Unveiling the globular cluster systems of early-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
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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,
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 142
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 143
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 144
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 145
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 146
A.1 Catalogue of objects detected around NGC 3607 and NGC 3608 . . . . . . 147
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
4 Chapter 1. Introduction
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-
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
N
0
50
100
1.41.21.0
V-I (mag)0.8
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
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 &
6 Chapter 1. Introduction
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.
8 Chapter 1. Introduction
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-
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/
22 Chapter 2. Galaxy selection and data acquisition
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.
2.4. Observations and reduction techniques 23
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.
24 Chapter 2. Galaxy selection and data acquisition
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
2.4. Observations and reduction techniques 25
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.
26 Chapter 2. Galaxy selection and data acquisition
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.
2.4. Observations and reduction techniques 27
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.
28 Chapter 2. Galaxy selection and data acquisition
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.,
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
32 Chapter 3. Globular cluster systems in three early-type galaxies
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
34 Chapter 3. Globular cluster systems in three early-type galaxies
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.
36 Chapter 3. Globular cluster systems in three early-type galaxies
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)
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
3.3. Analysis of GC systems 37
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.
38 Chapter 3. Globular cluster systems in three early-type galaxies
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.
3.3. Analysis of GC systems 39
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
40 Chapter 3. Globular cluster systems in three early-type galaxies
Fig
ure
3.5
Colo
ur
magn
itude
dia
gra
ms
for
the
selectedG
Ccan
did
atesu
sing
wid
e-field
data.
GC
cand
idates
show
nin
the
Figu
rein
clud
eob
jectsb
righter
than
Mi
=−
7.7
5m
agw
ithin
the
measu
redG
Csy
stemex
tent.
Th
etu
rnover
magn
itud
ein
the
i-filter
isMi
=−
8.2
3m
ag,
show
nas
ad
ash
edlin
ein
allth
reetop
pan
els.T
he
top
leftp
anel
show
sth
eG
Ccan
did
atesof
NG
C720
ob
servedu
sing
Su
baru
/S
uprim
e-Cam
.T
he
open
histogram
isp
lottedin
the
botto
mleft
pan
elrep
resentin
gth
eS
ub
arud
ataw
ithob
jectsd
etectedab
oveth
etu
rnover
magn
itud
e.T
he
shad
edarea
represen
tsth
eestim
atedb
ackgrou
nd
forth
eS
ub
arud
ata.T
he
top
mid
dle
pan
elsh
ows
the
GC
can
did
ates
ofN
GC
1023ob
served
usin
gC
FH
T/M
egaCam
.T
he
botto
mm
idd
lep
anel
disp
lays
the
histo
gra
mof
GC
can
did
ates
from
the
CF
HT
(open
)an
dth
eb
ackgrou
nd
contam
ination
(shad
ed).
Th
esh
ape
ofth
eb
ackgrou
nd
conta
min
atio
nap
pea
rsto
be
simila
rto
the
GC
selectionan
dh
ence
back
groun
dm
aycon
tainm
oreG
Cs.
Th
eto
prigh
tp
anel
show
sth
eG
Cca
nd
idates
of
NG
C2768
usin
gSu
baru
/Su
prim
e-Cam
.T
he
histogram
ofth
eG
Ccan
did
ates(op
en)
forN
GC
2768is
show
nalo
ng
with
the
back
gro
un
d(sh
ad
ed)
inth
ebo
ttom
right
pan
el.
3.3. Analysis of GC systems 41
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)
42 Chapter 3. Globular cluster systems in three early-type galaxies
Fig
ure
3.6
Glo
bu
lar
cluster
lum
inosity
fun
ctionin
ib
and
filter.
Th
eh
istograms
represen
tth
eglob
ular
cluster
lum
inosity
fun
ctionof
the
GC
system
sd
etectedfo
rth
ein
div
idu
algalax
ies.T
he
histogram
son
lyin
clud
eth
eG
Cs
detected
tillth
eG
Csy
stemex
tent
estimated
from
the
rad
ial
surfa
ced
ensity
distrib
ution
s.T
he
dotted
line
atMi
=−
8.23
mag
represen
tsth
etu
rnover
magn
itud
ein
ib
an
dfi
lter(H
arris,
2009a).
3.3. Analysis of GC systems 43
Fig
ure
3.7
Col
our
his
togr
ams
ofG
Cs
afte
rth
eco
rrec
tion
for
bac
kgr
ound
conta
min
atio
n.
Th
ees
tim
ate
db
ack
gro
un
dco
nta
min
ati
on
for
the
resp
ecti
ve
GC
syst
emis
sub
trac
ted
from
the
tota
lG
Cs
and
the
corr
ecte
dG
Cs
are
rep
rese
nte
din
his
togra
ms.
Th
ele
ftp
an
elsh
ows
the
final
GC
sof
NG
C72
0d
etec
ted
usi
ng
Su
bar
u/S
up
rim
e-C
am.
Th
eh
isto
gram
show
sa
clea
rb
imod
al
colo
ur
dis
trib
uti
on
for
NG
C72
0.T
he
mid
dle
pan
elsh
ows
the
GC
sof
NG
C10
23ob
serv
edu
sin
gH
ST
/WF
PC
2(s
had
edare
a)
an
dC
FH
T/M
egaC
am
(op
enar
ea)
dat
a.T
he
righ
tp
anel
show
sth
eG
Cs
ofN
GC
2768
usi
ng
HS
T/A
CS
(sh
ad
edare
a)
an
dS
ub
aru
/S
upri
me-
Cam
(op
enar
ea).
The
bac
kgr
oun
dsu
btr
acti
onhas
imp
rove
dth
eco
lou
rh
isto
gram
ssh
own
inF
igu
re3.5
an
dn
owth
ep
eaks
for
the
blu
ean
dre
dsu
bp
opu
lati
ons
are
mor
ed
isti
nct
lyse
en.
44 Chapter 3. Globular cluster systems in three early-type galaxies
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
3.3. Analysis of GC systems 45
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]
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
46 Chapter 3. Globular cluster systems in three early-type galaxies
Fig
ure
3.8
Tw
od
imen
sion
alsk
yim
ages
of
three
galaxies:
NG
C720,
NG
C1023
and
NG
C2768.
Th
egalax
ystellar
light
issu
btracted
from
the
ind
ivid
ual
images
with
North
up
an
dE
aston
the
left.E
achgalax
yim
agecov
ersan
areaof
10,6.3
and
10arcm
in2
centered
on
the
gala
xy,
respectively,
for
NG
C720,
NG
C1023
and
NG
C2768.
Th
eb
lue
and
redop
encircles
represen
tth
ep
ositions
ofth
eb
lue
an
dred
GC
can
did
ates
detected
fromth
egrou
nd
based
telescopes,
wh
ereasth
eb
lue
and
redop
ensq
uares
represen
tth
ep
ositio
ns
of
the
blu
ean
dred
GC
can
did
ates
detected
fromth
eH
ST
.W
en
oticeth
atth
eG
Cs
ofN
GC
720are
closelyalign
edalon
gth
ep
ositio
nan
gle
of
the
gala
xy
stellar
light.
3.3. Analysis of GC systems 47
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.
48 Chapter 3. Globular cluster systems in three early-type galaxies
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-
3.3. Analysis of GC systems 49
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.
50 Chapter 3. Globular cluster systems in three early-type galaxies
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.
3.3. Analysis of GC systems 51
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.
52 Chapter 3. Globular cluster systems in three early-type galaxies
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. Analysis of GC systems 53
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
54 Chapter 3. Globular cluster systems in three early-type galaxies
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
3.3. Analysis of GC systems 55
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
56 Chapter 3. Globular cluster systems in three early-type galaxies
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
3.3. Analysis of GC systems 57
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
Galaxy Stars 87±5 0.58±0.05GCs Total 89±7 0.35±0.09GCs Blue 110±32 0.15±0.15GCs Red 84±6 0.57±0.08
NGC 2768
Galaxy Stars 93±3 0.60±0.03GCs Total 89±2 0.59±0.03GCs Blue 90±3 0.57±0.04GCs Red 87±3 0.60±0.05
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
58 Chapter 3. Globular cluster systems in three early-type galaxies
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.
60 Chapter 3. Globular cluster systems in three early-type galaxies
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
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.
68 Chapter 4. Globular cluster systems of the Leo II group
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
4.3. Defining the GC systems of each galaxy 69
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.
70 Chapter 4. Globular cluster systems of the Leo II group
−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).
4.3. Defining the GC systems of each galaxy 71
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.
72 Chapter 4. Globular cluster systems of the Leo II group
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
74 Chapter 4. Globular cluster systems of the Leo II group
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
4.4. Analysis of photometric data 75
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)
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
76 Chapter 4. Globular cluster systems of the Leo II group
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.
4.4. Analysis of photometric data 77
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.
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,
78 Chapter 4. Globular cluster systems of the Leo II group
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.
4.4. Analysis of photometric data 79
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.
80 Chapter 4. Globular cluster systems of the Leo II group
Fig
ure
4.8
Azim
uth
al
distrib
utio
nfo
rth
eG
Csy
stemof
NG
C3607.
Th
eb
lack,
blu
ean
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histogram
srep
resent
the
azimu
thal
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utio
nof
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lp
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and
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ashed
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ased
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atio
n4.3
.T
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ashed
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Cs
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els.
4.4. Analysis of photometric data 81
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.
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)
82 Chapter 4. Globular cluster systems of the Leo II group
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.
4.4. Analysis of photometric data 83
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
84 Chapter 4. Globular cluster systems of the Leo II group
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.
4.4. Analysis of photometric data 85
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.
86 Chapter 4. Globular cluster systems of the Leo II group
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)
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.
4.4. Analysis of photometric data 87
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
88 Chapter 4. Globular cluster systems of the Leo II group
Fig
ure
4.1
3A
zimu
thal
distrib
utio
nfo
rth
eG
Csy
stemof
NG
C3608.
Th
ecolou
rsan
dsty
lesof
histogram
san
dlin
esare
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assh
own
inF
igu
re4.8
.T
he
leftp
an
elsh
ows
the
distrib
ution
ofG
Cs
selectedfrom
the
SB
meth
od
and
the
right
pan
elsh
ows
the
distrib
utio
nfro
mth
eM
Am
ethod
.T
he
gala
xy
stellarligh
tis
aligned
along
the
major
axis
(82d
egrees),rep
resented
by
the
verticald
ash
edlin
e.T
he
tota
lG
Csy
steman
db
oth
the
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pop
ulation
sare
arranged
along
ad
ifferen
tp
ositionan
gle(∼
100d
egrees)th
anth
egala
xy
stellar
light
inth
eS
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ethod
.T
he
right
pan
elsh
ows
the
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ution
ofG
Cs
selectedfrom
the
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od
.T
he
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Csy
steman
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oth
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tion
sare
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ata
position
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egreesin
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od
,sligh
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fromth
egala
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Also
inb
oth
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els,a
scarcityof
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salon
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ym
ajor
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isvisib
le.
4.5. Results and discussion 89
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
90 Chapter 4. Globular cluster systems of the Leo II group
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.
4.5. Results and discussion 91
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)
92 Chapter 4. Globular cluster systems of the Leo II group
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).
94 Chapter 4. Globular cluster systems of the Leo II group
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
98 Chapter 5. Global properties of GC systems
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).
5.2. Global relations of GC systems 99
GC systems.
The best fitted linear and second order polynomial (not shown in the Figure 5.1) are:
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
104 Chapter 5. Global properties of GC systems
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.
5.2. Global relations of GC systems 105
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:
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.
106 Chapter 5. Global properties of GC systems
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.
5.2. Global relations of GC systems 107
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)
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
5.2. Global relations of GC systems 109
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).
110 Chapter 5. Global properties of GC systems
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
5.2. Global relations of GC systems 111
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
112 Chapter 5. Global properties of GC systems
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.
5.2. Global relations of GC systems 113
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.
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
114 Chapter 5. Global properties of GC systems
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.
5.2. Global relations of GC systems 115
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
116 Chapter 5. Global properties of GC systems
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.
5.2. Global relations of GC systems 117
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
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.
118 Chapter 5. Global properties of GC systems
(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.
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
5.2. Global relations of GC systems 119
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.
120 Chapter 5. Global properties of GC systems
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