720 was observed

along with five other galaxies published in Faifer et al. (2011). A detailed description

about the observations and data reduction is given in the same publication.

2.4.2 NGC 1023

The wide-field imaging data for NGC 1023 were acquired from the CFHT archive. Ob-

servations were taken with the MegaCam imager. The detector consists of a 9 x 4 mosaic

of 2048 x 4612 CCDs with a scale of 0.187 arcsec giving a field of view of 0.96 x 0.94

square degree. A series of images taken in g and i filters was processed through the

MegaCam image stacking pipeline named MegaPipe (Gwyn, 2008). MegaPipe includes

the pre-processing (bias and dark subtraction, flat fielding) of the images. The pipeline

carries out an astrometric and photometric calibration for the MegaCam images. The

individual CCD images were then mosaiced with Swarp software. Figure 2.2 shows the

wide-field image of NGC 1023 observed using the CFHT/MegaCam instrument.

Using the WFPC2 imager onboard HST, Larsen & Brodie (2000) published the photo-

4http://www.astromatic.net/software/


Figure 2.1 A combined colour image of NGC 720 from the Subaru/Suprime-Cam g andi filter images. NGC 720 is located at a distance of 23.4 Mpc implying 1 arcsec = 0.113kpc.


Figure 2.2 A mosaic image showing the central 27 x 27 square arcmin area around NGC1023. This is a combination of g and i filter images obtained from the CFHT/MegaCaminstrument. NGC 1023 is at a distance of 11.1 Mpc implying 1 arcsec = 0.054 kpc. Thecentral region of NGC 1023 in i- band filter is shown in the inset.


metric magnitudes for 221 GCs of NGC 1023. They obtained two deep pointings in F555W

(V) and F814W (I) filters around the central nucleus. We made use of their photometric

catalogue to explore the GC distributions at the galaxy centre.

2.4.3 NGC 2768

The imaging data for NGC 2768 were taken using the Suprime-Cam imager mounted on

the 8-meter Subaru telescope. Table 2.4 records the details of observations. The basic

reduction techniques, presented in Section 2.4.1, are employed here to reduce the images.

A colour image of NGC 2768 extracted from the combination of multi-colour g, r, i filter

images is displayed in Figure 2.3.

We obtained a second photometric dataset for NGC 2768 from the HLA. The data

(HST ID: 9353) consist of one pointing taken in F435W(B), F555W(V) and F814W(I)

filters using the ACS instrument installed on the HST. The Wide Field Channel mounted

on ACS consists of two 2048 x 4096 CCDs with 0.049 arcsec pixel scale and 3.37 x 3.37

square arcmin field of view. Jordi et al. (2006) give the transformation equations to convert

the B, V, I magnitudes to the SDSS photometric system. The B, V, I magnitudes for all

of the NGC 2768 objects are converted to g, r, i magnitudes.

2.4.4 NGC 3607 & NGC 3608

Imaging

The wide-field photometric data for the Leo II group were obtained using the Subaru/Supri-

me-Cam instrument. The sky conditions were good with an average seeing of ∼ 0.81, 0.80

and 0.80 for the g, r, i filters, respectively. To fill the gaps between individual CCDs,

multiple exposures in a dithered pattern were taken. Table 2.1 presents the details of

observations taken from Subaru/Suprime-Cam.

The individual exposures were reduced and combined using the SDFRED2 for each of

the three filters. The pre-processing of images included flat fielding, distortion corrections

and atmospheric dispersion corrections. The pipeline also features custom-made modifi-

cations to improve the sky subtraction and alignment between multiple exposures. We

employed SExtractor and Montage5 for the alignment process. All point sources three

sigma above the background level are identified on each CCD image using SExtractor.

The positions of these point sources are matched with a reference catalogue (here we use

the Sloan Digital Sky Survey) to create an astrometric solution. The astrometric solution

5http://montage.ipac.caltech.edu/index.html


Figure 2.3 The Subaru/Suprime-Cam image showing NGC 2768 is a combination of g, rand i filter images. NGC 2768 is at a distance of 21.8 Mpc implying 1 arcsec = 0.106 kpc.


is used by the Montage program to align and combine the individual images, generating

mosaic images in the three filters. A combination of g, r and i filter mosaic images is

shown in Figure 2.4.

We also obtained a single pointing covering the central region of NGC 3607 from the

HLA. This was taken in the F814W (I) filter using the ACS instrument. The Wide-Field

Channel on the ACS consists of two 2048 x 4096 CCDs with a 0.049 arcsec pixel scale, and

3.37 x 3.37 square arcmin field of view. A custom-made pipeline (for detailed explanation

see Spitler et al. 2006) is employed to reduce the ACS data. The pipeline provides source

positions and half light radii for all the detected sources, which are utilised for a preliminary

selection of GCs in the Subaru/Suprime-Cam imaging (see Section 4.2).

Spectroscopy

Complementary spectroscopic data were obtained using the DEIMOS on the Keck II

telescope. The field of NGC 3607 was targeted on five nights during 2013 January 10 – 12

and 2014 January 26 and 27 as part of the SLUGGS survey. We used five slit-masks for

good azimuthal coverage and the seeing per night was 0.87 ≤ FWHM ≤ 1.15 arcsec with

a total exposure time of ∼10 hours. DEIMOS was used with 1200 l/mm grating centered

on 7800 A, with slit widths of 1 arcsec. In this way, we have a wavelength coverage from

6500 – 8700 A and spectral resolution of ∼ 1.5 A. We reduced the raw spectra using

the IDL SPEC2D reduction pipeline together with dome flats and arc lamp spectra. The

pipeline produces sky-subtracted GC spectra that covers the CaT absorption lines in the

near-infrared (8498, 8542, 8662 A) and Hα line at 6563 A(where possible).

We obtain the radial velocities from our science spectra using the FXCOR task in IRAF

by measuring the doppler shift of the CaT lines, cross-correlating each Fourier transformed

science spectrum with the Fourier transformed spectra of 13 Galactic template stars. In

practice, we require that the strongest CaT lines (8542, 8662 A) be present and where

possible the Hα line as well. Where the lines are not properly defined, but the velocity

is consistent with either galaxy, the GC is classified as marginal. Objects with velocities

less than 350 km/s are classified as Galactic stars and those with velocities greater than

1800 km/s as background galaxies. Our final catalogue has 75 GCs and 7 ambiguous

objects (see Table A.1 in Appendix A). Here, ’ambiguous’ denotes that either the velocity

or position has a mismatch with the target galaxies, but it has confirmed characteristics

of a GC.


Figure 2.4 A mosaic image showing the central 28 x 23 square arcmin area of the Leo IIgalaxy group. This Subaru/Suprime-Cam image is a combination of g, r and i filters. Thetarget galaxies are labelled. The central galaxy, NGC 3607, is at a distance of 22.2 Mpcimplying 1 arcsec = 0.107 kpc.


2.5 Summary

In this thesis, we investigate the GC systems of five ETGs using optical wide-field images.

The ETGs included in this study are NGC 720, NGC 1023, NGC 2768, NGC 3607 and

NGC 3608, that are part of the ongoing SLUGGS survey. The SLUGGS survey is carrying

out a combined photometric, spectroscopic and chemodynamical study of 28 galaxies (25

targets plus 3 bonus galaxies) within a distance of 30 Mpc.

We obtained the photometric data mainly from the Suprime-Cam instrument mounted

on Subaru telescope. Also, we use the archival data from the MegaCam instrument on

the CFHT, the WFPC2 and the ACS installed on the HST. Complementary spectroscopic

data for NGC 3607 and NGC 3608 were obtained from the DEIMOS instrument mounted

on the Keck II telescope. The details about different observations and reduction techniques

were briefly described in this Chapter.

3Globular cluster systems in three early-type

galaxies

3.1 Introduction

Galaxies residing in clusters and groups might have experienced multiple interactions

with neighbour galaxies. These interactions might have helped them to grow in size

and mass over the period of their lifetime (van Dokkum et al., 2010). On the other

hand, galaxies situated in isolated environments are less likely to experience multiple

mergers/interactions. Nevertheless, Tal et al. (2012) found that most of the isolated

elliptical galaxies are the products of late mergers. The footprints of these mergers can still

be detected as ripples, shells or halo substructures in images if the interaction happened

in last couple of Gyrs (Nulsen, 1989).

From Chapter 1, we showed that GCs have been direct probes to investigate the

outskirts of the galaxy haloes where integrated light can not provide much information.

Only a handful of isolated/field galaxies are explored for their GC systems (Kissler-Patig

et al., 1996; Spitler et al., 2008; Lane et al., 2013; Richtler et al., 2015; Salinas et al., 2015).

In almost all massive galaxies, GC systems are found to be bimodal in colour (Larsen

et al., 2001; Peng et al., 2006; Kim et al., 2013; Hargis & Rhode, 2014). Transforming

colours to metallicity connects this bimodality with two stages of GC formation. The

colour/metallicity distribution peaks are represented by blue/metal-poor and red/metal-

rich GC subpopulations (Brodie et al., 2012). In a recent work, Forbes et al. (2015)

determined the mean ages of blue and red GC subpopulations as 12.2 − 12.8 and 11.5 Gyr

respectively, suggesting that both subpopulations are very old. However, the two peaks

differ in colour (e.g. 0.8 and 1.1 in (g−i)) and metallicity (i.e. ([Z/H] peaks at −1.5 and

−0.4 dex) values.

29

30 Chapter 3. Globular cluster systems in three early-type galaxies

Other properties of the two subpopulations differ such as azimuthal distribution, spatial

distribution, radial colour distribution (Strader et al., 2011; Park & Lee, 2013) and also

kinematics (Pota et al., 2013). Three ‘classic’ scenarios have been suggested to explain

the formation of these two distinct GC subpopulations: major-merger (Ashman & Zepf,

1992), multi-phase collapse (Forbes et al., 1997) and accretion (Cote et al., 1998, 2000). See

Brodie & Strader (2006) and Harris (2010b) for reviews. Many cosmological simulations

of hierarchical galaxy formation have been used to investigate the characteristics of GC

systems (physical, dynamical, chemical etc.) in ETGs (Beasley et al., 2002; Bekki et al.,

2005, 2008; Muratov & Gnedin, 2010; Griffen et al., 2010; Tonini, 2013; Katz & Ricotti,

2013; Gnedin et al., 2014; Trenti et al., 2015).

In order to associate the formation of different GC subpopulations with galaxy for-

mation events, we explore the different GC distributions of the total system and their

subpopulations and then, compare these GC properties with the properties of the host

galaxy. In this Chapter, we investigate the GC systems of three intermediate mass galaxies

that are located in field (NGC 720) or small group (NGC 1023, NGC 2768) environments

and are within 25 Mpc distance (Refer Section 2.3 for galaxy characteristics). The three

galaxies reported here are among the most flattened in the SLUGGS survey and hence

useful to search for trends between the flattening (ellipticity) of the GC system and the

host galaxy.

The layout of this Chapter is as follows. Section 3.2 presents the techniques used

to select the GC systems of galaxies and the method employed to transform the HST

catalogue (from Johnson photometric system to SDSS system) of NGC 1023 (Larsen &

Brodie, 2000). In Section 3.3, we describe the GC system analysis - radial density, radial

colour and azimuthal distributions of individual GC systems and their GC subpopulations,

specific frequency estimations - for the three galaxies. The results from this study and their

implications regarding galaxy evolution are presented in Section 3.4. Finally, conclusions

are given in Section 3.5.

3.2 Photometry and selection of GC systems

The data acquisition and basic reduction techniques carried out for obtaining multi-filter

wide-field images are described in Chapter 2. Firstly in this Section, we report the trans-

formation of GC system catalogue of NGC 1023 (Larsen & Brodie, 2000) from V, I filters

to g, i filters. Then, we explore the techniques adapted for modelling the galaxy stellar

light, photometry and GC system selection in individual galaxies.

3.2. Photometry and selection of GC systems 31

Figure 3.1 Transformation of NGC 1023 GC magnitudes from HST to CFHT photometricsystem. The top panels show the linear fits between HST magnitudes and CFHT magni-tudes for the common GCs in g (left panel) and i (right panel) filters. The bottom panelsshow the difference between measured (from CFHT) and converted magnitudes versus themeasured magnitudes in the g (left panel) and i (right panel) filters.

3.2.1 HST/WFPC2 GC catalogue for NGC 1023

Larsen & Brodie (2000) have published a list of 221 GCs in NGC 1023 observed with

HST in the V and I filters. Their selection was primarily based on sizes, colour (i.e.

0.75 < (V−I) < 1.40) and magnitudes (i.e. 20 < V < 25). For uniformity between

the catalogues, we converted the V and I magnitudes into CFHT g and i magnitudes.

Jordi, Grebel, & Ammon (2006) transformation equations require three band magnitudes

whereas the HST/WFPC2 data contain only V and I magnitudes. In order to convert the

magnitudes, we selected a set of bright objects (in the colour range 0.85 < (V−I) < 1.35)

in common between the two data sets and the magnitudes are fitted with a linear bisector

relation of the form :

gconv = [(0.996 ± 0.021) × VHST ] + (0.473 ± 0.175) (3.1)

iconv = [(1.009 ± 0.031) × IHST ] + (0.304 ± 0.113) (3.2)


where gconv and iconv are CFHT filter equivalent magnitudes for the HST V and I magni-

tudes. Note here that errors generated in this magnitude transformation are not added to

the V and I magnitude errors. The top panels in Figure 3.1 show the magnitude conversion

between the HST and the CFHT photometric systems. The bottom panels in Figure 3.1

display the deviation between the measured (gCFHT and iCFHT ) and converted (gconv and

iconv) magnitudes. The root mean square deviation of converted magnitudes (using equa-

tions 3.1 and 3.2) from the corresponding measured CFHT magnitudes are 0.07 and 0.12

magnitudes with no obvious systematic trend. This conversion is used to transform the

HST photometric system to the CFHT system for the GCs of Larsen & Brodie (2000). We

also checked the colour transformation between the two photometric systems and found

no systematic trend.

3.2.2 Photometry

We modelled the galaxy light for the three galaxies and subtracted it from the corre-

sponding mosaic image with the IRAF task ELLIPSE keeping the centre, PA and ellipticity

as free parameters. Here we remind the reader that the galaxy light subtracted images

are only used to improve source detection and not for any photometric analysis. The

ELLIPSE parameters (PA and ellipticity) derived from the task match well with the values

mentioned in Hyperleda that are given in Table 2.1. Sources on images were identified

and aperture photometry was carried out using the source finding software, SExtractor.

SExtractor identifies a probable source only if it has a minimum of 5 adjacent pixels with

a threshold level of three sigma above the local background. SExtractor estimates the

total instrumental magnitude for the detected sources using the Kron radius (Kron, 1980)

in automatic aperture magnitude mode. For this, magnitudes within aperture sizes of 1

to 7 pixels, equivalent to 0.2 to 1.4 arcsec, are estimated for all the detected sources in

the respective mosaic images. Depending on the seeing values for the respective filters,

the extraction radius is determined and hence we obtain instrumental magnitudes. These

instrumental magnitudes are corrected for the light outside the extraction radius using

MAG AUTO task and finally SExtractor provides a list of point sources with positions and

aperture corrected magnitudes. We selected ∼ 20 bright stars within the colour range of

0.7 < (g−i) < 1.3 in the individual galaxy images and obtained their magnitudes from

the Sloan Digital Sky Survey catalogues, in order to estimate the zeropoints in each fil-

ter. These zeropoints were applied to calibrate the magnitudes for all the point sources

detected. Our final object lists have g and i magnitudes for all three galaxies, with ad-

ditional r magnitudes for NGC 2768. The object magnitudes are corrected for Galactic

3.2. Photometry and selection of GC systems 33

extinction using Schlegel et al. (1998) (see Table 2.1). All magnitudes discussed hereafter

are extinction corrected.

3.2.3 Globular cluster selection

NGC 720: The GC selection for NGC 720 is carried out on object size, magnitude

and colour of individual objects. Initially however, the source position matching between

the Subaru g and i band images removes spurious detections (e.g. cosmic rays) on the

individual images. To determine the object size, we measure the flux in two apertures.

Objects with surplus amount of light beyond the extraction aperture radius are removed

from the GC list. As GCs appear as point sources at the distance of NGC 720, the

probable GCs have a minimum magnitude difference between the extraction aperture and

the adjacent aperture. A further selection of objects is carried out in the i band, i.e. 20.6

≤i ≤ 24 (at the distance of 23.4 Mpc, objects brighter than i = 20.6 (i.e. Mi = -11.0 mag)

include ultra compact dwarfs (Brodie et al., 2011), while objects fainter than i = 24 have

magnitude errors greater than 0.15). Final selection of NGC 720 GCs (∼ 1200 objects) is

based on the (g−i) colour of individual objects, i.e. 0.6 ≤ (g−i) ≤ 1.3. In the SLUGGS

survey, we have a list of spectroscopically (velocity) confirmed GCs for each of the survey

galaxies. Hence we are able to check the reliability of GC selection for all the three sample

galaxies.

NGC 1023: The data for NGC 1023 include CFHT g and i band photometry and

a catalogue of 221 GCs from HST (Larsen & Brodie, 2000). The GC system of NGC

1023 is identified based on the same selection criteria followed for NGC 720 Suprime-Cam

data. Matching of object positions between the observed g and i band images cleared false

detections from the list. The i band magnitude selection for NGC 1023 GCs is 18.9 ≤ i

≤ 23.0 based both on the distance to NGC 1023 and on the error in the measured i band

magnitude. A final selection is made in colour by selecting sources in the same colour

range as used by Larsen & Brodie (2000), i.e. 0.65 ≤ (g−i) ≤ 1.3. There is ∼ 460 objects

in the NGC 1023 GC candidate list.

NGC 2768: The data for NGC 2768 include g, r and i band Subaru imaging. False

detections are primarily eliminated from the object list by matching the source position

with 0.1 arcsec accuracy between the three bands. Point source objects are chosen based

on the magnitude difference between the extraction and the adjacent aperture. As the data

set for NGC 2768 consists of three band data, an additional selection based on two colour

space is introduced (i.e. (g−i) versus (r−i)). We adopted a similar GC selection process

in the colour-colour diagram as used by Spitler et al. (2008) and Blom et al. (2012). It is


evident from earlier studies, viz., figure 6 in Blom et al. (2012) and figure 3 in Pota et al.

(2013), that the GCs populate a particular region in the colour-colour diagram. These

GCs along with neighbouring objects showing a 2-sigma deviation from the selected region

are chosen as final GC candidates. The i band magnitude cut for NGC 2768 is 20.4 ≤ i

≤ 24.0. The list of GC candidates include ∼ 600 objects. A second set of data for NGC

2768 comes from HST/ACS covering the central 2.1 arcmin region. The GCs from the

HST/ACS imaging are selected in the same colour-colour diagram mentioned above for

the Subaru imaging.

3.3 Analysis of GC systems

3.3.1 Surface density profiles

The one dimensional radial distribution of a GC system is revealed by its surface density

profile. The surface density for each radial bin is estimated by fixing a similar number

of globular clusters per circular bin and dividing by the effective covered area. The area

coverage in each annuli is corrected for two factors: the presence of saturated stars and the

annular area outside the image. The errors associated with the surface density distribution

are given by Poisson statistics.

A combination of a Sersic profile (Sersic, 1968) and a background parameter is fitted

to the GC surface density distribution. The fitted profile can be written as :

N(R) = Ne exp

[−bn

(R

Re

) 1n

− 1

]+ bg (3.3)

where Ne is the density of the GCs at the effective radius Re, n is Sersic index or the shape

parameter for the profile, bn is given by the term 1.9992n - 0.3271 (Capaccioli & Caon 1989,

valid for 0.5 < n < 10.0) and bg represents the background parameter. The background

values obtained for the three GC systems are then subtracted from the respective radial

density distribution which is shown in all density distribution plots.

NGC 720

Figure 3.2 displays the surface density profile for NGC 720 using the Suprime-Cam and

GMOS data, fitted with a Sersic profile. The radial coverage of GMOS data reaches out to

5.6 arcmin and overlaps with the Suprime-Cam data which is detected out to a radius of

∼ 18 arcmin. Due to long exposure time, the detection of GCs within the saturated region

(< 1 arcmin) are found uneven and hence, eliminated from further calculation. The GCs

3.3. Analysis of GC systems 35

Figure 3.2 Surface density profile for the GC system of NGC 720. The plot displaysthe Gemini (open circles) and Subaru (filled circles) data. The GCs selected within theturnover magnitude limit, i = 23.7, are employed to derive the radial surface densityvalues. The surface density reaches the background level around 9.8 ± 0.8 arcmin (∼ 15Re) with 0.98 objects per arcmin2. The solid line is the fitted Sersic profile for the GCsurface density.


Table 3.1 Fitted parameters for the surface density of NGC 720, NGC 1023 and NGC2768 GC systems. The last column in the table presents the extent of the GC system ineach galaxy.

Name Re n bg GCS ext.NGC (arcmin) (arcmin−2) (arcmin)

720 1.97±0.34 4.16±1.21 0.98±0.06 9.8±0.81023 1.00±0.35 3.15±2.85 1.27±0.12 6.2±0.52768 1.66±0.23 3.09±0.68 0.61±0.04 9.9±0.5

brighter than the turnover magnitude (i = 23.7) are selected to retrieve the radial surface

density distribution. Turnover magnitude is estimated from the luminosity function that

is the number of GCs per unit magnitude interval for a particular galaxy. Th luminosity

functions usually have a Gaussian distribution and the peak of the distribution occurs

at the turnover magnitude. A constant value of 0.98 objects per arcmin2 is reached at a

galactocentric radius of 9.8 ± 0.8 arcmin suggesting that the background is obtained. At a

distance of 23.4 Mpc, the GCs extend to at least 68 ± 6 kpc from the centre of the galaxy.

The parameter values for the fitted profile are reported in Table 3.1. As seen from Figure

3.2, the data sets from the Gemini and Subaru telescopes are generally consistent with

each other without applying any manual adjustment. Also, we matched the radial profiles

using elliptical apertures with circular ones and found to have similar results. Kissler-

Patig et al. (1996) have studied the radial density distribution of NGC 720 GCs using

the 2.2-meter telescope at the European Southern Observatory. They estimated the GC

system reaches the background at a galactocentric distance of 2.67 arcmin. This appears

to be an underestimation of the true extent by a factor of ∼ 3. This likely demonstrates

our high-quality wide-field imaging and its ability to remove contamination.

NGC 1023

We created a radial surface density plot for NGC 1023 using the GCs from the HST at the

very centre and the CFHT for the outer regions. Larsen & Brodie (2000) identified a third

set of GCs called red extended GCs or faint fuzzies. For the calculation of surface density,

the faint fuzzies are excluded (i.e. objects with V > 22.8) as the turnover magnitude limit

is i = 22.0. The area corrections are applied to account for the detector shape of HST

and for saturated stars in the CFHT image. Figure 3.3 shows a plot of surface density

for the NGC 1023 GCs using HST and CFHT data. The GC surface density for NGC

1023 is fitted with equation 3.3 and fitted parameters are given in Table 3.1. The HST

observations are limited to 2.2 arcmin radius and the CFHT observations extend to 15


Figure 3.3 Surface density profile for the GC system of NGC 1023. The plot shows HST(open circles) and CFHT (filled circles) data. The limiting magnitude for the two datasets is the turnover magnitude, i.e. i = 22.0. The surface density of the GC system reachesthe background level around 6.2 ± 0.5 arcmin (∼ 8 Re) with 1.27 objects per arcmin2. ASersic profile is fitted and is shown with a solid line.

arcmin from the centre of the galaxy. At a galactocentric radius of 6.2 ± 0.5 arcmin the

GC surface density flattens to a constant value of ∼ 1.27 objects per arcmin2. From the

centre of NGC 1023, the GCs reach an extent of 20 ± 2 kpc. The HST and CFHT data

have not been adjusted in surface density and are consistent with each other in the region

of overlap (when the two data are cut at the turnover magnitude). This overlap between

HST and ground based telescope is a representation of data quality. Young et al. (2012)

investigated the GC system of NGC 1023 using the 3.5-meter WIYN telescope. The radial

extent of GC system was estimated by them to be 6.3 ± 0.8 arcmin. Thus Young et al.

(2012) and ourselves are in agreement on the radial extent of NGC 1023 GC system.


Figure 3.4 Surface density profile for the GC system of NGC 2768. The plot shows HST(open circles) and Subaru (filled circles) data. The GCs within the turnover magnitudelimit, i = 23.3, are selected for the density distribution. NGC 2768 GCs reach the back-ground at a galactocentric distance of 9.9 ± 0.5 arcmin (∼ 10 Re) with 0.61 objects perarcmin2. The solid line represents the Sersic profile fitted on the GC density distribution.


NGC 2768

Figure 3.4 displays the radial distribution of the GC system of NGC 2768. The data

points in the inner 2.1 arcmin radius of the galaxy were obtained from the HST data and

the area beyond that was covered by the Subaru data. The data points shown in the

Figure 3.4 are generated from the GCs with i < 23.3 (i.e. the turnover magnitude). The

HST data points are corrected for the detector shape. The presence of saturated stars

in the inner annular radii and the area outside the detector were taken into account in

the area calculation for the Subaru data points. The GC system of NGC 2768 reaches

a background value of 0.61 objects per arcmin2 at a galactocentric distance of 9.9 ± 0.5

arcmin. The surface density distribution of the GCs is fitted with a Sersic profile and is

shown in Figure 3.4. The extent of the GC system of NGC 2768 is at least 63 ± 3 kpc.

Since both data sets are cut at the turnover magnitude, the good overlap between HST

and Subaru data sets confirms the magnitude completeness of the Subaru data. We are

unable to find any previous work which has studied the GC extent for this galaxy.

3.3.2 Colour magnitude diagrams

The top panels in Figure 3.5 show the colour magnitude diagrams (CMDs) of GC can-

didates for the sample galaxies, based on the selection discussed in Section 3.2.3. The

CMDs display all the detected objects brighter than Mi = −7.75 mag (0.5 mag fainter

than the turnover magnitude) for the respective galaxies. The bottom panels display the

(g−i) colour histograms of the same GC candidates along with the background contam-

ination for the respective galaxies. In this figure, we have displayed only the data from

the wide-field imaging and not from the space-based data. Also the histograms represent

only the GC candidates detected above the turnover magnitude. In order to estimate

the colour distribution of background objects within the GC extent, we have made use of

the objects detected outside the GC system extent. First the colour distribution of the

objects outside the GC extent is analysed and corrected for the relevant areal coverage.

Then this colour distribution (shown in lower panels of Figure 3.5) is subtracted from the

corresponding GC system colours to obtain the uncontaminated GC colour distribution.

The colour distribution of the background objects generally shows a broad colour range

and does not strongly affect the GC subpopulation peaks.

All CMDs have displayed objects detected above the magnitude Mi = −7.75 mag.

The top left panel shows the CMD for NGC 720 GC candidates detected within a galacto-

centric radius of 9.8 arcmin (see Section 3.3.1), observed using the Subaru/Suprime-Cam

telescope. The colour histogram of detected GC candidates above the turnover magnitude


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along with the background is displayed in the bottom left panel. The CMD for the NGC

1023 GC candidates is plotted in the top middle panel, detected from the CFHT/MegaCam

data. As the surface density of GC candidates reaches the background at 6.2 arcmin from

the centre, the CMD is plotted with the objects within that radius only. The bottom

middle panel displays the colour histogram for the GC candidates and the background.

The top right panel in Figure 3.5 displays the CMD for the NGC 2768 GC candidates.

The diagram exhibits the GCs detected using Subaru/Suprime-Cam data. Only the GC

candidates detected within a galactocentric radius of 9.9 arcmin are included in the plot

and the respective colour histogram for GC candidates along with background is shown in

the bottom right panel. The globular cluster luminosity function (GCLF) for the detected

GCs is plotted in Figure 3.6 for the three galaxies. All three GC systems are detected

with lower limit in magnitude as turnover magnitude. This implies that data are detected

for half of the GCLF and gives reliable estimations of total number and specific frequency.

3.3.3 GC bimodality

Colour histograms

Figure 3.7 illustrates the colour histograms of GCs corrected for the background contam-

ination. The background contamination for each GC system (shown in bottom panels of

Figure 3.5), after area correction, is subtracted and the final GC colour distribution is

shown. The final list of detected GCs above the turnover magnitude after background

contamination correction includes 554 (Subaru) for NGC 720, 62 (HST) and 105 (CFHT)

for NGC 1023, and 147 (HST) and 139 (Subaru) for NGC 2768.

The left panel of Figure 3.7 shows the NGC 720 GC colour histogram using Subaru/Sup-

rime-Cam data. The galaxy shows a clear distinction between the blue and red subpopu-

lations with more blue than red GCs. The blue and red GC subpopulations of NGC 720

peak in colour around (g−i) = 0.8 and 1.1 respectively. The middle panel shows the colour

histogram for NGC 1023 GCs using HST/WFPC2 and CFHT/MegaCam data. The colour

distribution shows a bimodal nature with two peaks around (g−i) = 0.8 and 1.05. The

right panel represents the colour histogram of NGC 2768 GCs detected using HST/ACS

and Subaru/Suprime-Cam data. Both data sets show a bimodal colour distribution. The

blue and red subpopulations peak in colour at (g−i) = 0.8 and 1.1 respectively.

The CMDs and colour histograms for the three sample galaxies strengthen the bimodal

distribution of GCs for the galaxies. Kissler-Patig et al. (1996) studied the GC system of

NGC 720, but did not detect bimodality. Larsen & Brodie (2000) confirm the bimodal

distribution for NGC 1023 GCs using the HST/WFPC2 data. Later, Young et al. (2012)


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reconfirmed the presence of multiple subpopulations in NGC 1023 using WIYN data. NGC

2768 was the only galaxy detected with a clear bimodal colour distribution in a survey of

29 S0 galaxies by Kundu & Whitmore (2001b).

Gaussian mixture modeling

Gaussian mixture modeling (GMM) is an algorithm to statistically quantify whether a

distribution is unimodal or multimodal (Muratov & Gnedin, 2010). The well known

Kaye’s Mixture Model (KMM, Ashman et al. 1994) algorithm is among the general class

of algorithms of GMM. Based on three statistics, the GMM signifies the presence of a

multimodal distribution over unimodal. They are: 1. confidence level from the parametric

bootstrap method (low values indicate a multi-modal distribution), 2. separation (D) of

the means relative to their widths (D > 2 implies a multi-modal distribution) and 3.

kurtosis of the input distribution (negative kurtosis for multi-modal distributions).

NGC 720: The GMM algorithm fit to the NGC 720 GC data gives a bimodal colour

distribution with two peaks at (g−i) = 0.793 ± 0.010 and 1.125 ± 0.012. The widths for

the blue and red GCs are 0.104 and 0.090 respectively. The GMM algorithm partitions

the total GC system into 64 percent blue and 36 percent red GC subpopulations. The

parametric bootstrap method rules out the unimodal distribution with a confidence level

better than 0.01 percent (implying that a multimodal distribution is supported with >

99.9 percent probability) and D = 3.42 ± 0.16 for the NGC 720 GCs.

NGC 1023: Using GMM on the HST data, the GC system of NGC 1023 has D =

3.55 ± 0.53 supporting multi-modality. The peaks of the blue and red subpopulations

are (g−i) = 0.785 ± 0.015 and 1.017 ± 0.022 respectively. The estimated widths for the

subpopulations are 0.033 and 0.086. The total GC system consists of 38 percent blue

and 62 percent red subpopulations. The heteroscedastic fit for the GCs of NGC 1023

from CFHT data gives a blue peak at (g−i) = 0.799 ± 0.020 and a red peak at 1.038 ±0.022. GMM algorithm divides the total GCs into 43 and 57 percent blue and red GCs

respectively. The blue and red peaks have a width of 0.069 and 0.091 respectively. GMM

provides similar peak values for the subpopulations from the two data sets. Larsen &

Brodie (2000) give the peak values of two subpopulations from the KMM test, i.e. (V−I)

= 1.02 and 1.25, which are in reasonable agreement with the values derived from GMM

i.e. (V−I) = 0.99 ± 0.01 and 1.26 ± 0.02.

NGC 2768: The GMM algorithm gives a multimodal colour distribution for the

NGC 2768 GC system from the HST data. The blue and red subpopulations peak in

colour around (g−i) = 0.821 ± 0.017 and 1.101 ± 0.025 respectively. GMM provides


Table 3.2 The peak values of colour for the blue and red GC subpopulations derivedfrom GMM. The colour - metallicity relation given by equation 3.4 is used to derive thecorresponding metallicity shown below. For NGC 1023 and NGC 2768, the peak colourand metalicity values from both data are recorded.

Galaxy Blue GCs Red GCsNGC (g−i) [Z/H] (g−i) [Z/H]

720 0.793±0.010 -1.26±0.07 1.125±0.012 -0.10±0.081023 0.785±0.015 -1.29±0.10 1.017±0.022 -0.48±0.15

0.799±0.020 -1.24±0.14 1.038±0.022 -0.41±0.152768 0.821±0.017 -1.16±0.12 1.101±0.025 -0.19±0.17

0.819±0.015 -1.17±0.10 1.076±0.017 -0.27±0.12

the widths of the two subpopulations as 0.085 and 0.109. The value of D statistic is

greater than 2.89, supporting two well separated subpopulations for the NGC 2768 GC

system. We then applied the GMM algorithm to the GC colours from the Subaru imaging.

The heteroscedastic split in GCs peak at (g−i) = 0.819 ± 0.015 and 1.076 ± 0.017 with

respective widths of 0.075 and 0.079 for the two subpopulations. The separation between

two subpopulations is 3.65, supports bimodal distribution. The total GC system is divided

into 65 percent blue and 35 percent red subpopulations.

Colour - metallicity transformation

Usher et al. (2012) give the colour - metallicity relation derived from an analysis of 903

GCs. The relation for GCs with (g−i) > 0.77 is of the form:

[Z/H] = [(3.49 ± 0.12) × (g − i)] + (−4.03 ± 0.11). (3.4)

We have converted the peak colours for the GC subpopulations of the three galaxies

into metallicity, and listed them in Table 3.2. The peak metallicity for the blue and red

subpopulations agrees with the GC colour/metallicity - galaxy luminosity relation (Peng

et al., 2006; Faifer et al., 2011).

3.3.4 GC subpopulations

With our high quality photometric data, we are able to separate the GC subpopulations

and investigate their properties. Figure 3.8 shows the two dimensional images of the

three galaxies after the subtraction of galaxy stellar light. The positions of the blue

and red GCs are displayed on each galaxy image. Only the GCs detected within the

turnover magnitude are used in the study of GC subpopulations. First the surface density


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Figure 3.9 GC subpopulations of NGC 720. Surface densities for the blue (diamonds) andred (triangles) GCs of NGC 720 are shown. The open and the filled symbols representthe Gemini and the Subaru data respectively. A Sersic profile is fitted to the three GCdistributions and is displayed in respective colour solid lines along with the total systemin a black solid line.

distribution of GC subpopulations with galactocentric radius is analysed. For this, the GC

system of NGC 720 is classified into blue and red subpopulations dividing at the colour

(g−i) = 0.98 (the colour at which the Gaussian distributions for the two subpopulations

cross in the GMM fit). The subpopulations are separately binned in galactocentric radius

and the surface density values are calculated. Figure 3.9 displays the estimated values

of background subtracted surface density for the blue and red GCs along with the total

system. The Gemini and Subaru data are merged together to obtain the distribution from

a galactocentric radius of 0.18 to 18 arcmin. The surface densities are fitted with a Sersic

profile (see Equation 3.3). The fitted parameters for the blue and red GCs are recorded in

Table 3.3. The blue subpopulation has a density enhancement over the red subpopulation

over the whole range of radius except in the central 0.9 arcmin. The effective radius for

the blue subpopulation is larger than for the red subpopulation.


Figure 3.10 GC subpopulations of NGC 2768. The data sets include HST (open symbols)in the inner 2.1 arcmin radius and Subaru (filled symbols) to 20 arcmin. The radial densitydistribution for the blue (diamonds) and red (triangles) GCs are shown. The solid linesare the Sersic profiles for the two subpopulations and the total system in black solid line.

Due to the small number of detected GCs within the turnover magnitude, we are

unable to fit the distribution of GC subpopulations of NGC 1023.

For NGC 2768, the GCs are classified into blue and red subpopulations at (g−i) =

0.96 (from the GMM fit). The background subtracted surface density values for the blue

and red subpopulations are plotted in Figure 3.10. Both the HST and Subaru data are

incorporated in the figure. The radial density distributions for blue and red subpopulations

are fitted with a Sersic profile. Table 3.3 tabulates the fitted parameters for the blue and

red GC density distributions. The blue and red GCs have similar density profiles, with

the more extended blue subpopulation.

3.3.5 Radial colour distribution

The blue and red subpopulations of NGC 720 are separated at a colour of (g−i) = 0.98.

The average colour in each radial bin is estimated separately for blue and red subpopula-


Table 3.3 Fitted parameters for the surface density of blue and red GC subpopulations ofNGC 720 and NGC 2768. We are not able to fit the GC subpopulations of NGC 1023.

NGC GCs Re n bg(arcmin) (arcmin−2)

720 Blue 3.93±2.30 4.78±2.30 0.63±0.06Red 1.33±0.31 5.55±2.53 0.39±0.04

2768 Blue 1.83±0.27 2.78±0.64 0.33±0.03Red 1.50±0.23 2.53±0.79 0.25±0.05

tions. Neither the red nor the blue subpopulations from the Subaru data reveal a colour

gradient. The average colour values for the two subpopulations with galactocentric radius

are displayed in Figure 3.11.

The separation between the two subpopulations for NGC 1023 GCs is (g−i) = 0.88

(from the GMM fit) for the HST and the CFHT data. The averaged colour values in each

radial bin for the HST and the CFHT data sets are plotted in Figure 3.12. The individual

GCs from the HST and CFHT are also plotted in the figure. A positive colour gradient is

visible for the HST red subpopulation (slope = 0.028 ± 0.009 mag per arcmin).

Figure 3.13 shows the radial colour distribution for the blue and red GCs of NGC

2768 to a galactocentric distance of 12 arcmin from the centre. The GCs are categorised

into blue and red subpopulations at (g−i) = 0.96. Figure 3.13 displays the individual

GCs from the HST and the Subaru data. The radial colour distribution from the Subaru

data does not show any statistically significant radial trend, which might be caused by the

contamination from the ground based data. But the inner blue GCs from the HST data

show a slight negative slope (0.007 ± 0.002 mag per arcmin).

The radial colour distribution is an important tool to study different GC formation

scenarios. In the cases of NGC 1407 and M87, both GC subpopulations show a negative

colour gradient, supporting an in-situ dissipative formation scenario for the GCs. Beyond

a transition radius, the GCs do not show a colour gradient. The GCs exterior to the

transition region may be formed by ongoing accretion/mergers. The data used for the

NGC 1407 study (Forbes et al., 2011) came from three band imaging with subarcsecond

seeing using the Subaru telescope. The colour gradient observed for the M87 GCs (Harris,

2009b) was taken with multi-band filters using the CFHT and the seeing for the observation

was 0.8 arcsec.


Figure 3.11 Colour distribution of NGC 720 GC system with galactocentric radius. Theindividual GCs from the Subaru data are represented by yellow squares. The mean coloursover particular bins in radius are shown as filled circles for Subaru data. The separationfor blue and red GCs is shown with a dashed line at (g−i) = 0.98.


Figure 3.12 Colour distribution of NGC 1023 GC system with galactocentric radius. Theplot shows the average colour for the blue and red subpopulations using HST (open circles)and CFHT (filled circles) data. The individual GCs are represented by plus signs (HST)and squares (CFHT). The separation between the blue and the red GCs is shown with adashed line at (g−i) = 0.88. The blue GCs show a constant colour with galactocentricradius, while the red GCs show a positive slope (0.028 ± 0.009 mag per arcmin) in theinner region and a constant colour for larger radii.


Figure 3.13 Colour distribution of NGC 2768 GC system with galactocentric radius. TheHST (open circles) and the Subaru (filled circles) data are incorporated in this figure. Theaverage colour values in radial bins for the blue and the red subpopulations are representedby blue and red circles respectively. The individual GCs from the HST (plus signs) andthe Subaru (squares) are also displayed in the figure. The separation for blue and red GCsis shown with a dashed line at (g−i) = 0.96. The blue GCs selected from the HST datashow a slight negative gradient with a slope of 0.007 ± 0.002 mag per arcmin


3.3.6 Azimuthal distribution

We study the azimuthal distribution of the GC systems and their blue and red subpopu-

lations. The position angles of individual GCs (θ) are estimated from the Right Ascension

and Declination from the centre of the galaxy keeping 0 degree for North and measuring

counter-clockwise. We measure the position angle from North and move counter clockwise

to reach North again. This data include position angles from zero – 360 degrees. Then,

we fold this data into zero – 180 degrees to increase the sample size. We bin the GCs in

wedges of 18 degrees and fit a profile (McLaughlin et al., 1994) of the form:

σ(R, θ) = kR−α[cos2(θ − PA)+

(1 − ε2)−2sin2(θ − PA)]−α/2

+ bg (3.5)

where σ(R, θ) is the azimuthal distribution of GCs at radius, R and angle θ, α is the power

law index fitted to the surface density of GCs, bg is the background estimated from the

Sersic fits (see Section 3.1) and k is the normalization constant. The profile is iterated

with the position angle of the GC system (PA) and the ellipticity (ε) as free parameters.

NGC 720

For NGC 720, the position angle of the galaxy light is 142 degrees (given in Table 2.1) and

the number of GCs in the azimuthal distribution peaks around 138 degrees for the total

GC population (see Figure 3.14). The ellipticity value determined for the total GC system

is 0.28 ± 0.06, while the galaxy light has an ellipticity of 0.47 ± 0.05. The GC system

of NGC 720 matches with the galaxy light in position angle but not in ellipticity. The

azimuthal distribution is also determined for the blue and red subpopulations and recorded

in Table 3.4. Both the blue and red subpopulations are aligned along the position angle of

the galaxy light. Also the ellipticity of the red subpopulation is in good agreement with

the galaxy stellar light. Kissler-Patig et al. (1996) studied the shape of the GC system

and the host galaxy. They estimated the position angle and ellipticity for the GC system

as 147 ± 10 degrees and 0.5 ± 0.1, whereas the starlight had 142 ± 3 degrees and 0.45 ±0.05 respectively. We conclude that our findings about the position angle and ellipticity

of the GC system of NGC 720 match well with Kissler-Patig et al. (1996). They have

also found that the position angle (115 ± 15 degrees) and ellipticity (0.2 – 0.3, Buote

& Canizares 1994) of the X-ray gas in NGC 720 differ from those shown by both the

host galaxy stars and the total GC system. We note that the ellipticity of the X-ray gas

and the blue subpopulation are in reasonable agreement. Although the ellipticities are


Figure 3.14 Azimuthal distribution of NGC 720 GCs. The histograms in black, blueand red represent the azimuthal distribution of total, blue and red GCs of NGC 720respectively. The distribution is fitted with the profile given by equation 3.5 which isalso plotted in the figure as solid (total system), dotted (blue subpopulation) and dashed(red subpopulation) lines. The host galaxy starlight (dashed vertical line) is aligned at aposition angle of 142 ± 5 degrees which matches with the total system, the blue and redsubpopulations of GCs.

consistent, we note that the PAs are not. This consistency in ellipticities implies that

both the X-ray gas and blue subpopulation might have a common dynamical behaviour

and hence strengthens the connection between the blue subpopulation and galaxy haloes

(Forbes et al., 2012a).

NGC 1023

The azimuthal distribution for the NGC 1023 GCs is shown in Figure 3.15. The profiles

obtained from equation 3.5 are fitted to the different GC subpopulations and displayed in

Figure 3.15. The photometric position angle for the galaxy NGC 1023 is 87 degrees and

the best fitted profile for the total and red GCs peaks at a similar values within errors.

The red GCs of NGC 1023 are aligned along the position angle of the galaxy light with


Figure 3.15 Azimuthal distribution of NGC 1023 GCs. The density of total system of GCsand blue and red GC subpopulations are shown in black, blue and red histograms. Thefitted lines (same patterns and colours as given in Figure 3.14) represent the profile givenby equation 3.5 for NGC 1023 GCs. The dashed vertical line represents the position angleof the galaxy light (PA = 87 degrees). The total system and red subpopulation of NGC1023 GCs are arranged in elliptical rings along the position angle of the galaxy light. Incontrast the blue subpopulation shows a nearly flat azimuthal distribution (indicating amore circular distribution).

ellipticity, ε = 0.57 ± 0.08. The best fitted profile generated by equation 3.5 for the blue

GCs shows a flat distribution. The profile peaks at 110 ± 32 degrees and represents a

nearly circular distribution for the blue subpopulation of NGC 1023.

NGC 2768

Figure 3.16 displays the azimuthal distribution of the total system, blue and red subpop-

ulations of NGC 2768 GCs. The distributions are fitted with sinusoidal profiles given by

the equation 3.5 and are shown in the figure. Table 3.4 displays the position angle and

ellipticity values estimated from the fitted profiles. Both the blue and red GC subpopu-

lations are distributed with ε ∼ 0.58 along the position angle of galaxy light (PA = 93


Figure 3.16 Azimuthal distribution of NGC 2768 GCs. The histograms in black, blue andred represent the azimuthal distribution of total, blue and red GCs of NGC 2768. Thefitted lines (same patterns and colours as given in Figure 3.14) represent the profile givenby equation 3.5 for NGC 2768 GCs. The position angle of the galaxy stellar light (PA= 93 degrees) is represented by the dashed vertical line. The total system, red and blueGCs of NGC 2768 have an ellipticity value of 0.58 ± 0.06. The position angles of the GCsystem and subpopulations match with the galaxy light of NGC 2768.

degrees). In addition, the estimated values for the total GC system match well with both

the subpopulations.

3.3.7 Specific frequency

Two key properties of a GC system that can be estimated accurately using wide-field

imaging data are the total number of GCs and the specific frequency. The specific fre-

quency (SN ) of a GC system is the total number of GCs in a galaxy per unit host galaxy

luminosity. In order to compare the GC systems of galaxies, the value of SN is a useful

parameter. The value of SN may be dependent on galaxy morphology, mass, luminosity

and environment. For elliptical and lenticular galaxies, the value of SN ranges from 2 to


Table 3.4 Position angle and ellipticity for the GC systems of NGC 720, NGC 1023 andNGC 2768. The values for the GCs are determined by fitting equation 3.5 to the histogramsof azimuthal distribution. The table displays the values of the parameters for the totalsystem, blue and red GCs along with the host galaxy stellar properties obtained fromHyperLeda (Paturel et al., 2003).

Name Type PA ε(degree)

NGC 720

Galaxy Stars 142±5 0.47±0.05GCs Total 138±6 0.28±0.06GCs Blue 142±8 0.26±0.06GCs Red 134±6 0.37±0.08

NGC 1023


NGC 2768


6 (Harris, 1991; Elmegreen, 1999) depending on the host galaxy mass/luminosity. The

value of SN is defined by the relation of Harris & van den Bergh (1981):

SN = NGC 100.4(MTV +15). (3.6)

The parameter NGC (the total number of GCs) is estimated from the surface density

distribution of GC systems. To determine the total number of GCs, the area under the

Sersic profile fitted to the radial density distribution of GCs (from the centre out to the

radius at which it reaches the background) is integrated and then doubled (by assuming

a symmetric GC luminosity function, only GCs within the turnover magnitude have been

counted). MTV in equation 3.6 represents the total absolute magnitude in the V band.

For NGC 720, NGC 1023 and NGC 2768, the total number of GCs is estimated to

be 1489 ± 96, 548 ± 59 and 744 ± 68 respectively. The total visual magnitude for the

respective galaxies is MTV = −21.68 ± 0.05, −21.07 ± 0.06 and −21.91 ± 0.1 mag with

respective to the distances given in Table 2.1. Hence the specific frequency of GCs in NGC

720, NGC 1023 and NGC 2768 is calculated to be 3.2 ± 0.2, 1.8 ± 0.2 and 1.3 ± 0.1.

Kissler-Patig et al. (1996) estimated the total number of GCs for NGC 720 to be 660

± 190. They derived a specific frequency of 2.2 ± 0.9. The GC extent used to derive these

properties is 2.67 arcmin, but the extent from our study is 9.8 ± 0.8 arcmin. The difference


in the estimation of GC extent is responsible for the difference in NGC and hence SN . For

NGC 1023, Young et al. (2012) estimated NGC = 490 ± 30 and SN = 1.7 ± 0.3 for the

GC system of NGC 1023. With the estimation of a similar extent for GC system of NGC

1023, we have derived NGC = 548 ± 59 and SN = 1.8 ± 0.2. Both the estimations are

in good agreement with each other for NGC 1023. Kundu & Whitmore (2001b) studied

the GC system of NGC 2768 using HST/WFPC2 data and calculated the total number

of GCs in their field of view as 343 with a local SN of 1.2 ± 0.4 using MFOVV = −21.2.

The estimated NGC using our wider field of view is double the number determined from

the smaller field of view of WFPC2. We note that NGC 2768 is found to have a lower SN

value compared with S0 galaxies of similar luminosity (Brodie & Strader, 2006).

3.4 Results and discussion

We carried out a detailed study of GC systems in three early-type galaxies: NGC 720,

NGC 1023 and NGC 2768. The key results from this study are discussed below.

NGC 720: The imaging data from Subaru/Suprime-Cam and Gemini/GMOS were

incorporated to investigate the GC system of NGC 720. Our study has determined the

extent of GC system as 9.8 ± 0.8 arcmin (68 ± 6 kpc), where the literature study shows an

extent of 2.67 arcmin (Kissler-Patig et al., 1996). With our wide-field images, we detect

the extent of GC system as three times the literature value. The alignment of the total GC

system (PA = 138 ± 6 degree) matches the galaxy position angle (PA = 142 ± 5 degree),

while an ellipticity of 0.28 ± 0.06 is estimated for the GC system in comparison with the

galaxy ellipticity of 0.47 ± 0.05. However, Kissler-Patig et al. (1996) found the ellipticity

of the globular cluster system (0.5 ± 0.1) to match the host galaxy (0.45 ± 0.05). The

majority of the GCs in the central 2.8 arcmin radius might be red GCs, and that might

be the reason behind the ellipticity matching in Kissler-Patig et al. (1996).

Using the deep imaging from the Subaru/Suprime-Cam, we detect substructure shells

around the galaxy (see Figure 2.1). Isolated galaxies retain the shells/ripples for long du-

ration of time, as they lack interactions from neighbouring galaxies. Hence, our detection

supports the isolated environment for NGC 720. Fitting a Sersic profile to the GC system

surface density distribution gives an estimation of the total number of GCs as 1489 ± 96

and an SN = 3.2 ± 0.2. NGC 3585 is another isolated elliptical galaxy with a luminosity

(MTV = −21.8) similar to NGC 720 (MT

V = −21.68 ± 0.05), but has a lower SN value of

1.05 (Lane et al., 2013). The SN value of NGC 720 is more similar to galaxies in groups

(SN ∼ 2.6 ± 0.5; Harris 1991) rather than an isolated galaxy. Additionally, Sikkema et al.

(2007) reported the specific frequencies for four shell galaxies in isolated environments are

3.4. Results and discussion 59

< 3. The SN for NGC 720 is in between galaxies in the field and small group environments.

The GC system exhibits a bimodal colour distribution, at a greater than 99.99 percent

confidence level. The total system contains 64 and 36 percent of blue and red GCs respec-

tively. The radial distribution shows that the blue subpopulation is more extended than

the red subpopulation (Figure 3.9). Both subpopulations are aligned along the position

angle of the host galaxy (Table 3.4). The ellipticity of blue subpopulation (0.26 ± 0.06)

matches well with the X-ray gas (0.2 – 0.3) in the galaxy. Multiple X-ray studies showed

that NGC 720 is surrounded by strong X-ray halo, which strengthens the presence of dark

matter around it (Buote & Canizares, 1994, 1996, 1997; Buote et al., 2002; Arp, 2005).

The radial distribution of blue GC subpopulation is in alignment with the X-ray cloud,

implying the association between the two (Forbes et al., 2012a) and in turn connects to

the dark matter content of the galaxy. Also, the effective radius of the red GC subpopu-

lation (1.33 ± 0.31 arcmin) is in better agreement with the galaxy stellar light (Re = 0.58

arcmin) than the blue subpopulation (Re = 3.93 ± 2.30 arcmin).

NGC 1023: We obtained the wide-field imaging data from the CFHT/MegaCam and

the data for the inner 2.2 arcmin from the HST/WFPC2. The extent of the GC system is

found to be 6.2 ± 0.5 arcmin, equivalent to 20 ± 2 kpc. The total GC system is aligned

at a position angle (89 ± 7 degree), similar to the host galaxy light position angle (87 ±5 degree). The total number of GCs derived from the radial surface density distribution

is 548 ± 59 and the SN value is 1.8 ± 0.2. A recent study of the NGC 1023 globular

cluster system by Young et al. (2012) estimated a similar extent, i.e. 6.3 ± 0.8 arcmin.

The globular cluster system extent, total number and SN found by Young et al. (2012)

matches within error bars of our result.

Larsen & Brodie (2000) studied the globular cluster system using HST/WFPC2 data

and observed a bimodal colour distribution. We also identified a clear GC bimodality using

the CFHT/MegaCam data. The GC system contains 40 percent blue and 60 percent red

subpopulations. The red subpopulation is aligned along the position angle of the total

globular cluster system and the host galaxy light at 84 ± 6 degree with an ellipticity value

of 0.57 ± 0.08, while the blue subpopulation is aligned at a different angle (110 ± 32

degree) with respect to the host galaxy light and is more circular shape. The low number

of GCs prevents us from obtaining any conclusive result for the radial density distribution

of subpopulations. We do not find any statistically significant colour gradient using the

ground based data. However, the colour distribution of the red subpopulation using the

HST data shows a slight positive gradient (0.028 ± 0.009 mag per arcmin) in the inner

galaxy region (Figure 3.12), indicating a bluer galaxy centre.


NGC 2768: We made use of the HST/ACS data for a galactocentric radius of 2.1

arcmin and the Subaru/Suprime-Cam data for further out. The radius at which the

density reaches the background is 9.9 ± 0.5 arcmin (63 ± 3 kpc). The position angle at

which the galaxy star light is aligned is 93 ± 3 degree with an ellipticity of ε = 0.6 ±0.05. From the azimuthal distribution of the GC system, we find that their arrangement

matches with the host galaxy light both in position angle and ellipticity (Table 3.4). The

total number of GCs is 744 ± 68 and hence the specific frequency is 1.3 ± 0.1. With our

wide-field images, we determine the total number of GCs as double the value found by

Kundu & Whitmore (2001b).

The radial density and the azimuthal distributions of subpopulations also show that

the galaxy has a denser blue subpopulation than a red subpopulation over the total extent

of the GC system (Figure 3.10, 3.16). We did not find any literature work that studied the

globular cluster system out to 10 arcmin from the centre. The CMD shows a well-defined

bimodal colour distribution (Figure 3.5), confirming the result from Kundu & Whitmore

(2001b) and Pota et al. (2013). The GMM algorithm supports a 65 percent blue and 35

percent red GC subpopulation of the total system.

Both the blue and red subpopulations are arranged along a similar position angle to

that of the galaxy light and the total GC system (Table 3.4). However, the effective

radius of the red subpopulation (1.5 ± 0.2 arcmin) is in better agreement with the galaxy

stellar light (1.13 arcmin) than the blue subpopulation (1.8 ± 0.3 arcmin). The blue

subpopulation is observed to be more extended than the red subpopulation. A weak

positive slope is noticeable for the red subpopulation in the HST/ACS data (Figure 3.13).

The positive slope indicates an increase in mean metallicity within a galactocentric radius

of 2.1 arcmin. A detailed high-resolution spectroscopic study of the inner red globular

clusters is needed to explore the feasibility of this trend. Also, we observe a slight, but

significant, negative colour gradient for the blue GCs using the HST/ACS data.

3.5 Conclusions

We carried out a detailed study of GC systems in three early-type galaxies: NGC 720,

NGC 1023 and NGC 2768. The galaxies were observed in multi-band wide-field images

using the 8-meter Subaru Telescope, the 3.6-meter Canada France Hawaii Telescope and

the 2.4-meter Hubble Space Telescope. A detailed study of GC systems using wide-field

images is the first investigation for NGC 720 and NGC 2768. The main conclusions are

discussed below.

3.5. Conclusions 61

1. The spatial extent of the GC systems of NGC 720, NGC 1023 and NGC 2768 are

estimated as 68 ± 6, 20 ± 2 and 63 ± 3 kpc respectively. The spatial extent matches

well with the literature for NGC 1023 and we provide a first estimate of the GC

system extent for NGC 720 and NGC 2768.

2. The radial surface densities of GCs are fitted with Sersic profiles. From the Sersic

fits, we estimated the effective radii for the GC systems of NGC 720, NGC 1023 and

NGC 2768 are 13.7 ± 2.2, 3.3 ± 0.9 and 10.6 ± 1.8 kpc respectively.

3. Colour magnitude diagrams show bimodal colour distributions of GCs in all three

galaxies with greater than 99.99 percent probability in all three galaxies.

4. The total number of GCs are estimated as 1489 ± 96, 548 ± 59 and 744 ± 68 for NGC

720, NGC 1023 and NGC 2768 respectively. The SN values for the corresponding

galaxies are 3.2 ± 0.2, 1.8 ± 0.2 and 1.3 ± 0.1.

5. The peak colour of the blue and red globular cluster subpopulation agrees with the

globular cluster colour - host galaxy luminosity relation (Peng et al., 2006; Faifer

et al., 2011). This strengthens the fact that more massive galaxies have more metal

enrichment.

6. The position angle of the host galaxy matches with both the blue and red subpopu-

lation in all three galaxies. Ellipticity values of the host galaxies match better with

the red subpopulation than the blue subpopulation for all three galaxies.

7. A slight, but significant, negative colour gradient is observed for the blue subpopu-

lation in the central region of NGC 2768. The negative colour gradients support the

in-situ dissipative formation for GCs, as seen in NGC 1407 and M87 (Forbes et al.,

2011; Harris, 2009b). Also, a weak central positive gradient is detected for the red

subpopulation of NGC 1023.

8. With the deep wide-field optical images, we detect GCs for NGC 720 and NGC 2768

to three times the distance found in literature studies, validating the significance of

such images in establishing the GC system properties.

4Globular cluster systems of the Leo II group

4.1 Introduction

Due to their low velocity dispersions, galaxies in group environments are subjected to

multiple galaxy-galaxy interactions, accretions and mergers. These galaxy interactions

may also transform the morphologies of individual galaxies (e.g. Toomre & Toomre 1972).

An investigation of stellar population in galaxy groups provide vital information about

their evolutionary transformations.

Many GC system studies are carried out on galaxy pairs residing in cluster environ-

ments. Using wide-field imaging data, Bassino et al. (2006b) studied three low-luminosity

ETGs around NGC 1399 in the Fornax cluster. From the GC system properties, they

found evidences for possible interaction between the central galaxies. Also, they sug-

gested tidal stripping process as the reason behind the enhancement of blue GCs in NGC

1399. Another study of GC systems in cluster galaxies is carried out in Antlia cluster

(Dirsch et al., 2003; Bassino et al., 2008). They studied two giant ETGs, NGC 3258 and

NGC 3268, separated by a distance of ∼ 170 kpc. They detected radial colour gradients

in individual GC systems and carried out radial colour distributions of GC subpopula-

tions. Additionally, they searched for intracluster GCs and did not detect any conclusive

evidence for their existence.

Although multiple cluster galaxies are explored for their GC systems in connection

with their host galaxy evolution, galaxies in group environments are yet not surveyed

deeply for their subpopulations. In this Chapter, we explore the two central galaxies in

the Leo II group. There are ∼ 16 bright galaxies with apparent B magnitudes of ∼ 12.8

mag in the Leo II group. The central region of the group is covered by three ETGs: NGC

3607, the brightest central galaxy, ∼ 6 arcmin (39 kpc at a galaxy distance of 22.2 Mpc)

away from NGC 3608, an elliptical galaxy, and ∼ 2 arcmin (9 kpc) away from NGC 3605,

63

64 Chapter 4. Globular cluster systems of the Leo II group

another elliptical galaxy (see Figure 2.4). NGC 3607 and NGC 3608 are studied by Lauer

et al. (2005) using the HST imaging and detected the presence of an infalling gas into the

central disk of NGC 3607. Many other stellar population studies (Annibali et al., 2007;

Rickes et al., 2009; McDermid et al., 2015) were carried out and found various ages for

the two galaxies. Jedrzejewski & Schechter (1988) did a kinematic study of absorption

lines in these galaxies and proposed a possible interaction between the two. Thus, the

central ETGs in the Leo II group present dissimilarities in their galaxy properties and

also suspected for a galaxy-galaxy interaction.

Only one source is available for the GC system study in NGC 3607 and NGC 3608.

Kundu & Whitmore (2001a,b) studied the central regions of the two galaxies using the

HST/WFPC2 data. They suggested that the GC systems in these galaxies are unimodal.

Here, we focus on a wide-field imaging study of these galaxies and explore the evolutionary

histories using their GC systems.

The layout of this Chapter is as follows. Section 4.2 describes the photometry and GC

selection of the Leo II group. We present the various methods explored to define the GC

systems and also, the analysis of spectroscopic data in Section 4.3. A detailed analysis

of various GC system distributions (radial density, colour and azimuthal) for the selected

GC systems is presented in Section 4.4. In Section 4.5, we discuss connections between

the characteristics of galaxy stellar light and GC systems followed, in Section 4.6, by the

conclusions.

4.2 Photometry and GC selection

4.2.1 Photometry

Before carrying out any photometric analysis, the galaxy light was subtracted in each of

the three mosaic images. The two large galaxies are individually modelled using IRAF task

ELLIPSE with the center of the galaxy, the major axis position angle (PA) and the ellipticity

(ε) as free fitting parameters. During the fitting process the bright stars were masked before

modelling the galaxy light. The best fit galaxy model produces radial profiles of surface

brightness, position angle and ellipticity measurements for both galaxies. We made use of

galaxy light subtracted images to improve the source detection in the central regions of

the target galaxies.

We utilised SExtractor for source identification and photometry. We instructed SEx-

tractor to identify a probable source only if it has a minimum of 5 adjacent pixels with a

flux higher than three sigma above the local background. SExtractor estimates the total

4.2. Photometry and GC selection 65

instrumental magnitudes for the detected sources using Kron radii (Kron, 1980) in the

automatic aperture magnitude mode. It provides an output list of point sources with

position and magnitude. As standard stars were not observed for zeropoint calibration,

we exploited the bright stars (i < 22) present in the galaxy field. A match between these

bright stars and the Sloan Digital Sky Survey catalogue (data release 7 version) was used

for the flux calibration in all three mosaic images. Photometric zeropoint magnitudes in

three filters are derived from the best-fit linear relationship between the instrumental mag-

nitudes of bright stars and calibrated magnitudes from the SDSS catalogue. Estimated

zeropoints in g, r, i bands are 28.68 ± 0.08, 28.92 ± 0.12, 28.78 ± 0.15 magnitudes, respec-

tively. All magnitudes have had the zeropoint correction applied. The galaxy photometry

is corrected for Galactic extinction using the dust extinction maps from Schlegel et al.

(1998). Hereafter, all the magnitudes and colours cited are extinction corrected.

4.2.2 Globular cluster selection

The large galaxies, NGC 3607 and NGC 3608, are at an assumed distance of 22.2 ± 0.1 Mpc

(Brodie et al., 2014) and NGC 3605 taken to be 20.1 Mpc (Cappellari et al., 2011). For GC

identification, a match of object positions between the three bands is carried out at first, in

order to eliminate the false detections. Afterwards a separation between extended objects

(galaxies) and point source objects (both GCs and stars) is incorporated. This separation

is based on the surplus light detected beyond the extraction aperture. Objects showing

large difference between the extraction aperture and an outer aperture are considered as

extended sources and are removed. A further selection of objects is carried out in the i

band, i.e. 20.7 ≤i ≤ 23.5 (at the distance of 22.2 Mpc, objects brighter than i = 20.7

include ultra compact dwarfs (Brodie et al., 2011), while objects fainter than i = 23.5 have

magnitude errors greater than 0.15) (see Section 3.2.3 for details).

We employ a colour-colour selection as the next step to identify the GC candidates.

To aid this selection, we used the position and half light radius of the sources from the

HST/ACS data. An upper limit of ∼ 9 pc at the distance of NGC 3607, for GC candidature

is applied, and the selected objects are visually verified. A positional match between the

Subaru objects and the GCs selected on the HST/ACS image is carried out and then the

half light radius is attached to the Subaru list for the common objects. Hence we create

a list of probable GCs with their positions, three magnitudes from the Subaru/Suprime-

Cam data, and half light radii from the HST/ACS data. From earlier studies, e.g., figure

6 in Blom et al. (2012) and figure 3 in Pota et al. (2013), it is evident that the GCs

populate a particular region in the colour-colour diagram. With the above list we identify


the locus of GCs in (r−i) versus (g−i) colour space, implementing similar procedures as

explained in Spitler et al. (2008) and Blom et al. (2012). The GC candidates, along with

neighbouring objects showing a 2σ deviation from the selected region, are chosen as final

GC candidates. The selected GCs range over 0.6 < (g−i) < 1.4, which corresponds to a

metallicity range of −1.94 < [Z/H] < 0.86 using the empirical relation given in Usher et al.

(2012). The upper and lower cut off in i band magnitude are 20.4 and 24.4 magnitudes,

respectively. At the distance of NGC 3607 objects brighter than 20.4 magnitude include

ultra compact dwarfs (Brodie et al., 2011) while the lower limit is one magnitude fainter

than the turnover magnitude for the GC system. This final list of GC candidates includes

∼ 1000 objects from NGC 3605, NGC 3607 and NGC 3608.

4.3 Defining the GC systems of each galaxy

In the process of separating the GC systems of three galaxies, we start by grouping the

GCs of the smallest galaxy NGC 3605. To find the extend of the GC system of a galaxy

with known V- band magnitude, we utilise the relation given by Kartha et al. (2014).

They found an empirical relation between the galaxy stellar mass and the extent of its

GC system. The relation is as follows:

GCS extent (kpc) = [(70.9 ± 11.2) × log(M?/M�)] − (762 ± 127). (4.1)

We derive the stellar mass of NGC 3605 as log(M?) = 10.76 M� from the galaxy V-band

magnitude (12.15 mag and is given in Table 2.1) and the mass to light ratio (10; Zepf &

Ashman 1993). A GC system extent of ∼ 40 arcsec is derived from the calculation and

we assume a maximum of 1 arcmin extent for NGC 3605. We detect 10 objects in the 1

arcmin region around NGC 3605 and eliminate them from the following calculations. The

surface density distribution of GCs around NGC 3605 has been investigated and we find

a constant GC density, implying no contamination from NGC 3605 to the NGC 3607 or

NGC 3608 GC systems.

The remaining GC candidates are a combination of objects from NGC 3607 and NGC

3608. In order to classify their individual GC systems, we invoke two methods, based on

surface brightness and position angle of the host galaxies.

4.3.1 Surface brightness method

The galaxy light for both galaxies is modelled and extracted using the IRAF task ELLIPSE.

The individual surface brightness profiles are fit with Sersic profiles (Graham & Driver,

4.3. Defining the GC systems of each galaxy 67

Figure 4.1 Surface brightness profiles for individual galaxies. The i- band profiles havebeen extracted (from −4 to 10 arcmin in galactocentric radius) using IRAF ELLIPSE taskand extrapolated towards larger radii from the centres of NGC 3607 and NGC 3608. Thenegative to positive radius represents the declination axis centered on NGC 3608.


2005). We extrapolate these profiles to larger galactocentric radius (∼ 15 arcmin) and use

these extrapolated profiles to represent the stellar light profiles of individual galaxies to

large radius. Figure 4.1 shows the surface brightness profiles of NGC 3607 and NGC 3608.

Based on the position of each GC, its membership probability is computed from the ratio

of surface brightness of NGC 3607 to NGC 3608. Hereafter we refer to this as the surface

brightness (SB) method. GCs with a probability greater than 55 percent are counted as

members of NGC 3607, while less than 50 percent are classified as members of NGC 3608.

The 6 Re ellipses overlap around 55 percent SB probability (see Figure 4.2). We classify

the GCs with probability between 55 and 50 percent as ambiguous objects.

4.3.2 Major axis method

We employed a second method called the major axis (hereafter MA) method, to separate

the GC systems of the two galaxies. In this method, we divided the GCs along the

photometric major axis (125 and 82 degrees for NGC 3607 and NGC 3608, respectively)

and selected the hemisphere pointing away from the other galaxy. Thus, the selection

of GCs for NGC 3607 includes GCs in the position angles 125 to 305 degrees and for

NGC 3608 GCs from 0 to 82 and 262 to 360 degrees. This method excludes the region

of maximum tidal interaction between the two galaxies. Coccato et al. (2009) adopted a

similar method for disentangling the planetary nebulae (PNe) of NGC 3608. To eliminate

the contaminants from NGC 3607, they excluded the PNe on the southern side of NGC

3608, which is equivalent to the major axis method used here.

4.3.3 Analysis of kinematic data

We obtained the radial velocity measurements for 82 (confirmed plus marginal) GCs in the

field of the Leo II group. The galaxy systemic velocities for NGC 3607 and NGC 3608 are

942 and 1226 km/s (Brodie et al., 2014), respectively. To assign the membership of GCs to

individual galaxies, we performed a biweight estimator distribution (following Walker et al.

2006) based on the right ascension, declination and line of sight velocity of each GC. The

GCs within 2σ (σ is the standard deviation calculated from the velocity distribution) from

the central galaxy velocity are assigned membership to the corresponding galaxy, while

keeping as marginal members those with velocities between 2σ to 3σ. Figure 4.2 displays

positions of spectroscopically confirmed GCs on a SB probability map. The background

map shows the SB probability used in the separation of GCs (see Section 4.3.1). The

positions of individual galaxy GCs (as determined using velocities) fall on the same region

derived from the SB method, confirming the robustness of the SB probability method for


classifying the GCs. The distribution gives 43 and 32 GCs, respectively, as NGC 3607 and

NGC 3608 members.

In addition, we classified the 7 ambiguous objects as 6 GCs and one extreme member.

The extreme member S41879 has a velocity of 1822 ± 22 km/s, but positionally it is

projected near the centre of NGC 3607 (see Figure 4.2) in the 2D map. Assuming it lies

at the distance of NGC 3607 (D = 22.2 Mpc), then it has Mi = −9.97 mag. From the line

of sight velocity and H0 = 70 (km/s)/Mpc, we calculate the distance as 26 Mpc and hence

the magnitude Mi = −10.31 mag. This suggests that it is a possible UCD (see Brodie

et al. 2011 and references theirein). To confirm this, we checked the HST image for an

estimation of its size. Unfortunately, this object is placed in the central gap region of the

HST pointing. We examined the Subaru image and found that the object is very circular

in shape. Another possibility is an intra-group GC, as it is blue (g−i) = 0.623, circular

in shape and lies in the projected region between NGC 3607 and NGC 3605. With the

above information, we suggest that this extreme object might be a background UCD or an

intra-group GC. Eliminating this extreme object, we have 81 spectroscopically confirmed

GCs for NGC 3607 and NGC 3608.

Figure 4.3 shows the velocity distribution of GCs with galactocentric radius measured

from the centre of NGC 3608. The distance above the galaxy NGC 3608 in Declination

axis is considered as negative. The six marginal GCs are labelled in Figures 4.2 and 4.3.

Based on both these figures, we assign a membership for the marginal GCs. Note here

that this manual membership assignment is unimportant for any broad conclusions of this

study. S51178 is positionally close towards NGC 3607 with velocity > 1300 km/s. But

according to the SB probability, this GC has > 80 percent probability to be associated

with NGC 3607. Hence, considering these facts we assign it to NGC 3607 as GC44 (name

given in Table A.1). Based on the SB probability and velocity measurement, S53407 is

assigned to NGC 3607 (GC45). The position of S64467 is close to NGC 3608 with 50

percent probability, but having a velocity of 807 km/s supports a membership with NGC

3607 (GC46). S60023 has a 70 percent probability with NGC 3608 and with a velocity of

1160 km/s. Hence, S60023 is a probable member of NGC 3608 (GC33). S55434 (GC34)

and S57144 (GC35) are GCs with velocities 1281 and 1229 km/s, respectively. Both fall

on the probability region of ∼ 60 percent for NGC 3607. However, a membership to

NGC 3608 is allocated for these GCs based on the positional closeness and velocities.

Hence, S60023, S55434, S57144 are NGC 3608 members and S51178, S64467, S53407 are

NGC 3607 members. Finally, NGC 3608 and NGC 3607 have 35 and 46 spectroscopically

confirmed GCs, respectively.


−505∆RA [arcmin]

−8

−6

−4

−2

0

2

4

6

∆D

EC

[arc

min

]

S51178

S53407

S60023

S64467

S55434

S41879

S57144

NGC 3608

NGC 3607

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

SB

pro

bab

ility

Figure 4.2 Spectroscopically confirmed GCs of NGC 3607 and NGC 3608. The galaxy cen-tres for NGC 3608 and NGC 3607 are, respectively, at co-ordinates (0,0) and (−1.1,−5.8).The magenta circles and green diamonds represent the GC members of NGC 3607 andNGC 3608, while open triangles and black square represent ambiguous GCs (with IDsdenoted) and one extreme object (ID: S41879). The colour map in the background rep-resents the membership probability from the surface brightness and the colour coding isshown to the right. GCs with the SB probability value > 0.55 are candidates of NGC3607 and < 0.5 are candidates of NGC 3608, while the objects between 0.55 and 0.5 areambiguous objects. The black ellipses represent six effective radii for the two galaxies withtheir respective ellipticity and position angle of the galaxy stellar light (refer to Table 2.1).


Figure 4.3 Velocity distribution of spectroscopically confirmed GCs as a function of radiuswith respect to NGC 3608. The NGC 3607 and NGC 3608 members are represented withmagenta circles and green diamonds, while marginal GCs and one extreme object (ID:S41879) with open triangles and a filled square. The position of NGC 3605 is representedwith a black star. The dot-dashed and the dashed horizontal lines represent the galaxysystemic velocities for NGC 3607 and NGC 3608, respectively. An average error of 14km/s is shown at the lower left.


Figure 4.4 GC subpopulations for the spectroscopically confirmed GC systems of NGC3607 and NGC 3608. The centre of NGC 3605, NGC 3607 and NGC 3608 are denotedwith star (−3.1, −7.9), cross (−1.1,−5.8) and plus (0,0) symbols. The diamonds andcircles (both open and filled) represent, respectively, the GCs of NGC 3608 and NGC3607. The red and blue colours represent the blue and the red subpopulations for bothgalaxies.

4.4. Analysis of photometric data 73

The mean velocities estimated from the GC systems of NGC 3607 and NGC 3608

are 963 and 1220 km/s, respectively, in good agreement with galaxy central velocities.

Estimates of the GC system velocity dispersions for NGC 3607 and NGC 3608 are 167

and 147 km/s, respectively. Cappellari et al. (2013) found central velocity dispersions of

206.5 ± 10 and 169.0 ± 9 km/s from the galaxy stars, respectively, for NGC 3607 and

NGC 3608. As the sample size is low, we are unable to estimate the velocity dispersions

of GC subpopulations in both galaxies.

GC subpopulations

Currently, we have 46 and 35 spectroscopically confirmed GCs, respectively, for NGC

3607 and NGC 3608. We have classified the GCs into blue and red subpopulations based

on a constant colour division with galactocentric radius due to small number statistics.

The GMM algorithm (explained in Section 4.4.1) gives a (g−i) dividing colour of 0.87 for

NGC 3607 and 0.93 mag for NGC 3608 (from photometric measurements). We used these

colours to separate the blue and the red subpopulations of the two galaxies as shown in

Figure 4.4. From the photometric analysis of the GC subpopulations, we obtained 62 and

38 percent blue and red subpopulations (see Section 4.4.2), respectively.

4.4 Analysis of photometric data

Below we describe the radial density, colour and azimuthal distributions of the NGC 3607

and NCG 3608 GC systems. Note here that the GC systems are selected from the colour-

colour space discussed in Section 4.2.2.

4.4.1 GC system of NGC 3607

Radial density distribution

To derive the radial distribution of the GC system, we define radial bins up to a galacto-

centric radius of 16.9 arcmin. Then the effective area coverage is obtained for each radial

annulus. The area is corrected for the presence of saturated stars and for any regions out-

side the detection area. The GC number in each annulus is then divided by the effective

spatial area to determine the spatial density in that particular annulus. The errors are

calculated using Poisson statistics.

We obtained the GC system surface density using two methods. In the SB method

(refer Section 4.3.1), a correction is applied for the missing area due to NGC 3608 and

NGC 3605. In the MA method (refer Section 4.3.2), the number density is doubled in each


Figure 4.5 Surface density distribution for the GC system of NGC 3607. The GCs areselected via the SB and the MA methods shown by filled and open circles. The solid andthe dotted lines represent the Sersic fits for the GCs selected from each method. TheGC system reaches the background around a galactocentric radius of 9.5 ± 0.6 arcmin, inagreement with the expected value using the galaxy stellar mass in the relation of Karthaet al. (2014).

radial bin. The radial density distribution is fitted with a combination of Sersic profile

plus a background parameter to estimate the effective radius and the background value

for the GC system. The fitted surface density profile is:

N(R) = Ne exp

[−bn

(R

Re

) 1n

− 1

]+ bg (4.2)

where Ne is the surface density of the GCs at the effective radius Re, n is Sersic index

or the shape parameter for the profile, bn is given by the term 1.9992n − 0.3271 and bg

represents the background parameter. Note that the radius R is the centre of each radial

bin.

Figure 4.5 shows the density profile of the GC system for NGC 3607 only. The GCs


Table 4.1 Fitted parameters for the surface density profile of the NGC 3607 GC system.The first column represents the method used for defining the GC systems. The effectiveradius, the Sersic index and the background estimation are given in the following threecolumns. The last column presents the extent of the GC system as measured. The errorvalues given are 1-sigma uncertainties.

Method Re n bg GCS ext.(arcmin) (arcmin−2) (arcmin)

SB 2.45 ± 0.54 2.74 ± 1.76 1.70 ± 0.15 9.4 ± 0.6MA 1.99 ± 0.29 1.97 ± 1.19 1.68 ± 0.08 9.6 ± 0.5

brighter than the turnover magnitude, i = 23.5, only are considered. The plot displays the

density values derived from the two different methods, i.e. SB and MA methods. Both

are fitted with the profile given in Equation 4.2. It is evident from the figure that both

methods yield consistent results and the profile reaches the background at a galactocentric

radius of 9.5 ± 0.6 arcmin (61 ± 3 kpc).

NGC 3607, an S0 galaxy, with absolute V-band magnitude MTV = −21.87 and assumed

mass to light ratio of 7.6 (given in Zepf & Ashman 1993). Using Equation 4.1, we estimate

the host galaxy mass of NGC 3607 as log(M/M�) = 11.56. The GC system extent for

NGC 3607 determined using the above equation is 57 ± 3 kpc, in good agreement with

the direct estimation using the wide-field Subaru/Suprime-Cam image (61 ± 3 kpc).

GC bimodality

Figure 4.6 shows the colour magnitude diagram of NGC 3607 GCs. The GCs, brighter

than Mi = −7.75 mag, within the GC system extent of NGC 3607 are shown in the

diagram. The bottom panel contains the histogram of GCs which are brighter than the

turnover magnitude (Mi = −8.23 mag, Harris 2009a; Blom et al. 2012) along with the

background contamination. To estimate the background contamination, we made use of

the detected objects beyond the GC system extent of the galaxy. For NGC 3607, the

objects beyond 11 arcmin (as GC system extent is 9.5 ± 0.6 arcmin) are considered as

background contamination. We applied an areal correction, if needed. The background

corrected colour histogram is also shown in Figure 4.6.

To quantify the colour distribution of the GC system, we used the gaussian mixture

modeling (GMM, Muratov & Gnedin 2010) algorithm on the GC system (g−i) colour,

after background correction. The algorithm tests for a multimodal colour distribution

over unimodal. To be a significant multimodal GC system distribution, the following

three statistics should be, 1. low values for the confidence level from the parametric


Figure 4.6 Colour magnitude diagram for NGC 3607. The top panel represents the GCsbrighter than Mi = −7.75 mag (0.5 fainter than the turnover magnitude) within theextent of NGC 3607 GC system. The dashed line represents the turnover magnitude ini filter, Mi = −8.23 mag. The bottom panel represents the colour histogram of NGC3607 GC system. The open, shaded and dashed histograms represent the GCs which arebrighter than the turnover magnitude, the estimated background contamination and thebackground corrected colour histograms.


Table 4.2 Fitted parameters for the surface density profile of NGC 3607 and NGC 3608GC subpopulations. The first and second columns represent the target galaxy and sub-population category. The derived parameters, effective radius, the Sersic index and thebackground estimation, after the Sersic fit are given in the last three columns.

NGC GC Re n bg(arcmin) (arcmin−2)

3607Blue 1.59 ± 0.94 4.14 ± 2.32 0.36 ± 0.12Red 0.67 ± 0.52 3.38 ± 1.35 0.48 ± 0.05

3608Blue 1.42 ± 0.31 1.03 ± 0.89 0.50 ± 0.05Red 0.91 ± 0.72 1.98 ± 0.82 0.35 ± 0.05

bootstrap method, 2. the separation (D) between the means and the respective widths

greater than 2, and 3. negative kurtosis for the input distribution.

For NGC 3607, the GMM algorithm confirmed a bimodal colour distribution from the

SB and MA method selected GCs, based on the following statistics : with less than 0.001

percent confidence level, D > 2.6 ± 0.3 and negative kurtosis. The blue and red GC

subpopulations peak in (g−i) colour at 0.74 ± 0.04 and 1.03 ± 0.03, respectively. The

(g−i) colour of separation between the blue and the red subpopulations is at 0.87 ± 0.02.

The total GC system is classified into 45 ± 9 and 55 ± 8 percent, respectively, blue and

red subpopulations. Also, we fit a three component colour distribution and found that

NGC 3607 GC system satisfies the above statistics for a three peak colour distribution.

The three colour peaks are at 0.71 ± 0.03, 0.90 ± 0.04 and 1.12 ± 0.06 in (g−i) colour.

The radial density distribution for both GC subpopulations (from the MA method)

are estimated and plotted in Figure 4.7. Both subpopulation distributions are fitted

with Sersic profile given in Equation 4.2. The parameters derived from the Sersic fit

are tabulated in Table 4.2. The red subpopulation is centrally concentrated while the

blue subpopulation is more extended. The red subpopulation appears to have higher

number density for most galactocentric radii. The galaxy stellar light profile is in better

agreement with the density distribution of red subpopulation than blue subpopulation.

Also the effective radius of the galaxy stellar light (39 arcsec) matches more with the red

subpopulation (40 ± 29 arcsec) than the blue ones (95 ± 50 arcsec).

Azimuthal distribution

To quantify the azimuthal distribution of GCs, they are initially folded along the North

to South direction, then binned in equal angular intervals. The azimuthal distribution,


Figure 4.7 Radial density distributions of GC subpopulations for NGC 3607. The densitydistributions for the blue and the red subpopulations (from the MA method) are repre-sented with blue diamonds and red triangles, respectively. The best fit Sersic profiles tothe density distributions are shown as solid lines. The black solid line represents the bestfit Sersic profile for the total GC system. The dashed line represents the galaxy brightnessprofile in the i filter. The blue subpopulation is found to be more extended than the redsubpopulation. However, the galaxy stellar light profile better matches with the densitydistribution of the red subpopulation than the blue subpopulation.


σ(R, θ), is then fitted with a profile (McLaughlin et al., 1994) of the form:

σ(R, θ) = kR−α[cos2(θ − PA)+

(1 − ε2)−2sin2(θ − PA)]−α/2

+ bg (4.3)

where α is the power law index fitted to the surface density of GCs, bg is the background

estimated from the Sersic fits (see Section 4.4.1) and k is the normalization constant. The

profile is iterated with the position angle of the GC system (PA) and the ellipticity (ε) as

free parameters. For the analysis, only the GCs within the extent of GC system (i.e., 9.5

arcmin) are included. The number of GCs in each angular bin is corrected for the missing

area due to NGC 3608 in the SB method, and is doubled in the MA method.

Figure 4.8(a) shows the azimuthal distribution of GCs selected based on the SB

method. The GCs are aligned to a position angle of 110 ± 7 degrees, which is in rea-

sonable agreement with the stellar light (125 degrees) of the galaxy. The alignment of GC

system is more elliptical (0.39 ± 0.08) than the stars (0.13). The GCs also show an en-

hancement along the minor axis (35 degrees), which is either a genuine feature or possibly

a contamination from the GCs of NGC 3608 and NGC 3605 (both positioned around the

minor axis of NGC 3607). We already found a constant surface density around NGC 3605

and hence, we assume that NGC 3605 is not contributing to the overabundance.

The only other possible contributor for this minor axis overabundance is NGC 3608,

situated in the NE direction. We have eliminated the maximum contamination from NGC

3608 in the MA method, as it counts only the hemisphere away from the other galaxy.

Hence, if the enhancement of GCs is not genuine, then we should not observe the same

in the MA method. Figure 4.8(b) displays the azimuthal distribution of GCs selected in

the MA method, including only the GCs from 125 to 305 degrees counted from North

in counter-clockwise direction. It is evident from this plot that the enhancement along

the minor axis is a genuine feature, with decreased strength which is consistent within

error bars. The position angle of GCs from the MA method also aligns with the galaxy

stellar light. Similarly, from the SB method, the GCs are found to be more elongated

than the arrangement of stellar light. Table 4.3 summarises the best fit sinusoidal profile

parameters.

Figure 4.8 also shows the azimuthal distribution of blue and red GC subpopulations

from the two methods. The subpopulations are separated at a (g−i) colour of 0.87, ob-

tained from the GMM algorithm. Both subpopulations have similar position angles for

the total GC system and are more elliptical than the galaxy stars.


Fig

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4.8

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Table 4.3 Position angle and ellipticity for the GC systems of NGC 3607 and NGC 3608.The values are derived by fitting Equation 4.3 to the azimuthal distribution. The tablegives the derived values for the total GC system, the blue and the red subpopulations.For comparison, the position angle and the ellipticity of the galaxy stellar light for NGC3607 are 125 degrees and 0.13, respectively and for NGC 3608 are 82 degrees and 0.20,respectively.

Galaxy Method GC PA εName (o)

NGC 3607

SBTotal 110 ± 7 0.39 ± 0.09Blue 112 ± 14 0.37 ± 0.11Red 108 ± 11 0.47 ± 0.09

MATotal 109 ± 8 0.42 ± 0.07Blue 108 ± 10 0.45 ± 0.11Red 109 ± 8 0.48 ± 0.11

NGC 3608

SBTotal 104 ± 15 0.20 ± 0.09Blue 106 ± 11 0.31 ± 0.10Red 97 ± 18 0.14 ± 0.16

MATotal 66 ± 7 0.39 ± 0.10Blue 67 ± 8 0.45 ± 0.09Red 64 ± 10 0.44 ± 0.13

Summarising, the total GC system and both subpopulations follow the galaxy stellar

light in position angle. But the distribution of GCs is not as circular as the galaxy stellar

component. The red GC subpopulation shows a more flattened distribution than the blue

subpopulation for NGC 3607.

Radial colour distribution

Figure 4.9 shows the radial distribution of GC colours from the centre of NGC 3607. The

GCs brighter than the turnover magnitude in the MA method only are included. The GC

subpopulations are divided with a moving colour with radius technique. In each radial bin,

the average colour for both subpopulations are determined (keeping a constant number of

GCs per radial bin).

As seen from the plot, for the total extent of the GC system, the average colour for

the blue subpopulation decreases with radius from the centre, while a flat colour gradient

is seen for the red subpopulation. The colour distribution for the blue subpopulation is

fitted with a logarithmic relation (following Forbes et al. 2011) as:

(g − i) = a+ b× log(R/Re) (4.4)


Figure 4.9 Radial colour distribution for the GC system of NGC 3607. The GCs areselected using the MA method, and are shown as small grey squares. The separation be-tween the two subpopulations is obtained using a moving mean colour, and shown in blackopen circles. The average colours with errors for the blue and the red GC subpopulationsare shown as blue and red filled circles, respectively. The solid lines represent the bestfit lines for the blue and the red subpopulations in the central 6.5 arcmin, the projectedseparation between the two galaxies. For the blue and the red GC subpopulations, signif-icant colour gradients (−0.070 ± 0.013 and −0.033 ± 0.015 mag per dex for blue and redGC, respectively) are obtained in the central 6.5 arcmin radius. The data points at outergalactocentric radius appear redder and hence, we suspect contamination effects in thatregion.


where Re is the effective radius for NGC 3607 equal to 39 arcsec (Brodie et al., 2014), a

and b are, respectively, intercept and slope of the fit. We obtained a best fit line using the

bootstrap technique and derived the parameters for the blue subpopulation as a = 0.82 ±0.018 and b = −0.036 ± 0.009 mag per dex. Maraston (2005) derived a relation between

(g−i) and [Z/H] over the metallicity range [Z/H] ≤ −0.2, using single stellar population

models, of ∆(g−i)/∆[Z/H] = 0.21 ± 0.05 mag per dex. Using this we obtained for the blue

subpopulation a metallicity gradient of −0.17 ± 0.04 dex per dex to the total extent of the

GC system. But, we did not detect a significant colour gradient for the red subpopulation

and the total population in the total extent of GC system (−0.01 ± 0.01 and −0.013 ±0.011 mag per dex for red and total GCs).

We also quantified the colour/metallicity gradient in the central (∼ 6.5 arcmin) region,

only including the common galactocentric radii between the two galaxies. The colour

gradient for the blue, red and the total population are −0.070 ± 0.013, −0.033 ± 0.015 and

−0.039 ± 0.018 mag per dex. In the inner 6.5 arcmin region, the blue subpopulation has a

higher metallicity gradient (−0.33 ± 0.06 dex per dex) compared to the red subpopulation

(−0.16 ± 0.07 dex per dex). Hence, we conclude that a significant colour/metallicity

gradient is obtained for the blue and the red subpopulations of NGC 3607.

4.4.2 GC system of NGC 3608

Radial density distribution

Figure 4.10 displays the radial density of GCs selected with the SB and the MA methods

for NGC 3608 fitted with the profile given in Equation 4.2 (fitted parameters are given

in Table 4.4). In the SB method, the selection of GCs for NGC 3608 gives a maximum

galactocentric radius of ∼ 5.5 arcmin (as seen from Section 4.3.1). But the MA method

identifies objects to a distance of 12.8 arcmin from the galaxy centre (thus extends up to

the edge of the detection area). In both methods, the GCs with i < 23.5 mag (turnover

magnitude) are counted for studying this distribution. The density distribution of GCs in

radial annuli, after applying respective corrections for both methods, are shown in Figure

4.10. The GC system reaches a background level of 1.65 ± 0.1 GCs per square arcmin

to a galactocentric radius of 6.6 ± 0.8 arcmin (43 ± 5 kpc), from the MA method. But

the density value for the final data point from the SB method is 1.82 ± 0.36 GCs per

square arcmin implying that the distribution has not reached the background level. The

elimination of marginal GCs (SB probability between 50 and 55 percent) in the SB method

might be the reason for this discrepancy in the extent of GC system. Another point from

the figure is that the surface density values estimated from both methods are consistent


Figure 4.10 Surface density distribution for the GC system of NGC 3608. The radialdensity distribution of GCs based on the SB method and the MA method are representedwith filled and open circles, respectively. The SB method detects GCs to a maximumgalactocentric radius of ∼ 5.5 arcmin. The best fit Sersic profiles are represented withsolid and dotted lines for the two methods. The GC system reaches a background in theMA method at a galactocentric radius of 6.6 ± 0.8 arcmin.

within error bars, up to 5.5 arcmin.

NGC 3608 is an E2 galaxy and MTV = −20.98 mag, assuming a mass to light ratio of

10 (Zepf & Ashman, 1993) has a stellar mass of log (M/M�) = 11.32. Using Equation

4.1, the expected GC system extent is calculated to be 40 ± 2 kpc, consistent with the

GC system extent from the observational data (43 ± 5 kpc).

GC bimodality

The colour magnitude diagram for the selected GCs of NGC 3608, within the GC system

extent (43 kpc) and brighter than Mi = −7.75 mag, is shown in the top panel of Figure

4.11. As explained in Section 4.4.1, the background contamination in the GC system

selection is quantified for NGC 3608 and is shown in the bottom panel of Figure 4.11.


Figure 4.11 Colour magnitude diagram for NGC 3608. The top panel represents theGCs brighter than Mi = −7.75 mag within the extent of GC system. The dashed linerepresents the turnover magnitude in i filter, Mi = −8.23 mag. The colour histogram ofthe GC system of NGC 3608 is shown in the bottom panel, where the open, shaded anddashed histograms represent the GCs which are brighter than the turnover magnitude, theestimated background contamination and the background corrected colour histograms.


Table 4.4 Fitted parameters for the surface density of NGC 3608 GC system. The firstcolumn represents the GC selection method. The following three columns give the derivedvalues for the effective radius, the Sersic index and background using the Sersic fit. Theextent of the GC system is given in the last column, which is not estimated for the SBmethod.

Method Re n bg GCS ext.(arcmin) (arcmin−2) (arcmin)

SB 1.29 ± 0.15 0.66 ± 0.36 1.82 ± 0.36 -MA 1.50 ± 0.15 0.93 ± 0.56 1.65 ± 0.10 6.6 ± 0.8

Figure 4.12 Radial density distributions of NGC 3608 GC subpopulations. The bluediamonds and the red triangles represent the surface density distributions of blue and redsubpopulations respectively. The blue and the red solid lines demonstrate the best fitSersic profiles on the distributions, while the black solid line represents the Sersic fit forthe total GC system. The galaxy brightness profile in the i filter is shown as dashed line,in reasonable agreement with the density distribution of red subpopulation. Also, the redsubpopulation is more centrally concentrated than the blue subpopulation for NGC 3608.


The bottom panel also displays the colour histograms of GCs which are brighter than the

turnover magnitude with and without background correction.

The GMM algorithm fit to NGC 3608 GCs selected from the MA method gives a

bimodal colour distribution with peaks at (g−i) = 0.80 ± 0.02 and 1.12 ± 0.04. The total

GC system contains 65 ± 6 and 35 ± 6 percent, respectively, blue and red subpopulations.

The blue and red subpopulations are divided at (g−i) = 0.93.

The radial surface densities (GCs from the MA method) are fitted with Sersic profiles

and are displayed in Figure 4.12. The parameters estimated from the Sersic fit are tab-

ulated in Table 4.2. For NGC 3608, the blue subpopulation shows a higher density than

the red subpopulation throughout the extent of the GC system. The red subpopulation

is found to be more centrally concentrated, and their density profile is in good agreement

with the galaxy stellar light.

Azimuthal distribution

The range of galactocentric radii for the selected GCs in the SB method is from 0.5 to

5.5 arcmin. The selection of GCs in all position angles is complete up to 2.2 arcmin and

hence, an areal correction is applied for the missing area outside that radius. Figure 4.13(a)

shows the azimuthal density distribution of GCs from the SB method. The histograms

are fitted with the sinusoidal profile given in Equation 4.3. Table 4.3 gives the position

angles and ellipticities obtained from the sinusoidal fit. The galaxy stellar light has a

major axis of 82 degrees and ellipticity of 0.20. As seen from Table 4.3, the total GC

system and both subpopulations are arranged along a different position angle of ∼ 100

degrees for the SB method. When the distribution is examined over 0 to 360 degrees

rather than 0 to 180 degrees (i.e., without folding along the North to South direction),

an overabundance is evident in the position angles between 90 and 230 degrees. This is

in the direction towards NGC 3607 and also the direction in which the area correction

is largest. Hence, this overabundance is either due to contamination from NGC 3607 (or

due to overestimation of missing area). Also a scarcity of GCs is observed in both major

axis position angles (82 and 262 degrees). The ellipticity for the total GC system is 0.20

± 0.09, matching with the galaxy stellar light.

Figure 4.13(b) shows the azimuthal density distribution of GCs selected in the MA

method, for which GCs in the position angles 80 to 260 degrees are under abundant.

The GCs within the extent of GC system (6.6 arcmin) are included in the azimuthal

distribution. As seen in Table 4.3, the best fit sinusoidal profile gives a position angle of

66 ± 7 degrees for the total GC system and an ellipticity of 0.39 ± 0.10. The GCs selected


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in the MA method includes GCs of NGC 3608 placed at a position angle pointing away

from NGC 3607, implying minimum contamination. For a better analysis of azimuthal

distribution, objects detected in complete position angles are necessary. Hence, we suggest

that the estimated parameters from the SB method are more reliable in comparison to

the MA method. The arrangement of GCs in the MA method is along the position angle

matching the galaxy stars, but the distribution is more elliptical. Since we observed an

overabundance in GCs for both galaxies, in the region towards each other, an interaction

may be occurring between the two.

The total GC system is separated into subpopulations at (g−i) = 0.93 (obtained from

the GMM algorithm). Regarding the azimuthal distribution of GC subpopulations, both

subpopulations are aligned along the position angle of the total GC system in the two

methods. Also the ellipticity of both subpopulations matches with the total GC system.

In the MA method, the total and both subpopulations are more elliptically aligned than

the galaxy stellar light.

Radial colour distribution

Figure 4.14 shows the radial (g−i) colour distribution of GC system of NGC 3608 selected

on the MA method. To study this distribution, GCs (from the MA method) brighter than

the turnover magnitude are selected. The total GC system and the red subpopulation

show a null gradient, while the blue subpopulation shows a strong gradient along the total

radial extent of the GC system. The colour distribution of the blue subpopulation is fitted

with the logarithmic relation given in Equation 4.4, where Re = 30 arcsec (Brodie et al.,

2014). The parameters, a = 0.823 ± 0.019 mag and b = −0.052 ± 0.011 mag per dex,

are derived from the best fit profile using the bootstrap technique (shown in Figure 4.14).

The colour gradient, when converted to a metallicity gradient, gives ∆[Z/H] = −0.25 ±0.05 dex per dex.

4.5 Results and discussion

In this study of two group galaxies (NGC 3607 and NGC 3608 situated within a projected

distance of 39 kpc), we introduce two methods, the Surface Brightness and the Major Axis

methods, to separate the individual GC systems. For NGC 3607, the radial GC system ex-

tent determined from both methods are consistent with each other and in good agreement

with the empirical relation for GC system extent (Equation 4.1), initially presented in

Kartha et al. (2014). From the radial surface density distribution, the red subpopulation


Figure 4.14 Radial colour distribution for the GC system of NGC 3608 (from the MAmethod). The individual GCs are represented as small grey squares. The average colourswith error for the blue and red GC subpopulations are denoted as blue and red filledcircles, respectively. The separation colours for the subpopulations in each radial bin iscalculated using a moving mean colour method and is denoted with black open circles.The blue subpopulation shows a colour gradient of −0.052 ± 0.011 mag per dex (∆[Z/H]= −0.25 ± 0.05 dex per dex) for the total extent of the GC system, but we did not detectany colour gradient for the red subpopulation.


is more centrally concentrated than the blue subpopulation. The galaxy surface brightness

distribution is in agreement with the density distribution profile of the red subpopulation

than the blue subpopulation (Figure 4.7). Also, the effective radius of the galaxy stars (39

arcsec) is consistent with that of the red GC subpopulation (40 ± 29 arcsec), while for the

blue GC subpopulation it is 95 ± 50 arcsec. Both the spatial distribution and the effective

radius measurements support the idea that the red GC subpopulation has evolutionary

similarities with the galaxy stellar component (Forbes & Forte, 2001; Larsen et al., 2001;

Brodie & Strader, 2006; Spitler, 2010; Forbes et al., 2012a).

For NGC 3608, the blue GC subpopulation is more extended than the red GC sub-

population. It is evident from Figure 4.12 that the density distribution of the red GC

subpopulation follows the galaxy stellar light distribution. However, the effective radius

of galaxy light (30 arcsec) is half of the red subpopulation (59 ± 40 arcsec) and one third

of the blue subpopulation (85 ± 18 arcsec). The effective radius of the red GC subpopula-

tion is therefore not consistent with the stellar light component. Even so the resemblance

of the density distribution profile with the galaxy stellar light might imply a significant

association.

In the Leo II group, NGC 3607 is the massive central galaxy and has a red GC sub-

population fraction higher than the blue, while the neighbouring galaxy NGC 3608 is less

massive and has a higher fraction of blue GCs. An overabundance of red GCs is observed

along the minor axis of NGC 3607 (even after removing the GCs in the direction towards

NGC 3608). From the azimuthal distribution of GCs of NGC 3608, it is found that both

GC subpopulations are aligned in position angle and that angle is different from the po-

sition angle of the galaxy stellar light. These results (overabundance and misalignment)

suggest a possible interaction between the galaxies in the group.

Using HST data, Lauer et al. (2005) carried out an imaging study of 77 early-type

galaxies, including NGC 3607. They detected an additional gas disk settling in NGC 3607

perpendicular to the existing dusty disk. They commented that the dusty disk is in a

transition phase merging with the gas disk. They explained this process as gas infalling

directly onto the centre of NGC 3607 without disturbing the dusty disk and without any

obvious features of interaction.

Later, Annibali et al. (2007) studied the stellar population properties of 66 early-

type galaxies. They estimated the age, metallicity and alpha enhancement using the Lick

indices with updated simple stellar population models (including the non-solar element

abundance patterns). They estimated a very young age, 3.1 ± 0.5 Gyr, for NGC 3607

and suggested it had experienced a recent episode of star formation. Rickes et al. (2009)


carried out long slit spectroscopy, out to galactocentric radii of 30.5 arcsec, and claimed

that NGC 3607 has undergone a minimum of three star formation episodes with ages

ranging from 1 to 13 Gyr. The young age for the stellar population of NGC 3607 and

the detection of a central gas disk indicate that NGC 3607 has experienced a recent star

formation episode and the overabundance of red GCs may be due to GCs formed in that

episode.

From the ATLAS3D survey, McDermid et al. (2015) estimated the mass-weighted ages

for NGC 3605, NGC 3607 and NGC 3608 as 8.1 ± 0.8, 13.5 ± 0.7 and 13.0 ± 0.7 Gyr

respectively. They utilised the spectra within 1Re to fit the single stellar population models

and hence derive the mass-weighted ages, metallicity and star formation histories of 260

ETGs. Using a second method of utilizing the Lick indices, they estimated the age for

NGC 3607 as 7.3 ± 1.3 Gyr that contradicts the young age determined by Annibali et al.

(2007).

Forbes et al. (2006b) carried out a multi-wavelength (X-ray, optical and Hi imaging)

study of ∼ 60 galaxy groups, including the Leo II group. They investigated the evo-

lutionary connections between different groups and the influence of group environment.

In their study, they detected extended X-ray emission associated with the Leo II group

but did not resolve individual galaxies. Recently, using Chandra X-ray data, Jang et al.

(2014) observed X-ray emission from the central AGN in NGC 3607 and diffuse emission

around NGC 3608. The detection of extended X-ray emissions confirms the presence of

hot intergalactic gas.

The misalignment in the position angles of the GCs relative to the galaxy in NGC 3608

might be another sign of interaction with NGC 3607. Additionally, each galaxy shows an

overabundance of GCs in the direct of the other, again suggesting a possible interaction

between them. Jedrzejewski & Schechter (1988) proposed a close encounter between these

two galaxies. They studied the absorption line kinematics for the stellar component of

NGC 3608 and found a change in direction of the rotation curve between the core and

outside region. They proposed that the reversal might be due to an interaction with the

nearby NGC 3607.

We conclude that our results also support a possible interaction between the two

galaxies. To confirm this proposition, deep surface photometric and detailed kinematic

studies are needed.

4.6. Conclusions 93

4.6 Conclusions

We present wide-field imaging data from the Subaru telescope with which we carry out

an investigation of the GC systems in the Leo II group to large galactocentric radii (∼120 kpc). Using the multi-band wide-field images in g, r and i filters, we analysed the

radial density, radial colour and azimuthal distributions of GC systems in the two bright-

est galaxies of the group, NGC 3607 and NGC 3608. Our study is complemented with

spectroscopic data obtained from DEIMOS on the Keck II telescope. We present the main

conclusions here.

1. The GC systems of NGC 3607 and NGC 3808 are found to have radial extents of 9.5

± 0.6 arcmin (equivalent to 61 ± 5 kpc or ∼ 4.4 Re) and 6.6 ± 0.8 arcmin (equivalent

to 43 ± 5 kpc or ∼ 4.7 Re), respectively. The derived values are in agreement with

estimates obtained from the empirical relation between the effective radius of the

GC system and galaxy stellar light given in Kartha et al. (2014).

2. The GC system colours of both galaxies are fitted with the GMM algorithm and

we detect a bimodal distribution with confidence level greater than 99.99 percent.

NGC 3607 is observed to have 45 ± 9 and 55 ± 8 percent of blue and red GC

subpopulations, while for NGC 3608 the blue and red GC subpopulations contribute

65 ± 6 and 35 ± 6 percent to the total GC system.

3. From the radial velocity measurements, we detect 81 GCs in the field of the Leo

II group. We assign 46 and 35 GCs, respectively, to NGC 3607 and NGC 3608.

We estimate a mean velocity of 963 and 1220 km/s for NGC 3607 and NGC 3608,

respectively. Also, the mean GC velocity dispersions for the respective galaxies are

167 and 147 km/s.

4. From the radial density distributions of the GC subpopulations of NGC 3607, the

red subpopulation is more centrally located while the blue subpopulation is more

extended. Also, the effective radius of the red GC subpopulation (40 ± 29 arcsec)

and the galaxy stellar light (39 arcsec) are in good agreement, compared to the blue

subpopulation (95 ± 50 arcsec).

5. For NGC 3608, the blue subpopulation is more extended in radius than the centrally

concentrated red subpopulation. The red subpopulation distribution shows similar-

ities with the galaxy surface brightness distribution. However, the effective radius

of the red subpopulation (59 ± 40 arcsec) is larger than the galaxy stellar light (30

arcsec).


6. The azimuthal distribution of the NGC 3607 GC system reveals that both subpop-

ulations are aligned along a position angle (∼ 110 degrees), which is in reasonable

agreement with the galaxy stellar light (125 degrees). However, the distribution

of the GC system is more elliptical in comparison with the circular distribution of

galaxy stellar light. The red subpopulation shows a more elliptical distribution when

compared with the blue subpopulation.

7. For NGC 3608, the GCs are arranged along position angles that are different from the

galaxy stellar population. Using two different methods of GC selection, the position

angles for the total GC system are found to be along 104 ± 15 and 67 ± 7 degrees,

while the galaxy major axis is at 82 degrees. One method of GC selection suggests

that the GCs have an ellipticity = 0.20 ± 0.09, while the other shows an ellipticity

of 0.39 ± 0.10. By comparison, the stellar light ellipticity is 0.20. In NGC 3608, the

blue subpopulation has a more elliptical arrangement than the red subpopulation.

8. The total GC system, and both subpopulations of NGC 3607, become bluer in colour

with increasing galactocentric radius; a significant metallicity gradient is observed

for both subpopulations. We find that the blue subpopulation has a steeper gradient

than the red subpopulation. We also detect a strong colour gradient only for the

blue subpopulation of NGC 3608. The colour gradient for the blue subpopulation in

NGC 3608 is steeper than that in NGC 3607.

5Global properties of GC systems

5.1 Introduction

Accurate imaging studies of ETGs can determine their GC system properties only in a

statistical sense. Over these years, large numbers of studies aimed at establishing complete

GC system studies in galaxies, but only limited studies explored the GC system to reach

the outer galaxy halos. Only if GC system properties are extracted reliably, we can better

understand their parent galaxies and their evolutionary connections between them. For

example, although many studies of GC system density distributions have been carried

out, only a handful of them explored the GC subpopulation distributions. As part of our

research - exploring the GC systems in five ETGs, we investigated the global properties of

the total systems and their subpopulations (Chapter 3 & 4). In this chapter, we explore

different correlations of global properties of GC systems (including GC systems of other

well studied ETGs) with host galaxy mass, galaxy effective radius and local environment

density.

With the global properties of a sample of GC systems, we are also equipped to

study their global relations with the host galaxies. A relevant question to study is the

(in)dependence of GC formation efficiency with different environments. Recently, Tonini

(2013) constructed a theoretical model to investigate GC bimodality. She predicted that

the GC bimodality is a direct outcome of hierarchical galaxy assembly. Also she predicted

that a larger fraction of blue GCs can be found in early-type galaxies residing in higher den-

sity environments. However, using ACSVCS data Cho et al. (2012) studied the variation

in the fraction of red GCs in field and cluster environments. They found that the fraction

of red GCs was enhanced from field to high density environment. Spitler et al. (2008)

also studied the dependence of mass normalized blue GC number with environment for a

sample of early-type galaxies. They concluded that the GC formation efficiency depends

95

96 Chapter 5. Global properties of GC systems

primarily on galaxy mass and is nearly independent with respect to galaxy environment.

In this chapter, we try to analyse these different results regarding the dependence of GC

formation efficiency on environment.

The outline of this chapter is as follows. Section 5.2 presents seven different correlations

between GC systems and host galaxies. In Section 5.3, we discuss the feasibility of different

GC system formation models from an angle of wild-field imaging. Conclusions from this

global property study are described in Section 5.4.

5.2 Global relations of GC systems

In this section, we explore seven global scaling relations between the GC systems and

their host galaxy. Multiple scaling relations including SN are already published by Rhode

et al. (2007); Spitler et al. (2008), etc. and hence, we plan to associate other parameters

such as effective radius, ellipticity, colour gradient etc. Along with the earlier discussed

five galaxies, we include 33 literature studied galaxies plus another four (NGC 821, NGC

1407, NGC 4278 and NGC 4365) galaxies from the SLUGGS survey studies (Spitler et al.,

2008; Forbes et al., 2011; Usher et al., 2013; Blom et al., 2012). We have carried out a

selection of galaxies based on their available GC system properties and used the same

selection criteria as adopted in Spitler et al. (2008), followed from Rhode et al. (2005).

The main criteria followed for the selection of literature galaxies are: the GC system must

have been observed in two filters with an estimate of total GC number, the fraction of

blue to red GCs must have been given or can be calculated and the uncertainties in the

estimated parameters should be < 40 percent. In our sample of 42 galaxies selected for

this scaling relation study, three lack an estimate of GC system extent and the other two

lack the ratio of blue to red GCs, but all have a reliable total GC number estimate.

5.2.1 GC system extent versus galaxy stellar mass

Rhode et al. (2007) and Rhode, Windschitl, & Young (2010) have given a relation between

the radial extent of a GC system and the host galaxy stellar mass for 11 galaxies. The

extent of a GC system is defined as the radial distance at which the GC surface density

distribution reaches the background. The host galaxy mass is estimated from the absolute

visual magnitude making use of mass to light ratios given by Zepf & Ashman (1993). The

mass to light ratios applied for the different Hubble types are as follows : M/L = 10

for elliptical galaxies, 7.6 for S0 galaxies, 6.1 for Sa - Sb galaxies and 5 for Sc galaxies.

Before discussing the GC extent versus galaxy stellar mass relation, we discuss the possible

5.2. Global relations of GC systems 97

sources of error.

The galaxy stellar mass is derived from the galaxy V- band magnitude, distance and

mass to light ratio. Measurement of the total magnitude involves a typical error of 0.05 to

0.2 mag. Due to the extended accretion history, field galaxies are on average younger than

cluster galaxies (Kuntschner et al., 2002; Reda et al., 2007). This induce a factor of error

in V- band magnitude estimation. Another large error comes from the mass to light ratio

for different galaxy morphologies. For a given Hubble type, the mass to light ratio for a

sample of galaxies is not constant. For example, NGC 1316 is included as an elliptical

galaxy, and assumed to have a value of M/LV = 10 (Zepf & Ashman, 1993). However,

Shaya et al. (1996) found a lower mass to light ratio of 2.2 for the galaxy. A possible

explanation for the lower value is the presence of an intermediate age stellar population

(Shaya et al., 1996; Kuntschner, 2000). Estimation of mass to light ratios for individual

galaxies is a difficult process. Here we use the Zepf & Ashman (1993) values, but note the

potentially large source of error.

Errors in the GC system extent include the galaxy distance errors, the bin size er-

rors involved in GC surface density distribution and issues due to image quality. The

main component determining a precise GC spatial extent is the imaging quality. In order

to completely observe the extent of a GC system, wide-field imaging data from a large

aperture telescope must be used. Imaging data needs to be observed in good seeing con-

ditions which reduces the contamination in point source identification. Also GC selection

from multi-filtered imaging data reduces the contamination. For example, NGC 720 has

a GC system 3 times larger (this work) than the literature estimate (Kissler-Patig et al.,

1996), with the use of better quality and wider field data. The amount of contamination

in a three filter imaging data can be as low as ∼ 5 percent (Romanowsky et al., 2009).

Hence accurate estimations of GC system extent using wide-field imaging data is needed

to reduce errors.

We have expanded the Rhode et al. (2007, 2010) studies of GC system extent versus

host galaxy mass (for 11 galaxies) by including another 28 galaxies: five from Chapter 3

and 4, four from the earlier SLUGGS studies and nineteen from other literature studies (as

the GC system extent is not estimated for the other three galaxies). Table 5.1 tabulates

the distance, total visual magnitude, estimated galaxy mass and the GC extent for the

sample of 39 galaxies (as three galaxies lack the estimation of GC system extent). The

extent of GC systems against the host galaxy mass is plotted and displayed in Figure

5.1. As the galaxy mass increases, it is evident from the figure that the extent of GC

systems grows. Or in other words, more massive galaxies accommodate more extended


Figure 5.1 Radial extent of GC system versus log galaxy mass. The galaxies studiedby the SLUGGS survey are represented with double star and double hexagon symbols,while others represent galaxies studied using wide-field photometry from the literature.Elliptical, lenticular and spiral galaxies are drawn with star, hexagon and spiral symbolsrespectively. The linear fits given by equations 5.1 and 5.4 are shown by a straight lineand a dot-dash line respectively. The dash-dot-dot-dot line represents the second order fitgiven by equation 5.2. The dashed line depicts the linear relation given by equation 5.3from Rhode et al. (2007).


GC systems.

The best fitted linear and second order polynomial (not shown in the Figure 5.1) are:

GCS extent = [(70.9 ± 11.2) × log(M�)] − (762 ± 127) (5.1)

GCS extent = [(41.5 ± 4.3) × (log(M�))2] − [(891 ± 97) × log(M�)] (5.2)

+(4791 ± 548)

respectively, where the spatial extent of GC system is in kpc. Figure 5.1 also shows the

linear fit from Rhode et al. (2007):

GCS extent = [(57.7 ± 3.7) × log(M�)] − (619 ± 41). (5.3)

The slope of the linear fit has changed with the addition of more galaxies and is steeper

than in Rhode et al. (2007). The second order polynomial fit given by Equation 5.2 also

provides a reasonable match to the data (shown in Figure 5.1).

In order to better understand the relation between the GC system extent and host

galaxy mass, we analysed the host galaxy’s morphology. The total sample is divided into

different Hubble types and shown with different symbols in the figure (see the caption of

Figure 5.1). Spiral galaxies are positioned at the bottom left side of the figure. Since

the extent of a GC system for spiral galaxies in the sample is found to be independent of

the host galaxy mass, we did a separate analysis excluding them. In the total sample of

galaxies, we have nineteen elliptical galaxies and ten lenticular galaxies. Although most of

the early-type galaxies agree well with the fitted linear relation (within error bars), some

are displaced from the fit (i.e. NGC 4365, NGC 1407, NGC 4374). Another linear fit is

carried out only for the 29 ETGs and is shown in Figure 5.1, which is given by:

GCS extent = [(80.5 ± 15.7) × log(M�)] − (872 ± 179). (5.4)

It is evident from Figure 5.1 that the spatial extent of GC systems is larger for more

luminous early-type galaxies.


Tab

le5.

1.P

rop

erti

esof

our

gala

xy

sam

ple

for

GC

syst

emgl

obal

pro

per

tyst

ud

y

NG

CT

yp

eD

V0 T

MT V

log(

M?)

GC

Ext

NGC

NBGC

/NRGC

Re

ρ(M

pc)

(mag

)(m

ag)

(M�

)(k

pc)

(kp

c)(M

pc−

3)

720

E5

23.4

410

.17

−21

.68

11.6

0468

±6

1489

±96

a1.

784.

60x

0.25

821

E6

23.4

010

.79

−21

.06

11.3

5426

±3

320±

45b

2.33

4.51

z0.

95102

3S

011

.10

9.15

−21

.07

11.2

4320

±2

548±

59a

0.75

2.57

z0.

57140

7E

023

.11

9.7

4−

22.0

811

.764

140±

764

00±

700c

1.50

8.06

x0.

42276

8S

021

.80

9.78

−21

.91

11.5

7863

±3

744±

68a

1.86

6.66

z0.

3136

07S

022

.20

9.89

−21

.86

11.5

5861

±5

1600

±20

0a0.

824.

19w

0.34

3608

E2

22.3

010.

76−

20.9

811

.325

43±

590

0±

150a

1.86

3.24

w0.

5642

78E

115

.60

10.

07−

20.9

011

.290

64±

713

78±

113d

2.03

2.39

z1.

2543

65E

323

.30

9.54

−22

.30

11.8

5113

4±

764

50±

110e

1.63

5.92

z2.

9389

1S

b8.

368.8

2−

20.7

911

.034

9±

370

±20

f1.

704.

14z

0.55

105

2S

b19

.60

10.4

4−

21.0

211

.341

19±

340

0±

120g

1.00

3.50

x1.

80105

5S

b16

.30

10.0

9−

20.9

711

.106

26±

721

0±

40h

4.00

5.34

z0.

25131

6E

20.1

48.5

3−

22.9

911

.526

62±

563

6±

35i

1.50

6.75

z1.

15137

9E

017

.71

10.9

9−

20.2

511

.032

19±

222

5±

23j

0.82

3.64

x5.

79138

7S

017

.24

10.7

2−

20.4

610

.998

14±

239

0±

27j

0.32

1.75

t5.

80142

7E

319

.35

10.9

1−

20.5

211

.141

11±

247

0±

80k

4.56

3.08

x4.

94268

3S

b7.7

08.

97−

20.4

610

.902

9±

312

0±

40l

2.03

2.10

z2.

48325

8E

132

.10

11.3

0−

21.2

311

.425

–60

00±

150u

3.2

4.26

x0.

72326

8E

234

.80

11.3

0−

21.4

111

.495

–47

50±

150u

1.6

6.08

x0.

69337

9E

110

.30

9.2

4−

20.8

211

.262

34±

427

0±

68m

2.33

1.99

z4.

12


Tab

le5.

1(c

ont’

d)

NG

CT

yp

eD

V0 T

MT V

log(

M?)

GC

Ext

NGC

NBGC

/NRGC

Re

ρ(M

pc)

(mag

)(m

ag)

(M�

)(k

pc)

(kp

c)(M

pc−

3)

3384

S0

11.3

09.

84−

20.4

310

.983

17±

412

0±

30n

1.50

1.77

z0.

5435

56S

b7.

109.

26−

20.0

010

.629

20±

429

0±

80l

1.70

3.00

z1.

7735

85E

618

.30

9.75

−21

.56

11.5

5736

±4

550±

55o

–3.

51x

0.12

4013

Sb

15.1

010

.52

−20

.37

10.8

6714

±5

140±

20f

3.00

3.42

z1.

3441

57S

b14

.70

10.4

4−

20.4

010

.876

21±

480

±20

l1.

782.

71z

7.55

4261

E2

30.8

010

.39

−22

.05

11.7

53–

1242

±90

v1.

505.

67z

0.84

4374

E1

18.5

09.

07−

22.2

711

.838

30±

417

75±

150p

2.33

4.70

z21

.38

4406

E3

16.7

08.

84−

22.2

711

.841

83±

629

00±

415m

1.50

7.55

z12

.25

4472

E2

17.1

08.

38−

22.7

812

.046

102±

759

00±

721q

1.50

7.91

z19

.68

4594

Sa

9.80

7.55

−22

.41

11.7

7554

±5

1900

±18

9m1.

507.

28y

0.95

4636

E0

14.3

09.

51

−21

.27

11.4

3956

±5

4200

±12

0r1.

866.

17z

9.44

4649

E2

17.3

08.

75

−22

.44

11.9

1042

±3

3600

±50

0t1.

675.

54z

3.49

4754

S0

16.1

010

.43

−20

.60

11.0

5415

±4

115±

15n

0.67

2.47

z2.

6247

62S

022

.60

10.1

6−

21.6

111

.457

27±

727

0±

30n

0.67

4.78

z2.

6558

12E

027

.95

10.8

9−

21.3

411

.469

27±

340

0±

40o

–3.

23x

0.19

5813

E1

31.3

010

.48

−22

.00

11.7

3112

0±

1429

00±

400n

2.13

8.73

z0.

8858

66S

014

.90

9.9

9−

20.8

811

.163

44±

1134

0±

80n

2.85

2.62

z0.

2473

31S

b13

.10

8.7

5−

21.8

411

.452

18±

421

0±

130l

1.04

3.91

z1.

5973

32S

023

.00

11.0

6−

20.7

511

.112

13±

417

5±

15h

4.00

1.94

z0.

1273

39S

bc

22.4

011.

42−

20.3

310

.850

10±

375

±10

h2.

332.

66z

0.11


Tab

le5.

1(c

ont’

d)

NG

CT

yp

eD

V0 T

MT V

log(

M?)

GC

Ext

NGC

NBGC

/NRGC

Re

ρ(M

pc)

(mag

)(m

ag)

(M�

)(k

pc)

(kp

c)(M

pc−

3)

745

7S

013

.20

10.9

3−

19.6

710

.682

13±

221

0±

30s

1.50

2.32

z0.

1378

14S

b17

.17

10.2

0−

20.9

711

.107

13±

419

0±

20q

0.67

3.39

z0.

91

Not

e.—

Th

eto

pp

art

of

the

tab

lein

clu

des

dat

afo

rga

laxie

sin

the

SL

UG

GS

surv

eyan

dth

eb

otto

mp

art

ofth

eta

ble

list

sot

her

lite

ratu

regal

axie

s.M

orph

olog

ical

typ

eis

take

nfr

omN

ED

.T

he

dis

tan

ces

are

obta

ined

from

Cap

pel

lari

etal

.(2

011)

ifav

aila

ble

,ot

her

wis

efr

omN

ED

.T

he

tota

lvis

ual

mag

nit

ud

efo

rth

ega

laxie

sis

take

nfr

omd

eV

auco

ule

urs

etal

.(1

991)

and

hen

cew

ed

eriv

eth

eab

solu

tem

agn

itu

de,

MT V

.T

he

dis

tan

ce,

abso

lute

mag

nit

ud

ean

dth

em

ass

toli

ght

rati

o(g

iven

by

Zep

f&

Ash

man

1993

)ar

ein

corp

orat

edto

det

erm

ine

gala

xy

stel

lar

mas

s(M

?).

GC

nu

mb

ers

(NGC

)is

take

nfr

omd

iffer

ent

refe

ren

ces

asre

cord

edin

the

foot

not

e.N

BGC

/NRGC

rep

rese

nts

the

rati

oof

blu

eto

red

GC

s.T

he

refe

ren

ceco

rres

pon

din

gto

gala

xy

effec

tive

rad

iiar

eal

som

enti

oned

inth

efo

otn

ote

.T

he

loca

ld

ensi

typ

aram

eter

ista

ken

from

Tu

lly

(198

8).

Ref

eren

ces.

—a

-C

hap

ter

3&

4;b

-S

pit

ler

etal

.(2

008)

;c

-F

orb

eset

al.

(201

1);

d-

Ush

eret

al.

(201

3);

e-

Blo

met

al.

(2012

);f

-R

hod

eet

al.

(201

0);

g-

For

bes

etal

.(2

001)

;h

-Y

oung

etal

.(2

012)

;i

-R

ichtl

eret

al.

(201

2);

j-

Bas

sin

oet

al.

(200

6b);

k-

For

teet

al.

(200

1);

l-

Rh

od

eet

al.

(200

7);

m-

Rh

od

e&

Zep

f(2

004)

;n

-H

argis

&R

hod

e(2

012)

;o

-L

ane

etal

.(2

013)

;p

-G

omez

&R

ichtl

er(2

004)

;q

-R

hod

e&

Zep

f(2

003)

;r

-D

irsc

het

al.

(200

5);

s-

Har

gis

etal

.(2

011)

;t

-L

eeet

al.

(200

8);

u-

Bas

sin

oet

al.

(200

8);

v-

Bon

fin

iet

al.

(201

2);

w-

Bro

die

etal

.(2

014)

;x

-F

ab

eret

al.

(198

9);

y-

Ben

der

etal

.(1

992)

;z

-C

app

ella

riet

al.

(201

1).


With this limited sample of galaxies, we conclude that the spatial extent of GC systems

is proportional to the host galaxy stellar mass. This result is in agreement with Rhode

et al. (2007), but our linear fit is steeper than Rhode et al. (2007) (since the majority

of their sample was spiral galaxies), when more galaxies are included. The main errors

affecting the relation are the image quality and the assumed constant mass to light ratios

for galaxies of individual Hubble type. With our sample of galaxies, we also infer that

the extent of a GC system is only weakly dependent on galaxy stellar mass for late-type

galaxies.

5.2.2 GC extent versus galaxy effective radius

Given the errors associated with determining galaxy stellar mass, we now examine galaxy

effective radius. The effective radius (Re) is defined as the galaxy radius comprising half

of the total luminosity. We exclude the late-type galaxies from this analysis because the

effective radius for late-type galaxies includes the bulge plus extended disc components,

but only the bulge component for ETGs. This is done for the sake of uniformity.

The effective radii for ETGs are taken from Faber et al. (1989), Bender et al. (1992) and

Cappellari et al. (2011). The effective radius for NGC 1387 is taken from de Vaucouleurs

et al. (1991) and we have multiple measurements for other galaxies. Faber et al. (1989)

and Bender et al. (1992) estimated effective radii from de Vaucouleurs fits to the surface

brightness profiles. Cappellari et al. (2011) derived the effective radii combining the RC3

and 2MASS determinations, both measurements are based on growth curves. Estimation

of the effective radius includes a large error of ∼ 20 percent (Cappellari et al., 2011). This

error has a greater effect on larger sized galaxies (as shown in Figure 5.2). The priority for

effective radius values used here are Cappellari et al. (2011), then Faber et al. (1989) and

finally Bender et al. (1992). The effective radii for the sample galaxies are also recorded

in Table 5.1. Figure 5.2 shows the GC system extent versus effective radius for early-type

galaxies. As evident from the figure, the GC system extent is larger for greater effective

radii. A linear fit is carried out for the sample of 29 galaxies and is represented with a

straight line in Figure 5.2. The fitted linear relation between GC system size and galaxy

size is given by:

GCS extent = [(14.1 ± 2.1) ×Re(galaxy)] − (16.2 ± 10.1) (5.5)

For a sample of 29 ETGs the extent of a GC system is ∼ 14 times the effective radius of

the host galaxy. An advantage of this relation is that it is independent of an assumed mass


Figure 5.2 Radial extent of GC system versus galaxy effective radius for ETGs. Thesymbols shown in the figure are same as in the Figure 5.1. The linear fit given by equation5.5 is drawn with a solid line. The typical 20 percent error at Re = 2 and 7 kpc are shownat the top of the figure.


to light ratio as needed in Section 4.1. Hence, Figure 5.2 provides a better understanding

between GC system extent and their host galaxies.

5.2.3 GC system effective radius versus galaxy effective radius

Although we can confirm the correlation of GC spatial extent with galaxy mass as found

by Rhode et al. (2007), we also find evidence that the measurement of the spatial extent

is strongly dependent on the quality of the data used. Thus the Rhode et al. (2007)

correlation should be considered more as a general trend than a quantitative relation. A

better quantity to use is the effective radius of the GC system, although this has only been

measured for a handful of GC systems to date.

Here we plot GC system effective radius versus galaxy effective radius. The effective

radius of the GC system is derived from a Sersic profile fitted to the radial GC surface

density profile. Most literature studies have used a power law or de Vaucouleurs law (a

Sersic fit with n fixed to 4) to analyse the GC radial density distribution. Figure 5.3 shows

the plot for twelve galaxies available with both parameters (recorded in Table 5.2). We

have linearly fitted the data with the bootstrap technique and found:

Re(GCS) = [(6.5 ± 1.3) ×Re(galaxy)] − (13 ± 6) (5.6)

where both Res are measured in kpc. The effective radii for both GC subpopulations

are determined only for six galaxies. With the available data, we could not detect any

significant relation between the effective radius of GC subpopulations and the host galaxy

stellar light.

The GC system spatial extent (shown in Figure 5.1 & 5.2) includes errors mainly from

quality of data used. But the GC system effective radius is a more reliable parameter as

it is derived from a Sersic profile. Hence, we suggest GC system effective radius versus

galaxy effective radius as a better version of Figure 5.1. From Equation 5.6, we can infer

that the GC system effective radius is ∼ 6 times the galaxy effective radius, which confirms

that the GC system of a galaxy extends further out than the bulk of its stellar component

(Harris et al., 2000; Forbes et al., 2006a; Brodie & Strader, 2006; Alamo-Martınez et al.,

2012; Cantiello et al., 2015). A byproduct from the above relation is that we can estimate

the GC system effective radius by knowing the galaxy effective radius.


Figure 5.3 GC system effective radius versus galaxy effective radius. The plot displays asample of twelve galaxies in which eight are from the SLUGGS survey. The GC systemeffective radius is derived from the Sersic profile fitted to the radial surface density distri-bution of GCs and the galaxy effective radius is discussed in Section 5.2.2. The data inthe plot are fitted with a linear relation using the bootstrap technique shown by a blackline. The GC system effective radius is ∼ 6 times the galaxy stellar light.


Table 5.2 Effective radius of GC systems from a Sersic fit and their host galaxy. Thereference for GC system and galaxy effective radii are given in the last column respectively.

Galaxy Effective radius Ref.NGC GC system (kpc) Stellar light (kpc)

720 13.7±2.2 4.60±0.9 1, 51023 3.3±0.9 2.57±0.5 1, 51407 25.5±1.4 8.06±1.6 2, 52768 10.6±1.8 6.66±1.3 1, 53607 14.2±2 4.2±1 7, 53608 9.1±1 3.2±0.7 7, 54278 11.3±1.5 2.39±0.5 3, 54365 41.3±8.1 5.92±1.2 4, 54406 28.2±1 7.6±0.5 8, 64472 58.4±8 7.9±0.8 8, 64594 16.8±1 3.2±0.7 8, 65813 36.6±3 8.8±0.8 8, 6

References– 1 - Chapter 3; 2 - Spitler et al. (2012); 3 - Usher et al. (2013);4 - Blom et al. (2012); 5 - Brodie et al. (2014); 6 - Cappellari et al. (2011);

7 - Chapter 4; 8 - Hargis & Rhode (2014)

5.2.4 Ratio of blue to red GC number as a function of host galaxy

density

Tonini (2013) has performed a series of Monte Carlo simulations to study the assembly his-

tory of galaxies and the formation of associated GC systems. One prediction is that galax-

ies in higher density environments are expected to have a higher minor merger/accretion

frequency and hence to contain a higher number of accreted blue GCs. According to

Tonini’s prediction, the ratio of blue to red GCs should be larger for galaxies in higher

density environments.

To quantify the density of environment around a galaxy, we have employed the local

density parameter. We use the local environment density as a proxy for the merger history

in comparison with Tonini (2013). Tully (1988) has estimated the local density parameter

ρ (in Mpc−3) for 2367 galaxies in the Nearby Galaxies Catalog. He defined it as the

number of galaxies per Mpc−3 found around a galaxy within a smoothing length σ. The

density parameter is given by:

ρ =∑i

C exp [−r2i /2σ2] (5.7)

where C = 1/(2πσ2)3/2 = 0.0635/σ3 is a normalization coefficient, ri is the projected

distance towards the ith galaxy from the central galaxy and the distribution around each


galaxy is fitted with a Gaussian profile of half width σ. The density parameter ρ is the

sum over all galaxies excluding the central galaxy. The definition of ρ given above does

not take into account the incompleteness of the catalogue at large distances. Hence, the

ρ values calculated by Tully (1988) have a large uncertainty factor. The environmental

measure should ideally give an indication of the merger/interaction history for individual

galaxies. As such a measure is unavailable, we use ρ as a proxy.

Using our total sample of galaxies, we searched for confirmation of Tonini’s prediction.

The galaxies with reliable GC number ratios are selected based on the criteria mentioned

in Section 5.2 and are tabulated in Table 5.1 along with ρ. Figure 5.4 shows the ratio of

blue to red GCs versus the local density parameter ρ for a sample of 42 galaxies. Galaxies

of different morphological types are shown with different symbols in the figure. It is visible

from the figure that there is no strong correlation between the density of environment and

the blue to red GC number ratio for elliptical and spiral galaxies. However, we find an

anti-correlation for the lenticular galaxies: the ratio of blue to red GCs decreases with

increasing local density. With the bootstrapping technique, a best fit linear relation to

the data points of lenticular galaxies is:

log(NBGC/NRGC) = [(−0.59 ± 0.07) × log(ρ)] + (−0.031 ± 0.052) (5.8)

This negative slope implies that there is a higher relative number of red GCs for lenticular

galaxies in denser environments. We note that the correlation still holds if the galaxy with

the lowest blue to red ratio (NGC 1387) is removed from the sample.

Cho et al. (2012) studied ten early-type galaxies in low density environments using

HST/ACS data. They compared the properties with cluster galaxies from the ACS Virgo

Cluster Survey (ACSVCS, Cote et al. 2004). They found that the mean colour of GCs is

bluer and also the relative fraction of red GCs is lower for field galaxies than for the cluster

galaxies from the ACSVCS. From these trends, they inferred that the galaxy environment

has only a weak effect on the formation and mean metallicities of GCs, while the host

galaxy luminosity/mass plays a major role. They also suggested a possible explanation

for the environmental dependence whereby the GC formation in dense environments is

affected by neighbouring galaxies through interaction/accretion which produces a large

variation in the GC system properties for galaxies in high density environments.

Spitler et al. (2008) investigated the relationships of Tblue (the number of blue GCs

normalised to the host galaxy stellar mass) with host galaxy stellar mass (M∗) and local

density ρ. They studied a sample of 25, mostly elliptical, galaxies with only two lenticular

galaxies. Both Tblue versus M∗ and Tblue versus ρ, showed positive trends implying a


Figure 5.4 Ratio of blue to red GCs versus density of environment for a sample of 42galaxies. Spirals, lenticular galaxies and elliptical galaxies are represented by spirals,hexagons and stars respectively. The double symbol points are the galaxies from SLUGGSsurvey and others from the literature. We did not find any correlation for the spiral andelliptical galaxies. But we found that the ratio of blue to red GCs decreases with thedensity of environment for lenticular galaxies (the fitted linear relation is shown as astraight line). Note the presence of two overlapping galaxies, NGC 4754 and NGC 4762,around the coordinates (2.6, 0.7).


lower Tblue value for lower mass galaxies and lower density environments. This supports

the idea that the T parameter has a dependence on either mass and density or possibly

both. Trying to disentangle the dependance, they noticed a slight positive trend in a

residual plot of Tblue versus M∗ after removing the dependence of Tblue with ρ. They

argued that GC formation efficiency is highly dependent on host galaxy stellar mass, but

much less so on environmental density.

In our sample, the relative fraction of red GCs in lenticular galaxies increases with

the environmental density (Figure 5.4), while the same trend is not shown by elliptical or

spiral galaxies. Cho et al. (2012) detected an increase in the relative fraction of red GCs

with the environmental density. The majority of their galaxies are also lenticular galaxies,

after combining with the ACSVCS data. Hence our result matches with Cho et al. (2012).

Thus from our study, we also confirm the dependence of GC formation on the galaxy

environment, at least for lenticular galaxies, as seen in Cho et al. (2012). However, Spitler

et al. (2008) found the GC formation is dependent on host galaxy mass, and only weakly

on environmental density. Their result was based on a sample mostly of elliptical galaxies

and does not show any environmental dependence. Similarly the elliptical galaxies in our

sample do not show any dependence on environment. Spiral galaxies in our sample also

exhibit an independence of blue to red ratio from their environments. Salinas et al. (2015)

estimated the red fraction in five ETGs (three Es and two E/S0s). They found that the

red fraction in low-density elliptical galaxies are equal or lower than high-density elliptical

galaxies. This result disagrees with our result and Cho et al. (2012), where the result is

obtained from lenticular galaxies.

We find a relatively higher fraction of red GCs in lenticular galaxies residing in high

density environments. Among the various galaxy interactions which can cause variations

in GC numbers, as discussed in Forbes et al. (1997), is tidal stripping which removes the

outer halo or blue GCs. For example, NGC 1387 is an S0 galaxy in our sample with the

lowest relative fraction of blue to red GCs (NBGC/NRGC = 0.32). The lack of blue GCs

could be caused by a tidal interaction between NGC 1387 and NGC 1399. Bassino et al.

(2006a,b) observed a low number of blue GCs around NGC 1387 and an overabundance in

the direction near to NGC 1399. They proposed this as a case of tidal stripping through

which NGC 1399 has stripped away the outer halo of NGC 1387, creating a deficit of

blue GCs compared to the red GCs. Using numerical simulations, Bekki et al. (2003)

confirmed an asymmetry in the distribution of blue GCs around NGC 1399 and also

suggested the influence of a tidal interaction with the nearby galaxies. We propose that

the tidal stripping might be the cause for the observed trend by lenticular galaxies. As the


outer regions of elliptical galaxies are mostly dominated by strong dark matter content in

comparison to lenticular galaxies, the elliptical galaxies might be weakly affected by tidal

stripping.

5.2.5 Ratio of blue to red GC number as a function of host galaxy stellar

mass

In Figure 5.5, the ratio of blue to red GCs is plotted against the host galaxy stellar mass

for the above sample of 42 galaxies. There is no obvious correlation between the ratio of

blue to red GCs with the galaxy stellar mass. We divide the galaxies into three mass bins

of size 0.5 log(M�) and derive the mean value for the ratio of blue to red GCs. The mean

ratio of blue to red GCs in the low (log(M?)< 11 M�), intermediate (11 < log(M?) < 11.5

M�) and high mass (log(M?) > 11.5 M�) bins are respectively, 1.7 ± 0.8, 2.0 ± 1.2 and

1.6 ± 0.4. The mean ratio of blue to red GCs for the total sample of forty two galaxies is

∼ 1.76.

Using cosmological simulations, Bekki et al. (2008) investigated the structural, kine-

matical and chemical properties of GC systems in different Hubble type galaxies. They

estimated the ratio of blue to red GCs, in the host galaxy luminosity range − 14 < MB

< −22 to vary from ∼ 50 – 0.25, with an average of 1.5. Using the ACSVCS, Peng et al.

(2006) also investigated the ratio of blue to red GCs in a similar luminosity range and

determined that the fraction varies from 5.6 to 0.67 percent from low to high luminosity

galaxies, suggesting an average ratio of ∼ 1.5 blue to red GCs over the total luminosity

range.

There is a decreasing trend in the ratio of blue to red GCs with host galaxy luminosity,

both observationally (Peng et al., 2006) and theoretically (Bekki et al., 2008). We observe

a nearly constant ratio of blue to red GCs in our sample of 42 galaxies because our

luminosity range is much more restricted. As seen in the inset of Figure 5.5, our sample of

forty two galaxies lie in the galaxy luminosity range −18.5 < MB < −22 mag, whereas the

faint end extends to MB = −14 mag for both Peng et al. (2006) and Bekki et al. (2008).

5.2.6 GC ellipticity versus galaxy stellar light ellipticity

To further address the association of galaxy stellar light with GC subpopulations, we need

to study the two dimensional spatial distribution of these systems. Different studies of two

dimensional distributions (position angle and ellipticity) have confirmed an association of

both subpopulations with galaxy stellar light (e.g. NGC 2768 by Kartha et al. 2014,

NGC 4636 by Dirsch et al. 2005). Park & Lee (2013) analysed the two dimensional


Figure 5.5 Ratio of blue to red GCs versus galaxy stellar mass. The representation of sym-bols is same as in Figure 5.4. For all types of galaxies, there is no correlation between theratio of blue to red GCs and galaxy stellar mass. They have a mean ratio of NBGC/NRGC

∼ 1.7 for the total sample. An inset plot of ratio of blue to red GCs versus galaxy absoluteB- band magnitude is given for the same sample. The mean ratio of blue to red GCs is ∼1.7 for the galaxy range −18.5 < MB < −22 mag.


Table 5.3 Ellipticity values for GC subpopulations and their respective galaxy stellar lightfor the ten galaxies. The reference for GCs and galaxy stellar light are given in the lastcolumn.

Galaxy Ellipticity Ref.

NGC Blue GCs Red GCs Stellar light

720 0.26 ± 0.06 0.37 ± 0.08 0.47 ± 0.05 1, 51023 0.15 ± 0.15 0.57 ± 0.08 0.58 ± 0.05 1, 52768 0.57 ± 0.04 0.60 ± 0.05 0.60 ± 0.03 1, 53607 0.45 ± 0.11 0.48 ± 0.11 0.13 ± 0.03 7, 53608 0.31 ± 0.10 0.14 ± 0.16 0.20 ± 0.03 7, 54365 0.44 ± 0.08 0.30 ± 0.08 0.25 ± 0.03 2, 24406 0.39 ± 0.06 0.36 ± 0.07 0.40 ± 0.03 6, 64486 0.30 ± 0.07 0.34 ± 0.10 0.40 ± 0.05 3, 34649 0.03 ± 0.02 0.09 ± 0.04 0.22 ± 0.05 4, 45813 0.52 ± 0.15 0.36 ± 0.11 0.30 ± 0.03 6, 6

References– 1 - Chapter 3; 2 - Blom et al. (2012); 3 - Strader et al. (2011);4 - Lee et al. (2008); 5 - Brodie et al. (2014); 6 - Hargis & Rhode (2014); 7 - Chapter 4

shape parameters of 23 early-type galaxies using the HST/ACSVCS. They found that

the arrangement of both subpopulations is aligned with the photometric major axis of

galaxies. Also, the red GC subpopulations show a tight relation in ellipticity with galaxy

stellar light, while the blue GC subpopulations show a less tight relation.

Figure 5.6 demonstrates the relation between GC subpopulation ellipticity and galaxy

stellar light ellipticity for ten ETGs. The ellipticity values of galaxy stellar light are de-

rived by fitting ellipses on the radial light distribution and the GC subpopulations are

estimated from the azimuthal distribution of GCs. Most literature studies have examined

the azimuthal distribution of the total GC system and not for individual GC subpopula-

tions. Hence we have accessible values for GC subpopulation ellipticity for only a handful

of galaxies. Table 5.3 displays the ellipticity values for blue and red GCs and the galaxy

stellar light for the ten available galaxies.

We observe a positive correlation between the ellipticity for red GCs and galaxy stellar

light (Figure 5.6). But the distribution of blue GCs shows no trend. We are able to fit a

linear relation to the red GCs:

εRGC = [(1.0 ± 0.1) × εStars] + (−0.02 ± 0.06) (5.9)

The intrinsic scatter in the above relation is estimated as 0.10. This one-to-one relation

signifies that the red subpopulations are affiliated with the stellar light of the parent

galaxies (Park & Lee, 2013). This suggests that both the red GC subpopulation and the


Figure 5.6 GC ellipticity versus galaxy stellar light ellipticity. The top and the bottompanels show the relation between ellipticities of blue GCs (open circles) and red GCs (filleddiamonds) versus galaxy stellar light (recorded in Table 5.3), respectively. The blue andthe red GCs are represented in blue open circles and red filled diamonds, respectively. Alinear fit to the red GCs is drawn as a solid line and a one-to-one relation is shown as adashed line. The red GC subpopulation confirms a one-to-one relation with galaxy stellarlight, whereas only a weak relation for the blue GC subpopulation is present.


underlying stellar populations share a common evolutionary history (see also Forbes et al.

2012a). This supports the GC formation scenarios which predict the red GC subpopulation

have originated along with the majority of galaxy stars. These scenarios suggested that

the blue GC subpopulation formed before the red GCs.

In contrast to Park & Lee (2013), we notice a poor association of blue GC subpopu-

lation ellipticity with galaxy stellar light ellipticity. We explain this as a consequence of

our wide-field imaging, as the ACSVCS data used by Park & Lee (2013) does not reach

far out enough to detect the whole blue GC subpopulation for the most extended galaxies

(Peng et al., 2006).

In this small sample of ten galaxies, NGC 3607 shows the lowest ellipticity (nearly

circular at ε = 0.13) for the galaxy stellar component. For NGC 3607, the ellipticities

of both GC subpopulations show a deviation from the galaxy stellar light, although both

are arranged along the photometric major axis of the galaxy. So, NGC 3607 supports the

idea that galaxies with low ellipticities might have randomly arranged GC subpopulations

(Wang et al., 2013). The difference in spatial distribution of GC subpopulations from the

galaxy stellar component suggests that a major fraction of both GC subpopulations might

have formed separately from the galactic stars and later settled in the host galaxies. In

the case of NGC 3608, both GC subpopulations show deviations from the galaxy stellar

light in position angle. In addition, the blue GC subpopulation shows a more elongated

distribution than the red GC subpopulation.

In addition to NGC 3608, three other galaxies - NGC 4365, NGC 4406 and NGC

5813 - also have blue GC subpopulations more elongated in shape than the red GC sub-

populations. The elongated shape of the blue GC subpopulation suggests that it shows

spatial distribution similarities with the red subpopulation that mostly follows the dis-

tribution of galaxy stellar component. If the distribution of blue GCs is not spherical,

Wang et al. (2013) suggest that it may not have been built from accretions that were

equally distributed in all directions. Instead they might formed through local filamentary

structures in particular directions. This points out that directional dependent accretion

or minor mergers might have occurred in these galaxies, altering the shape of blue GC

subpopulations.

In addition, these four elliptical galaxies are all slow rotators with kinematically distinct

cores, KDCs, (Emsellem et al., 2011; Krajnovic et al., 2011). Naab et al. (2014) carried

out hydrodynamical simulations to kinematically study the centres of early-type galaxies.

They suggested that KDCs were generally formed in slow rotators that had experienced

multiple gas-poor minor mergers. They proposed that their recent mass assembly histories


are devoid of any major mergers and are expected to have older stellar populations. Few,

if any GCs, are expected to have formed from such mergers. It is unclear whether blue

GCs from the accreted galaxies would form a more elongated distribution than the host

galaxy starlight as we observe.

In summary, the ellipticities of red GC subpopulations have a one-to-one relation with

the galaxy stellar light ellipticities, whereas only a weak relation is seen for the blue GC

subpopulation. Additionally, slowly rotating galaxies with a KDC have larger values for

blue GC subpopulation ellipticities than their red GC counterparts. The elongated shape

of the blue GC subpopulations may be due to recent minor mergers that were asymmetric

in direction (Tempel et al., 2015).

5.2.7 GC metallicity gradients and galaxy stellar mass

Colour gradients are important observational features for exploring the formation history

of GC subpopulations and are clues to galaxy mass assembly. A negative colour gradient

(GCs are redder at the centre of the galaxy than the outskirts) represents either the

presence of younger (or more metal-rich) GCs at the galaxy centre or older (more metal-

poor) GCs at the outskirts. As GCs are observed to be mostly old (∼ 10 Gyr, Strader

et al. 2005; Dotter et al. 2010; Forbes et al. 2015), the colour gradients are basically caused

by metallicity gradients rather than age gradients.

The observed gradients in GC subpopulations help discriminate between the different

galaxy formation processes e.g., a negative gradient is predicted when the GCs are formed

from a dissipative collapse (Pipino et al., 2010), while a gas-poor major merger will wash

away any existing gradient (Di Matteo et al., 2009), a gas-rich major merger may remake

a new gradient different from the original one (Hopkins et al., 2009), etc. Also, minor

mergers (accretions) can deposit GCs in the outskirts of galaxies (Hirschmann et al.,

2015; Pastorello et al., 2015) which will alter the existing gradient, perhaps resulting in an

inner negative gradient and a flat outer gradient (Oser et al., 2010; Forbes et al., 2011).

The first detection of a radial colour gradient in a GC system was by Geisler et al.

(1996) in NGC 4472. With ground based data, GC colour gradients have been detected

in other massive galaxies (NGC 4486: Harris 2009b, NGC 1407: Forbes et al. 2011, NGC

4365: Blom et al. 2012), while only seen in a handful of intermediate mass galaxies (NGC

3115: Arnold et al. 2011, NGC 4564: Hargis & Rhode 2014) to date.

In NGC 3607, another intermediate mass galaxy, the mean colours of both the blue and

the red GC subpopulations reveal a significant colour gradient in the inner 6.5 arcmin (10

Re). The colour gradient for the blue subpopulation is steeper than the red subpopulation.


Table 5.4 List of twelve galaxies observed with metallicity gradients for GC subpopulations.The metallicity gradients (∆[Z/H]) given below are obtained from the colour gradients.Galaxy name, logarithmic galaxy stellar mass, metallicity gradients for blue and red GCsubpopulations with errors and the corresponding references (for colour gradient followedby the transformation equation used) are given.

Galaxy log(M?) Metallicity Gradient Ref.NGC Blue GCs Red GCs

(M�) (dex dex−1) (dex dex−1)

1399 11.660 −0.12±0.05 −0.10±0.05 1, 141399 11.660 −0.21±0.04 – 2, 111407 11.892 −0.22±0.04 −0.24±0.07 3, 103115 11.249 −0.17±0.03 −0.24±0.06 4, 103115 11.239 −0.27±0.06 −0.11±0.10 5, 53607 11.677 −0.33±0.06 −0.16±0.07 6, 103608 11.205 −0.25±0.05 – 6, 103923 11.796 −0.18±0.07 −0.17±0.08 5, 54278 11.290 −0.23±0.10 −0.23±0.12 7, 144365 11.843 −0.19±0.01 −0.22±0.03 8, 144472 12.046 −0.08±0.04 −0.10±0.05 1, 144472 12.046 −0.13±0.03 −0.10±0.05 9, 114486 11.953 −0.12±0.02 −0.12±0.03 1, 144486 11.953 −0.09±0.01 −0.12±0.01 10, 104486 11.953 −0.17±0.07 −0.17±0.05 11, 114594 11.653 −0.17±0.04 −0.17±0.04 12, 124649 11.867 −0.00±0.04 −0.05±0.02 5, 54649 11.867 −0.21±0.05 – 13, 14

References– 1 - Liu et al. (2011); 2 - Bassino et al. (2006a); 3 - Forbes et al. (2011);4 - Arnold et al. (2011); 5 - Faifer et al. (2011); 6 - Chapter 4; 7 - Usher et al. (2013);

8 - Blom et al. (2012); 9 - Geisler et al. (1996); 10 - Harris (2009b); 11 - Forte et al.(2012); 12 - Hargis & Rhode (2014); 13 - Strader et al. (2012); 14 - Usher et al. (2013)

Within the total extent of the GC system (beyond 10 Re), only the blue subpopulation

has a significant colour gradient. We detect a significant colour gradient only for the blue

GC subpopulation of NGC 3608.

Table 5.4 compiles the list of galaxies in which colour gradients are detected for the

GC subpopulations. The colour gradients are detected in different colour filters. For a

uniform comparison, the different colour gradients are converted to metallicity gradients

(∆[Z/H]) using colour-metallicity transformation equations (references are given in Table

5.4). The converted metallicity gradients are given in Table 5.4. The list includes the

gradients obtained only from wide-field imaging data and hence we exclude galaxies with

single pointing HST/ACS imaging. This criterion excludes most galaxies from Liu et al.


(2011), for which only the central regions of target galaxies were covered. The sample of

galaxies in the Table includes two galaxies from this paper plus another ten galaxies. The

galaxy stellar masses are also tabulated. In order to calculate the galaxy stellar masses, we

used their distance and visual magnitude from NED and the mass to light ratios of Zepf

& Ashman (1993). In the sample of twelve galaxies, half have multiple measurements

of their metallicity gradients. We include all measured GC gradients and their quoted

uncertainties for the 12 galaxies. This comprises 18 measurements of blue GC gradients

and 15 measurements of red GC gradients for 12 galaxies.

In Table 5.4, multiple measurements are given for five galaxies. For the same galaxy,

the observed gradients are not always consistent among different works. For example, in

the case of NGC 4649 the gradients for the blue subpopulation are −0.00 ± 0.04 (Faifer

et al., 2011) and −0.21 ± 0.05 (Strader et al., 2011). Both studies extended to 7 Re. In

another example, the gradient for the red subpopulation of NGC 3115 is quoted in Arnold

et al. (2011) as −0.24±0.06, while Faifer et al. (2011) quoted −0.11±0.1. But in the case

of NGC 4472, Geisler et al. (1996) and Liu et al. (2011) find consistent gradients for the

red subpopulation.

Figure 5.7 shows the metallicity gradients for blue/red GC subpopulations versus the

galaxy stellar mass. We plot multiple measurements for individual galaxies. Linear fits are

carried out separately for the blue and the red GCs with uncertainties estimated from the

bootstrap technique. The technique uses the errors associated with individual gradients.

Best fit relations are:

∆[Z/H]BGC = [(0.31 ± 0.08) × log(M?)] − (3.8 ± 0.9) (5.10)

∆[Z/H]RGC = [(0.004 ± 0.1) × log(M?)] − (0.1 ± 1.0). (5.11)

The intrinsic scatter estimated for the above relations are ∼ 0.11. The galaxies in our

sample have a mass range 11.0 < log(M?) < 12.0 M�. From the above relations, we find

that the metallicity gradient for the blue subpopulation has a significant correlation with

stellar mass; the negative gradients flattens with increasing stellar mass. As more massive

galaxies are expected to accrete more satellites (Oser et al., 2010), we expect more GC

accretion to have taken place in these galaxies. This addition of mostly blue GCs at

different galactocentric radii may make the initial gradient of the blue GCs shallower. In

addition, Hirschmann et al. (2015) found that gradients resulting from major mergers are

shallower in more massive galaxies due to radial mixing of GCs. From the spectroscopic

metallicities of GC subpopulations in twelve ETGs, Pastorello et al. (2015) observe a


Figure 5.7 Metallicity gradients of GC subpopulations versus galaxy stellar mass. Themetallicity gradients (converted from colour gradients) for the blue (blue open circles)and the red (red filled diamonds) GC subpopulations for 12 galaxies are plotted againsthost galaxy stellar mass. The blue solid line and the red dashed line represent the linearfits to the metallicity gradients of blue and red GCs, respectively. It is evident from theplot that for the blue GC subpopulation, the metallicity gradients become shallower withincreasing galaxy stellar mass. Note that multiple measurements of metallicity gradientsfor the same galaxy are included.


similar trend of decreasing metallicity gradient with increasing galaxy stellar mass.

For the red GC subpopulation, we are unable to find a significant relation between the

metallicity gradient and galaxy stellar mass. In comparison with the blue GC subpopula-

tions, the metallicity gradients for the red GC subpopulations have higher errors and also

a lower number of data points. In Table 5.4, the least significant gradient measurement is

for the red subpopulation of NGC 3115 (Faifer et al., 2011). Hence, we carried out another

fitting for the red GCs without that measurement and the best fitted relation is

∆[Z/H]RGC = [(0.07 ± 0.05) × log(M?)] − (0.95 ± 0.86). (5.12)

From the above relation, we infer that the gradients for the red GC subpopulation show

a very weak dependence on galaxy stellar mass.

The galaxy stellar mass is derived from the M/L ratios that are given in Zepf & Ashman

(1993). We appreciate that the Zepf & Ashman (1993) values are an approximation but

have chosen to use them as this is the approach used by Rhode et al. (2010) and Spitler

et al. (2008). So in order to match the results with the above mentioned publications, we

use the same method. Bell et al. (2003) derived the relationships to estimate the stellar

mass from galaxy colours (see Appendix B.1 for details). We used their relationship to

derive the galaxy stellar mass from (B - V) colour. We find that the equations 5.10 – 5.12

are statistically unchanged when using Bell et al. (2003) to derive galaxy stellar masses.

In summary, we suggest that the subsequent addition of GCs from minor mergers

may weaken any pre-existing gradients in metallicity (from an early dissipative formation

event) both for the blue and the red GC subpopulations.

5.3 GC system formation scenarios

As described in the introduction, three ’classic’ formation scenarios were proposed to

explain bimodality in globular cluster systems. In the major merger model (Ashman &

Zepf, 1992), the blue GCs already exist in the merging galaxies, while the red GCs form

during the merging process. In the multi-phase collapse scenario (Forbes et al., 1997),

the blue GCs are formed early, followed by a quiescent phase. After a few Gyrs, star

formation is restarted with the formation of red GCs, which can be followed by accretion

of additional blue GCs. According to Cote et al. (1998, 2000), the red GCs are inherent

to the parent galaxies and the blue GCs are purely accreted from dwarf galaxies.

The three classic scenarios were explored in cosmological simulations which addressed a

variety of GC system properties: structural and kinematical (Bekki et al., 2005), dynamical

5.3. GC system formation scenarios 121

and chemical (Bekki et al., 2008), colour and metallicity bimodality (Muratov & Gnedin,

2010; Tonini, 2013), as well as physical relationships with the host galaxies (Beasley et al.,

2002). Recently, Trenti et al. (2015) proposed another scenario for GC formation from the

merging of multiple gas rich mini halos.

In all the classic formation scenarios, there is a strong association between red GC

subpopulations and the parent galaxy. This relationship is established from different

observations such as the strong relation between red GC peak colour and galaxy luminosity

(Peng et al., 2006; Strader et al., 2006; Faifer et al., 2011), position angle arrangement

of red GCs and the galaxy stellar component (Wang et al., 2013), connection between

rotation velocity for red GCs and field stars (Pota et al., 2013) etc. On the other hand,

the association between blue GC subpopulations and parent galaxy stars is weak. Peacock

et al. (2015) found that the blue GC subpopulations of NGC 3115 are consistent with the

stellar halo in metallicity and spatial distributions. However, the origin of the blue GC

subpopulation is quite controversial. Cote et al. (1998, 2000) and Tonini (2013) proposed

a dissipationless accretion origin whereas dissipational in-situ formation (Forbes et al.,

1997; Beasley et al., 2003) is suggested for the formation of blue GCs in the inner regions.

This distinction in region (inner or outer) is mentioned since accretion of blue GCs to the

galaxy outskirts in the later phase is also included in the multi-phase scenario (Forbes

et al., 1997).

Strader et al. (2004, 2005) investigated the feasibility of the above formation scenarios

using observational data for massive elliptical galaxies. From the GC colour-galaxy lu-

minosity relation and the age-metallicity relation, they proposed an in-situ plus accretion

model for the formation of inner blue GCs which were then truncated by reionization,

whereas the red GCs formed along with the bulk of field stars. They suggested that dwarf

galaxies residing in overdense regions collapse before dwarfs in less dense regions, and then

accrete more enriched gas from nearby star forming regions. These dwarf galaxies, along

with their blue GCs, are later accreted into the halo of a massive galaxy forming part

of the main system. This implies an in-situ+accretion origin for blue GCs. Hence, the

origin of blue GCs in the inner regions could be due to one of three proposed processes,

i.e. completely in-situ, fully accreted or in-situ+accretion.

In the following paragraphs, we try to differentiate between these three formation

processes for blue GCs based on their global properties. In particular, we measure radial

density, radial colour and azimuthal distributions in relation to their parent galaxies.

From the azimuthal distribution of GC subpopulations, both blue and red GCs have a

positional arrangement in common with the galaxy stellar light component (Wang et al.,


2013). This suggests that the blue GC subpopulation and galaxy stellar component have

similar evolutionary histories. For galaxies in which the blue GCs and stars accreted from

satellite dwarfs, this similarity is expected (Cote et al., 2001). From the derived ellipticities

it is seen that red GC subpopulations have a one-to-one relation with the galaxy stellar

component whereas the relation is not tight for blue GC subpopulations (see Figure 5.6).

If the galaxy has accreted its blue GCs recently, then a complete one-to-one correlation

with host galaxy properties is not expected. Park & Lee (2013) also investigated this

relationship for 23 early-type galaxies using ACSVCS data and found an approximate

one-to-one relation between blue GC ellipticity and the galaxy stellar component. As

is well-known, the ACS field of view does not provide anywhere near complete coverage

for massive nearby galaxies (Peng et al., 2006). That means a nearly one-to-one relation

between inner blue GCs and galaxy stellar component suggests a common origin for both

and hence, supports the in-situ formation scenario.

Another diagnostic trend is the GC subpopulation peak colour versus galaxy lumi-

nosity. The peak colour of the red GC subpopulation gets redder with increasing galaxy

luminosity. Perhaps a weaker correlation exists for the blue GC subpopulation. Liu et al.

(2011) found that projection effects tend to flatten GC radial trends, particularly for the

blue subpopulation because if its extended nature. Hence, the slope of the relation between

the blue GC subpopulation peak colour and galaxy luminosity is reduced to half (−0.0069

± 0.0025) of the earlier value (−0.0126 ± 0.0025: Peng et al. 2006), making the relation

between peak colour of the blue GC subpopulation and galaxy luminosity insignificant.

This result weakens the idea that the formation of blue GCs is via in-situ processes.

Radial colour gradients may also reveal the origin of blue GCs. The colour gradients for

blue GCs formed in-situ are expected to be steeper than for a subpopulation formed from

in-situ+accretion or completely accreted processes. We expect this because the addition

of GCs through accretion can dilute (in the case of in-situ+accretion) the existing colour

gradient for the blue GC subpopulation. In the case of complete accretion, we assume

zero colour gradient for the blue subpopulation. Hence, to disentangle the origin of blue

GCs, the steepness of the gradient needs to be quantified with large samples of galaxies

where the colour gradients are measured with maximum accuracy. Our present work is

limited by a small sample of 10 galaxies collected from the literature (Geisler et al., 1996;

Bassino et al., 2006a; Harris, 2009b; Forbes et al., 2011; Faifer et al., 2011; Arnold et al.,

2011; Blom et al., 2012; Usher et al., 2013; Hargis & Rhode, 2014) and two from this work.

Liu et al. (2011) carried out an analysis of the colour gradients for 76 early-type galaxies

using ACSVCS and ACS Fornax Cluster Survey (FCS). Even though the sample size is

5.4. Conclusions 123

impressive, only three galaxies have more than one pointing and we have included them in

the above sample. Hence, significant color gradients are detected in a total of 12 galaxies,

five of which have multiple measurement. Gradient values are provided in Table 5.4.

Figure 5.7 show this sample of GC metallicity gradients plotted against host galaxy

stellar mass. The blue GC subpopulation shows a trend of decreasing gradient with in-

creasing galaxy stellar mass. This implies that high mass galaxies have shallower gradients,

whereas low mass (log(M?) ∼ 11.0 M�) galaxies have steeper gradients. As the metallic-

ity gradients show a dependency on galaxy stellar mass, both the GC subpopulations are

expected to have some formational similarities with the galaxy stellar component. This

means that a completely accreted origin (Cote et al., 1998, 2000; Tonini, 2013) may not

be the best scenario to explain the formation of blue GCs. Also, we notice that both

GC subpopulation gradients show a dependence on galaxy stellar mass (see Figure 5.7).

Thus, a common, or in-situ origin (Forbes et al., 1997; Beasley et al., 2003), is probably

involved in the formation of blue and red GC subpopulations (Pastorello et al., 2015).

However, we note that large red (early-type) galaxies tend to preferentially accrete red

satellite galaxies (Hearin et al., 2014; Hudson et al., 2015). Thus GC system metallicity

gradients may also reflect the gradients of the accreted satellites, if they are preserved

in the accretion process.In the in-situ+accretion formation scenario (Strader et al., 2004,

2005) for the blue GCs, we expect the gradient to be shallower than for the blue GCs

formed completely in-situ, but a reference scale is not yet established by models.

To summarise, from the present study it is difficult to ascribe either a completely in-

situ or an in-situ+accretion origin for the blue GC subpopulations. A homogeneous large

sample with accurate GC properties is needed to address this issue in depth.

5.4 Conclusions

We discuss seven global relationships between the host galaxy and the GC system. We

found that the spatial extent of a GC system is dependent on the host galaxy stellar

mass/luminosity and the effective radius of the galaxy. Knowing the host galaxy luminos-

ity, or the size of the galaxy, can therefore provide an estimation of the extent of the GC

system. The extent of a GC system is determined to be ∼ 14 times the effective radius

of the host galaxy. The spatial extent of GC systems in elliptical and lenticular galaxies

shows a strong dependence on host galaxy stellar mass, but not for spiral galaxies. Also,

we confirm that the extent of a GC system is a function of galaxy size and the effective

radius of a GC system is nearly 6 times the effective radius of parent galaxy.

We analysed the relation between ellipticities for blue and red GC subpopulations and


galaxy stellar light for a sample of ten galaxies. We obtain a one-to-one relation between

the parent red GC ellipticities and galaxy stellar light ellipticities. We support the view

that the red GCs and the galaxy stellar light have a coeval formation. This result from a

small sample of ten galaxies and is supported by Park & Lee (2013). Also, the blue GC

ellipticities of slow rotators with kinematically decoupled cores are more elongated than

their red GC subpopulation ellipticities. We propose that they might have experienced

recent minor mergers from anisotropic directions (Tempel et al., 2015).

We also found that the relative fraction of blue to red GCs decreases with galaxy

environment density for lenticular galaxies. This result is in general agreement with the

observations of Cho et al. (2012) and in disagreement with the predictions of Tonini (2013).

We did not observe any specific trend for elliptical (supporting Spitler et al. 2008) and

spiral galaxies with galaxy environment density. An interaction between galaxies, which

can decrease the blue GC number in cluster environments, is tidal stripping. Through

tidal effects, the outer halo (containing the blue GCs) of the small galaxy may be stripped

away giving a lower fraction of blue to red GCs (Forbes et al., 1997; Bassino et al., 2006a,b)

for lenticular galaxies in cluster environments.

From a sample of twelve galaxies, we investigate the relationship between the metal-

licity gradients and host galaxy stellar mass. We found that the gradients of both GC

subpopulations become shallower with increasing stellar mass. The average ratio of blue

to red GCs in galaxies in the mass range 11.0 < log(M?) < 12.0 M� is nearly 1.7. These

findings agree with the predictions from the simulations of Bekki et al. (2008) and also

with the findings from other observations (Peng et al., 2006). We also carried out a study

to disentangle the formation of blue GC subpopulations (i.e. completely in-situ versus in-

situ+accretion versus completely accreted), which have not given conclusive results and

need to be followed up with a homogeneous, large sample.

6Conclusions

6.1 Conclusions

In this thesis we described the impact of GC system studies in understanding the evolution

of their parent galaxies. During the evolution of galaxies, they leave behind records of the

transformative events. These records are best preserved in the galaxy halos rather than

in the well mixed inner galaxy regions. To probe these galaxy halos, we utilised the GC

systems to trace these evolutionary events. Due to the strong internal gravitational forces,

the majority of the GCs overcome destruction caused by powerful events such as galaxy

merging, accretion or tidal stripping. Additionally, their luminosity and compactness are

the key features which make them detectable even at large radii from the galaxy centre.

In this study we investigated the characteristics of GC systems to retrieve evolutionary

information about ETGs.

This thesis has presented wide-field imaging studies of a sample of five intermediate

mass ETGs. Our five target galaxies are a part of the ongoing SLUGGS survey, which uses

the wide-field imaging data from the Subaru telescope. This thesis is also complemented

with data from the Canada France Hawaii telescope, the Keck II telescope and the Hubble

Space Telescope. We explored the individual GC systems and investigated their radial

density, radial colour and azimuthal distributions. We also separated the total system

into subpopulations and investigated their properties. Only a handful of GC system

studies have explored the GC subpopulation properties in intermediate mass galaxies,

where this study has enhanced the number statistics. Combined with similar GC system

literature studies, we provided a detailed analysis of global property relationships between

GC systems and their host galaxies.

Even though each chapter is provided with independent conclusions, we summarise

below the major outcomes.

125

126 Chapter 6. Conclusions

In Chapter 3, we investigated the distributions of GC systems in three ETGs (NGC

720, NGC 1023 and NGC 2768) residing either in the field or small group environments.

We determined the extent of the GC systems for the three galaxies and found that the

estimation matches with Young et al. (2012) for NGC 1023. However, our finding for the

GC system extent of NGC 2768 is a first estimate using the wide-field imaging, while the

GC system extent of NGC 720 is ∼ 3 times larger than the literature study of Kissler-

Patig et al. (1996). Colour magnitude diagrams for the three galaxies show strong bimodal

colour distributions, with greater than 60 percent blue GCs detected in NGC 720 and NGC

2768 whereas ∼ 40 percent blue GCs in NGC 1023. We derived the total GC number and

specific frequency for all three galaxies. The specific frequency for NGC 720 is in between

galaxies in the field and small groups. Also, the specific frequency value matches that

of shell galaxies and we detect shell structures in the central region of NGC 720. For

NGC 2768, we note that the specific frequency is lower than other galaxies with similar

luminosity (Brodie & Strader, 2006).

With the classification of GC subpopulations, we found that the blue GC subpopu-

lation is always more extended than the red subpopulation in the three galaxies. Also,

both subpopulations are arranged along the position angle of the galaxy stellar light. The

distribution of red GCs matches with the ellipticity values of the galaxy stellar component

in NGC 720 and NGC 1023, while both subpopulations and galaxy stellar light show an

elongated distribution in NGC 2768. In addition the effective radius of the red subpopu-

lation matches with the galaxy stellar light in all three galaxies. These evidences support

the coeval formation between the red GC subpopulation and galaxy stellar component in

the three galaxies (Larsen et al., 2001; Spitler, 2010; Forbes et al., 2012a). In the central

region of NGC 2768, we observed a slight, but significant, negative colour gradient for the

blue GC subpopulation.

We explored the GC systems of two central galaxies in the Leo II group in Chapter 4.

To separate the GC systems of the individual galaxies, we introduced two methods: the

surface brightness method and the major axis method. We determined the GC system

extents for NGC 3607 and NGC 3608 as 4.4 and 4.7 effective radii respectively. For both

GC systems, we confirmed that the colour magnitude diagrams are bimodal in nature with

45 and 65 percent blue GCs in NGC 3607 and NGC 3608 respectively. Complementary

spectroscopic data obtained from the Keck II telescope detected 81 GCs in the Leo II

group.

The GC subpopulation study revealed that both galaxies have a central concentration

of red subpopulation and an extended blue subpopulation. For NGC 3607, the radial

6.1. Conclusions 127

density distribution of red GC subpopulation matches with the galaxy surface brightness

distribution. Also, the effective radius of red subpopulation is similar to the galaxy stellar

light than the blue subpopulation. This implies a significant association between the

two. However for NGC 3608, the radial density distribution of red subpopulation shows

similarities with galaxy stellar light, but the effective radius of red subpopulation is bigger

than the galaxy stellar light.

The azimuthal distributions of NGC 3607 GC system showed that both subpopula-

tions (∼ 110 degrees) are reasonably aligned with the galaxy stellar light (125 degrees).

Among the two subpopulations of NGC 3607, the red one showed a more elongated dis-

tribution than the blue. In the case of NGC 3608, both subpopulations deviate from the

position angle of galaxy stellar light. The blue GC subpopulation presented an elongated

distribution in comparison to the red subpopulation. Each of these galaxies showed an

overabundance of GCs along the direction of other galaxy, which we confirmed as a genuine

feature. Hence, the misalignment in GC position angles and GC overabundance suggested

a possible interaction between the two and supports the proposition by Jedrzejewski &

Schechter (1988).

Using our imaging data we detected significant colour gradients in the total GC system

and blue, red subpopulations of NGC 3607. We also noticed that the gradient for the blue

subpopulation is steeper than the red subpopulation. In NGC 3608, we detected a strong

colour gradient only for the blue subpopulation. The negative colour gradients in NGC

3607 and NGC 3608 are associated with their evolutionary events and it supports an in-

situ dissipative formation for the respective GC subpopulations (Harris, 2009b; Forbes

et al., 2011).

With the GC system and subpopulation properties extracted from the wide-field imag-

ing studies (shown in Chapter 3 & 4), we are able to explore their global relationships

with host galaxies. In Chapter 5, we investigated seven different relationships between

host galaxies and GC system properties. For this study, we utilised our sample of five

galaxies, another four from the SLUGGS survey studies and thirty three galaxies from

literature studies. With our sample of galaxies, we concluded that the GC system extent

is proportional to host galaxy stellar mass. We also confirmed that this relation is weak

for spiral galaxies. As the above relation between stellar mass and GC system extent

involves mass to light ratio and quality of observational data, the relation may be vastly

affected by their errors. Hence, we explored the relationship between effective radius of

GC systems and host galaxies. We found that the GC system effective radius is about 6

times the galaxy effective radius and this supports various literature studies (Harris et al.,


2000; Forbes et al., 2006b; Brodie & Strader, 2006; Alamo-Martınez et al., 2012; Cantiello

et al., 2015).

With a sample of ten galaxies, we investigated the relationship between blue or red

GC subpopulation ellipticities with galaxy stellar light ellipticities. We observed that

the red GC ellipticities follow a one-to-one relationship with the galaxy ellipticities (Park

& Lee, 2013). This confirmed that the red GC subpopulations might have originated

together with galaxy stars. In contrast to Park & Lee (2013), we noticed that the blue

GC ellipticities show a weak relationship with galaxy ellipticities. We proposed that this

disparity might be the result of wide-field imaging data in comparison to HST/ACS data

as it fails to detect all of the blue GC subpopulation for the most extended galaxies

(Peng et al., 2006). Four out of ten galaxies in this sample have more elongated blue

subpopulation ellipticities than the red subpopulation. These four galaxies belong to the

category of slow rotator galaxies with kinematically decoupled cores. We suggested that

the elongated shapes of blue GC subpopulation may be due to recent minor mergers that

were asymmetric in direction (Tempel et al., 2015).

We investigated the impact of galaxy environment in varying the ratio of blue to red

GCs in elliptical, lenticular and spiral galaxies. We detected that the ratio of blue to red

GCs decreases with increase in local galaxy density for lenticular galaxies. This implies

that the relative number of red GCs increases with increase in local galaxy density. Our

finding supported the Cho et al. (2012) result, while in disagreement with Tonini (2013).

No specific trend is observed for elliptical galaxies and this is in agreement with Spitler

et al. (2008). As the density of local galaxies increases, the chance for galaxy interaction

also increases. Through galaxy interactions, e.g. tidal stripping (Forbes et al., 1997;

Bassino et al., 2006a,b), lenticular galaxies might have lost their blue GCs and might have

ended up with low ratio of blue to red GCs. This might be a possible reason for the

decreasing ratio of blue to red GCs in lenticular galaxies.

With the available metallicity gradients for GC subpopulations, we searched for a

(in)dependence of metallicity gradients with galaxy stellar mass. We observed that the

metallicity gradient for the blue subpopulation has a significant correlation with stellar

mass; the negative gradients flattens with increasing stellar mass. Also, we infered that

the gradients for the red GC subpopulation show a very weak dependence on galaxy stellar

mass. Hence, we suggested that the subsequent addition of GCs from minor mergers may

weaken any pre-existing gradients in metallicity for both GC subpopulations (Oser et al.,

2010; Hirschmann et al., 2015). To disentangle the formation of blue GC subpopulations

(i.e. completely in-situ versus in-situ+accretion versus completely accreted), we carried

6.2. Future directions 129

out a study which have not given conclusive results and needs to be followed up with a

homogeneous, large sample.

6.2 Future directions

The study of GC systems and their subpopulations in ETGs provides us with information

about the evolutionary history of GC systems and their host galaxies. To improve our

understanding about the two, we present here some future directions.

• Imaging data for more field/isolated ETGs

As mentioned in Chapter 3, galaxies situated in isolated environments are expected

to experience less interactions/mergers than in clusters. Also, the isolated galaxies

preserve the residuals of the evolutionary events that occurred in their surroundings

such as ripples, shells or halo substructures. Thus isolated/field galaxies can be called

‘pristine systems’. With the aid of deep imaging, we can detect these substructures

and hence retrieve knowledge about their evolution. Only a handful of field ETGs

have been studied using wide-field imaging for their GC systems and by increasing

their statistics we will improve the information about their characteristics of field

ETGs.

• Lenticular galaxies and local galaxy density

In Chapter 5, we obtained the result that the ratio of blue to red GCs decreases with

increasing local galaxy density of lenticular galaxies. We derived this relationship

from the imaging data of only ten lenticular galaxies. In the SLUGGS survey, we aim

to explore the GC systems of ∼ 14 lenticular galaxies, out of which three are only

included in this study. Expanding this study with another 11 galaxies will provide

us a range of lenticular galaxies that differ in mass and local galaxy density.

• Complete imaging study of the SLUGGS survey

The SLUGGS survey aims to study the physical, kinematical and chemo-dynamical

studies of 25 plus 3 bonus galaxies. Detailed analysis of the imaging data for 10

galaxies (5 from Chapter 3 & 4) are published to date. With the completion of the

imaging studies of 28 galaxies, we are equipped with a homogeneous large sample.

This will provide a better platform to explore the global property studies given in

Chapter 5.

• Need for more simulations

Recently, Tonini (2013) modelled the hierarchical assembly of galaxies and one of


her predictions was that more blue GCs are expected in ETGs residing in higher

galaxy densities. However, our study do not support this proposition in its entirety.

Hence, there is a need for improved simulations that better predict characteristics

of GC subpopulations and their relationship with galaxy properties.

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AConfirmed GCs around the Leo II group

A.1 List of spectroscopically confirmed objects around the Leo

II group

Table A.1 presents the photometric magnitudes g, r and i and the radial velocities for

GCs, Galactic stars and background galaxies detected around NGC 3607 and NGC 3608

in the Leo II group.

The horizontal lines differentiate GCs of NGC 3607, GCs of NGC 3608, 7 ambiguous

objects (classified into GCs and probable UCD - see Section 4.3.3), Galactic stars and

background galaxies. Column 1 represents the object ID with the galaxy name followed by

the object classification such as GC, star and galaxy. Columns 2 and 3 present the position

in Right Ascension and Declination (J2000). Columns 4 – 9 present the Subaru/Suprime-

Cam photometry in g, r and i filters and their respective uncertainties (given here are

extinction corrected magnitudes). The heliocentric velocity and the respective uncertainty

for each object is given in column 10 and 11.

141

142 Appendix A. Confirmed GCs around the Leo II group

Tab

leA

.1.

Cat

alog

ue

ofob

ject

sdet

ecte

dar

oun

dN

GC

3607

an

dN

GC

3608

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

07G

C1

169.

2172

2918

.0033

0022

.320

0.00

221

.863

0.00

321

.653

0.00

395

814

NG

C36

07G

C2

169.

2314

2518

.0224

0022

.782

0.00

322

.019

0.00

321

.622

0.00

392

49

NG

C36

07G

C3

169.

2988

2918

.0257

7422

.706

0.00

422

.228

0.00

322

.027

0.00

412

5513

NG

C36

07G

C4

169.

2687

8818

.0265

1622

.646

0.00

321

.898

0.00

221

.533

0.00

391

012

NG

C36

07G

C5

169.

2477

6318

.0293

3121

.396

0.00

120

.756

0.00

120

.492

0.00

190

45

NG

C36

07G

C6

169.

2397

9218

.0278

0022

.370

0.00

221

.734

0.00

221

.477

0.00

382

515

NG

C36

07G

C7

169.

2018

8318

.0325

6623

.010

0.00

322

.235

0.00

321

.837

0.00

396

117

NG

C36

07G

C8

169.

2515

2518

.0341

0522

.218

0.00

221

.596

0.00

221

.361

0.00

273

213

NG

C36

07G

C9

169.

2088

5018

.0351

4120

.924

0.00

120

.340

0.00

120

.115

0.00

195

04

NG

C36

07G

C10

169.

2301

5018

.0371

7022

.053

0.00

221

.321

0.00

221

.027

0.00

292

415

NG

C36

07G

C11

169.

1990

6718

.0372

6423

.225

0.00

422

.434

0.00

422

.066

0.00

411

3615

NG

C36

07G

C12

169.

1594

9218

.0334

9424

.264

0.01

123

.764

0.01

423

.499

0.01

410

5212

NG

C36

07G

C13

169.

2360

6718

.0381

7222

.161

0.00

221

.525

0.00

221

.279

0.00

279

213

NG

C36

07G

C14

169.

0992

1718

.0395

6822

.358

0.00

221

.732

0.00

221

.482

0.00

210

4815

NG

C36

07G

C15

169.

2075

3318

.0431

0023

.017

0.00

422

.368

0.00

422

.065

0.00

476

417

NG

C36

07G

C16

169.

2136

7118

.0443

0023

.698

0.00

523

.089

0.00

622

.770

0.00

710

6014

NG

C36

07G

C17

169.

2376

9218

.0478

0021

.814

0.00

121

.057

0.00

120

.719

0.00

192

012

NG

C36

07G

C18

169.

2389

7918

.0490

0023

.307

0.00

722

.484

0.00

721

.903

0.00

610

9213

NG

C36

07G

C19

169.

1844

7518

.0496

4822

.226

0.00

221

.579

0.00

321

.377

0.00

296

613

A.1. List of spectroscopically confirmed objects around the Leo II group 143

Tab

leA

.1(c

ont’

d)

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

07G

C20

169.

1944

5818

.0520

8222

.753

0.00

322

.098

0.00

321

.713

0.00

497

414

NG

C36

07G

C21

169.

2407

2118

.0545

0021

.360

0.00

120

.738

0.00

120

.463

0.00

159

89

NG

C36

07G

C22

169.

2207

3818

.0478

1521

.831

0.00

121

.313

0.00

121

.092

0.00

213

0319

NG

C36

07G

C23

169.

2426

8318

.0552

8321

.524

0.00

120

.757

0.00

120

.448

0.00

184

09

NG

C36

07G

C24

169.

2653

7118

.0600

0522

.899

0.00

322

.149

0.00

321

.811

0.00

310

2711

NG

C36

07G

C25

169.

2321

9618

.0585

0023

.611

0.00

622

.948

0.00

622

.492

0.00

698

713

NG

C36

07G

C26

169.

2717

9218

.0650

6523

.112

0.00

422

.420

0.00

422

.110

0.00

410

2512

NG

C36

07G

C27

169.

1863

9218

.0652

0021

.930

0.00

221

.293

0.00

321

.060

0.00

384

816

NG

C36

07G

C28

169.

2199

7918

.0683

0021

.646

0.00

120

.972

0.00

120

.655

0.00

183

56

NG

C36

07G

C29

169.

2371

0418

.0743

9822

.956

0.00

422

.211

0.00

421

.830

0.00

495

816

NG

C36

07G

C30

169.

2136

7118

.0763

0024

.242

0.00

923

.568

0.00

923

.240

0.01

1012

12N

GC

3607

GC

3116

9.30

8429

18.0

751

7823

.142

0.00

422

.514

0.00

422

.248

0.00

594

914

NG

C36

07G

C32

169.

2290

9218

.0868

0022

.753

0.00

322

.003

0.00

321

.650

0.00

381

59

NG

C36

07G

C33

169.

2125

4218

.0870

0021

.839

0.00

121

.158

0.00

120

.890

0.00

298

57

NG

C36

07G

C34

169.

1604

4218

.1060

1822

.294

0.00

221

.748

0.00

221

.521

0.00

369

49

NG

C36

07G

C35

169.

1068

4218

.1407

2423

.123

0.00

422

.499

0.00

422

.267

0.00

511

3818

NG

C36

07G

C36

169.

3764

0718

.2067

2622

.467

0.00

221

.941

0.00

321

.741

0.00

311

0614

NG

C36

07G

C37

169.

1897

0018

.0111

8923

.796

0.00

523

.047

0.00

522

.757

0.00

672

317

NG

C36

07G

C38

169.

2110

2518

.0187

5322

.581

0.00

222

.030

0.00

321

.810

0.00

394

018


Tab

leA

.1(c

ont’

d)

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

07G

C39

169.

2223

5418

.0450

2121

.901

0.00

121

.198

0.00

120

.898

0.00

111

4523

NG

C36

07G

C40

169.

2034

7118

.0383

6622

.804

0.00

422

.081

0.00

421

.699

0.00

477

514

NG

C36

07G

C41

169.

2331

0018

.0404

3422

.867

0.00

322

.145

0.00

321

.782

0.00

387

326

NG

C36

07G

C42

169.

2420

0818

.0746

8424

.662

0.01

324

.083

0.01

623

.961

0.01

811

8819

NG

C36

07G

C43

169.

1070

9918

.2441

9422

.618

0.00

322

.043

0.00

321

.819

0.00

312

7916

NG

C36

08G

C1

169.

2319

4218

.1297

0025

.547

0.02

124

.951

0.02

324

.783

0.02

810

3913

NG

C36

08G

C2

169.

2467

1718

.1310

9022

.657

0.00

322

.041

0.00

321

.806

0.00

312

9313

NG

C36

08G

C3

169.

2611

2918

.1358

7521

.721

0.00

121

.065

0.00

120

.849

0.00

110

916

NG

C36

08G

C4

169.

2271

9218

.1385

0021

.595

0.00

120

.916

0.00

120

.648

0.00

112

728

NG

C36

08G

C5

169.

2981

5818

.1388

8622

.732

0.00

322

.140

0.00

321

.918

0.00

312

4215

NG

C36

08G

C6

169.

2458

3318

.1461

1123

.950

0.00

723

.105

0.00

622

.668

0.00

611

7629

NG

C36

08G

C7

169.

2696

9218

.1391

2622

.568

0.00

221

.890

0.00

321

.623

0.00

314

589

NG

C36

08G

C8

169.

2637

3318

.1426

7124

.392

0.00

923

.568

0.00

923

.227

0.00

911

4115

NG

C36

08G

C9

169.

2240

5818

.1452

5422

.229

0.00

221

.650

0.00

221

.418

0.00

214

9314

NG

C36

08G

C10

169.

2412

6618

.144

3121

.213

0.00

120

.639

0.00

120

.371

0.00

112

0312

NG

C36

08G

C11

169.

2758

2518

.1515

0624

.155

0.01

123

.506

0.01

123

.181

0.01

314

6719

NG

C36

08G

C12

169.

2982

0018

.1494

0522

.834

0.00

322

.243

0.00

322

.044

0.00

410

6112

NG

C36

08G

C13

169.

2223

8318

.1555

0022

.851

0.00

322

.260

0.00

322

.029

0.00

495

715

NG

C36

08G

C14

169.

2433

4218

.1566

0022

.166

0.00

221

.581

0.00

221

.258

0.00

213

3512


Tab

leA

.1(c

ont’

d)

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

08G

C15

169.

2292

0818

.1677

0023

.038

0.00

322

.479

0.00

322

.272

0.00

412

2917

NG

C36

08G

C16

169.

3242

0818

.1635

6922

.591

0.00

221

.995

0.00

321

.763

0.00

312

689

NG

C36

08G

C17

169.

2602

2118

.1652

1122

.266

0.00

221

.670

0.00

221

.487

0.00

212

8312

NG

C36

08G

C18

169.

2734

9618

.1654

1123

.057

0.00

522

.558

0.00

522

.414

0.00

510

3813

NG

C36

08G

C19

169.

2929

3618

.1669

1621

.915

0.00

221

.332

0.00

221

.130

0.00

211

767

NG

C36

08G

C20

169.

2292

0718

.1677

2522

.623

0.00

221

.976

0.00

221

.741

0.00

312

3314

NG

C36

08G

C21

169.

2525

8318

.1687

0022

.874

0.00

322

.248

0.00

422

.035

0.00

412

4719

NG

C36

08G

C22

169.

3208

3118

.1698

3022

.265

0.00

221

.576

0.00

221

.289

0.00

213

837

NG

C36

08G

C23

169.

3378

1218

.1714

5922

.885

0.00

322

.267

0.00

422

.031

0.00

412

9411

NG

C36

08G

C24

169.

2204

9518

.1731

1323

.444

0.00

622

.925

0.00

522

.703

0.00

611

1817

NG

C36

08G

C25

169.

2598

0618

.1794

4722

.292

0.00

321

.759

0.00

321

.582

0.00

313

858

NG

C36

08G

C26

169.

2379

4618

.1381

5723

.728

0.00

522

.946

0.00

522

.619

0.00

510

3126

NG

C36

08G

C27

169.

2713

2118

.1598

6823

.265

0.00

422

.567

0.00

422

.266

0.00

480

822

NG

C36

08G

C28

169.

2287

7918

.1336

7522

.476

0.00

221

.936

0.00

221

.736

0.00

313

5817

NG

C36

08G

C29

169.

2669

4618

.1588

1523

.398

0.00

422

.629

0.00

422

.304

0.00

410

7618

NG

C36

08G

C30

169.

2135

7118

.1596

8523

.121

0.00

422

.496

0.00

422

.268

0.00

412

3825

NG

C36

08G

C31

169.

2540

5518

.1608

2423

.176

0.00

422

.574

0.00

422

.354

0.00

513

2812

NG

C36

08G

C32

169.

2566

1618

.1693

9023

.532

0.00

522

.965

0.00

622

.689

0.00

611

8019

NG

C36

07G

C44

169.

3033

5018

.0824

0522

.710

0.00

322

.061

0.00

321

.800

0.00

313

1811


Tab

leA

.1(c

ont’

d)

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

07G

C45

169

.245

171

18.0

9570

022

.927

0.00

322

.233

0.00

321

.962

0.00

410

8914

NG

C36

07G

C46

169

.184

189

18.1

6435

822

.793

0.00

321

.974

0.00

321

.599

0.00

380

79

NG

C36

08G

C33

169

.203

088

18.1

3586

422

.218

0.00

221

.563

0.00

221

.314

0.00

211

6010

NG

C36

08G

C34

169

.217

304

18.1

0947

222

.905

0.00

422

.333

0.00

422

.084

0.00

512

8123

NG

C36

08G

C35

169

.192

558

18.1

2116

323

.079

0.00

422

.484

0.00

422

.250

0.00

512

2918

NG

C36

08ex

t116

9.19

7333

18.0

364

7222

.384

0.00

2021

.893

0.00

2021

.761

0.00

3018

2222

NG

C36

08st

ar1

169

.181

300

18.0

0049

022

.633

0.00

222

.119

0.00

321

.950

0.00

311

311

NG

C36

08st

ar2

169

.189

558

18.0

0411

421

.235

0.00

120

.761

0.00

120

.625

0.00

1−

106

7N

GC

3608

star

3169

.223

729

18.0

2522

925

.096

0.01

724

.464

0.01

824

.073

0.01

926

4N

GC

3608

star

4169

.106

475

18.0

5368

425

.544

0.03

224

.902

0.03

124

.719

0.03

990

10N

GC

3608

star

5169

.109

129

18.0

7455

821

.437

0.00

120

.954

0.00

120

.821

0.00

2−

3710

NG

C36

08st

ar6

169

.293

779

18.1

0963

321

.351

0.00

120

.865

0.00

120

.739

0.00

113

97

NG

C36

08st

ar7

169

.243

571

18.1

1506

322

.741

0.00

322

.112

0.00

321

.871

0.00

4−

5917

NG

C36

08st

ar8

169

.251

296

18.1

2911

222

.151

0.00

221

.527

0.00

221

.315

0.00

215

911

NG

C36

08st

ar9

169

.198

996

18.1

4736

921

.484

0.00

120

.985

0.00

120

.849

0.00

287

9N

GC

3608

star

10169

.148

208

18.1

7692

225

.108

0.03

024

.433

0.03

324

.134

0.02

7−

107

16N

GC

3608

star

11169

.389

467

18.2

5084

322

.643

0.00

322

.093

0.00

321

.938

0.00

466

12N

GC

3608

gal1

169.

2959

9218

.0401

9622

.481

0.00

321

.922

0.00

321

.613

0.00

3-

-N

GC

3608

gal2

169.

1905

8318

.0430

6423

.802

0.00

623

.230

0.00

623

.023

0.00

8-

-


Tab

leA

.1(c

ont’

d)

IDR

AD

ecg

δgr

δri

δiV

rad

δV(d

egre

e)(d

egre

e)(m

ag)

(mag

)(m

ag)

(mag

)(m

ag)

(mag

)(k

m/s

)(k

m/s

)(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)(1

0)(1

1)

NG

C36

08ga

l316

9.07

6800

18.0

459

9423

.127

0.00

422

.546

0.00

422

.340

0.00

5-

-N

GC

3608

gal4

169.

2181

2118

.0528

6821

.831

0.00

121

.313

0.00

121

.092

0.00

2-

-N

GC

3608

gal5

169.

1112

2918

.0954

0325

.878

0.04

325

.324

0.05

624

.929

0.05

6-

-N

GC

3608

gal6

169.

1250

5418

.1082

4222

.672

0.00

322

.205

0.00

322

.070

0.00

4-

-N

GC

3608

gal7

169.

2892

6718

.1191

3725

.637

0.02

524

.959

0.03

224

.744

0.04

0-

-N

GC

3608

gal8

169.

1593

5818

.1340

9025

.586

0.02

725

.101

0.03

224

.762

0.03

7-

-N

GC

3608

gal9

169.

1158

5018

.1389

6921

.265

0.00

120

.782

0.00

120

.536

0.00

2-

-N

GC

3608

gal1

016

9.21

9142

18.1

558

5723

.989

0.00

823

.270

0.00

823

.021

0.00

9-

-N

GC

3608

gal1

116

9.24

5833

18.1

488

8922

.166

0.00

221

.581

0.00

221

.258

0.00

2-

-N

GC

3608

gal1

216

9.28

2651

18.1

651

4623

.456

0.00

522

.881

0.00

622

.709

0.00

8-

-N

GC

3608

gal1

316

9.27

3496

18.1

654

1123

.057

0.00

522

.558

0.00

522

.414

0.00

5-

-N

GC

3608

gal1

416

9.19

9783

18.1

737

7525

.439

0.04

124

.884

0.04

224

.507

0.03

8-

-N

GC

3608

gal1

516

9.21

0004

18.0

119

1323

.890

0.00

723

.230

0.00

822

.909

0.00

9-

-

BMass to light ratio estimations

B.1 M/L ratio calculation using Bell et al. (2003)

Relationships between stellar M/L values and various colours in SDSS and 2MASS pass-

bands are given in Bell et al. (2003). They derived these relationships by fitting galaxy

evolution models to a large sample of 22679 galaxies from the SDSS Early Data Release

(Stoughton et al. 2002) and 2MASS extended source catalog (Jarrett et al. 2000). To

estimate the stellar mass for our sample of 42 galaxies, we utilize the relationship between

M/L ratio and (B − V) colour which is given below.

log10(M/L) = −0.628 + (1.305 × (B − V )) (B.1)

We find that the Bell et al. (2003) M/L ratios are about a factor of ∼ 2 times lower

for ellipticals and a factor of ∼ 1.5 times lower for lenticulars than Zepf & Ashman (1993)

values. This affects the X-axes of Figures 18 and 20. Hence, we fit the trends in Figure

18 after incorporating the stellar mass from Bell et al. (2003). The fits are given below

which can be compared to Equations 5.10 – 5.12.

∆[Z/H]BGC = [(0.33 ± 0.07) × log(M?)] − (3.9 ± 0.8) (B.2)

∆[Z/H]RGC = [(0.0007 ± 0.06) × log(M?)] − (0.15 ± 0.9) (B.3)

∆[Z/H]RGC = [(0.07 ± 0.05) × log(M?)] − (0.89 ± 0.75) (B.4)

We find that even if the stellar mass varies between Zepf & Ashman (1993) and Bell et al.

(2003), the relationships shown by blue and red GCs with metallicity remains statistically

the same. This also implies that our results remain unchanged between different M/L

ratio estimations.

149

150 Appendix B. Mass to light ratio estimations

Publications

As part of this thesis, the author has produced the following publications:

• Kartha, S. S., Forbes, D. A., Alabi, A. B., Brodie, J. P., Romanowsky, A. J.,

Strader, J., Spitler, L. R., Jennings, Z. G., Roediger, J. C., The SLUGGS survey:

Exploring the globular cluster systems of the Leo II group and their global relation-

ships, 2016, MNRAS, arXiv:1602.01838

• Kartha, S. S., Forbes, D. A., Spitler, L. R., Romanowsky, A. J., Arnold, J. A.,

Brodie, J. P., The SLUGGS survey: The globular cluster systems of three early-type

galaxies using wide-field imaging, 2014, MNRAS, 437, 273

Other co-author publications are:

• Foster, C., Pastorello, N., Roediger, J., Brodie, J. P., Forbes, D. A., Kartha, S. S.,

Pota, V., Romanowsky, A. J., Spitler, L. R., Strader, J., Usher, C., Arnold, J. A.,

The SLUGGS Survey: stellar kinematics, kinemetry and trends at large radii in 25

early-type galaxies, 2016, MNRAS, 457, 147

• Cortesi, A., Chies-Santos, A. L., Pota, V., Foster, C., Coccato, L., Mendes de

Oliveira, C., Forbes, D. A., Merrifield, M. M., Bamford, S. P., Romanowsky, A.

J., Brodie, J. P., Kartha, S. S., Alabi, A. B., Proctor, R. N., Almeida, A., The

SLUGGS survey: chromo-dynamical modelling of the lenticular galaxy NGC 1023,

2016, MNRAS, 456, 2611

• Pastorello, N., Forbes, D. A., Usher, C., Brodie, J. P., Romanowsky, A. J., Strader,

J., Spitler, L. R., Alabi, A. B., Foster, C., Jennings, Z. G., Kartha, S. S., Pota,

V., The SLUGGS survey: combining stellar and globular cluster metallicities in the

outer regions of early-type galaxies, 2015, MNRAS, 451, 2625

• Cappellari, M., Romanowsky, A. J., Brodie, J. P., Forbes, D. A., Strader, J., Foster,

C., Kartha, S. S., Pastorello, N., Pota, V., Spitler, L. R., Usher, C., Arnold, J.

A., Small Scatter and Nearly Isothermal Mass Profiles to Four Half-light Radii from

Two-dimensional Stellar Dynamics of Early-type Galaxies, 2015, ApJL, 804, 21

• Brodie, J. P., Romanowsky, A. J., Strader, J., Forbes, D. A., Foster, C., Jennings,

Z. G., Pastorello, N., Pota, V., Usher, C., Blom, C., Kader, J., Roediger, J. C.,

Spitler, L. R., Villaume, A., Arnold, J. A., Kartha, S. S., Woodley, K. A., The

151

SAGES Legacy Unifying Globulars and GalaxieS Survey (SLUGGS): Sample Defi-

nition, Methods, and Initial Results, 2014, ApJ, 796, 52

• Arnold, J. A., Romanowsky, A. J., Brodie, J. P., Forbes, D. A., Strader, J., Spitler,

L. R., Foster, C., Blom, C., Kartha, S. S., Pastorello, N., Pota, V., Usher, C.,

Woodley, K. A., The SLUGGS Survey: Wide-field Stellar Kinematics of Early-type

Galaxies, 2014, ApJ, 791, 80

unveiling the globular cluster systems of early-type ... · spectroscopic data from the keck ii...

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