Globular Cluster Systems of Relic Galaxies

MNRAS 000,1–11 (2019) Preprint 22 February 2021 Compiled using MNRAS LATEX style ﬁle v3.0

Karla A. Alamo-Mart´ınez,1,2? Ana L. Chies-Santos,1 Michael A. Beasley,3 Rodrigo Flores-Freitas,1 Cristina Furlanetto,4 Marina Trevisan,1 Allan Schnorr-Muller,¨ 1 Ryan Leaman,5 Charles J. Bonatto1 1Departamento de Astronomia, Instituto de F´ısica, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, R.S, Brazil 2Departamento de Astronom´ıa, Universidad de Guanajuato, Apartado Postal 144, 36000, Guanajuato, Guanajuato, Mexico 3Instituto de Astrof´ısica de Canarias, Calle V´ıaL´actea, La Laguna, Spain 4Departamento de F´ısica, Instituto de F´ısica, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, R.S, Brazil 5Max-Planck Institut fur¨ Astronomie, K¨onigstuhl 17, D-69117 Heidelberg, Germany

Accepted 2021 February 18. Received 2021 February 17; in original form 2020 December 8

ABSTRACT We analyse the globular cluster (GC) systems of a sample of 15 massive, compact early-type galaxies (ETGs), 13 of which have already been identified as good relic galaxy candidates on the basis of their compact morphologies, old stellar populations and stellar kinematics. These relic galaxy candidates are likely the nearby counterparts of high redshift red nugget galaxies. Using F814W (≈ I) and F160W (≈ H) data from the WFC3 camara onboard the Hubble Space Telescope we determine the total number, luminosity function, specific frequency, colour and spatial distribution of the GC systems. We find lower specific frequencies (S N < 2.5 with a median of S N = 1) than ETGs of comparable mass. This is consistent with a scenario of rapid, early dissipative formation, with relatively low levels of accretion of low-mass, high-S N satellites. The GC half-number radii are compact, but follow the relations found in normal ETGs. We identify an anticorrelation between the specific angular momentum (λR) of the host galaxy and the (I-H) colour distribution width of their GC systems. Assuming that λR provides a measure of the degree of dissipation in massive ETGs, we suggest that the (I-H) colour distribution width can be used as a proxy for the degree of complexity of the accretion histories in these systems. Key words: galaxies: star clusters: general – galaxies: evolution – galaxies: formation

1 INTRODUCTION Oser et al. 2010, Hill et al. 2017). In the first phase, an in situ component is formed through dissipational processes, cre- Massive early-type galaxies (ETGs) are host to some the most ating a massive and compact central component. This first extreme formation events, and are the end products of com- phase happens rapidly (< 1 Gyr) and early (at z & 2)(Zolotov plex processes such as gas accretion, in-situ star formation, et al. 2015), and gives rise to a population of passively evolv- hierarchical merging, tidal interactions, and secular evolution ing objects seen at high redshift (Daddi et al. 2005, Schreiber (Trager et al. 2000, Thomas et al. 2005, La Barbera et al. et al. 2018, Valentino et al. 2020), sometimes termed “red 2013, Salvador-Rusiñol et al. 2020). ETGs experience dra- nuggets” (Damjanov et al. 2009). A second phase, dominated matic size evolution over cosmic history (e.g. Trujillo et al. by minor mergers, then builds-up predominantly the outer 2006, Buitrago et al. 2008, van Dokkum et al. 2010), have regions of ETGs (Naab et al. 2009, Johansson et al. 2009). arXiv:2012.04783v2 [astro-ph.GA] 18 Feb 2021 the most extreme initial mass functions (i.e. weighted to low- This process grows massive galaxies in size and mass, and mass stars, van Dokkum & Conroy 2010, La Barbera et al. presumably lowers their central densities (Hilz et al. 2012, 2013) and host the most massive black-holes in the Universe Hilz et al. 2013). Simulations suggest that the second phase (Ferrarese & Merritt 2000, McConnell & Ma 2013). The rich may initially begin concurrently with the first, but continues variety of mechanisms that shape ETGs together with the to operate until the present day (e.g., Wellons et al. 2015, fact that these galaxies contain ∼70% of the total stellar bud- Furlong et al. 2017. For the purposes of this paper, we refer get in the local Universe (Fukugita et al. 1998), turn these to an ”accretion event” as any merger that has occurred at galaxies into attractive laboratories to test galaxy formation z < 2. theories. A consequence of this formation pathway is that a small There is theoretical and observational evidence that mas- 11 fraction of these red nuggets are expected to survive “frozen” sive ETGs (M∗ > 10 M ) in the local Universe have gone until the present-day Universe (Trujillo et al. 2009, Poggianti through two major formation phases (eg. Hopkins et al. 2009, et al. 2013, Spiniello et al. 2020) . These objects are thus considered relics of the first phase of ETG formation. In fact, ? E-mail: [email protected] such relic candidates have been reported to exist relatively

© 2019 The Authors 2 Alamo-Mart´ınezet al. nearby (Yıldırım et al. 2017, Ferré-Mateu et al. 2017, 2018). 50–90% of their stars, with the rest comprising of an in-situ As relic galaxies, they are expected to have uniformly old component (Oser et al. 2010; Navarro-González et al. 2013). stellar populations (> 10 Gyr, Yıldırım et al. 2017), and be Here, we present the first systematic study of GC popula- extremely compact, as is the case for the prototypical relic tions in relic candidate galaxies. This paper is structured as galaxy NGC 1277 (Trujillo et al. 2014) and also Mrk 1216 and follows. In Section 2 we introduce the data, photometric anal- PGC 032873 (Ferré-Mateu et al. 2017). In addition, stellar ysis and GC candidates selection. In Section 3 we analyse the population studies indicate that relics such as NGC 1277 have spatial distribution, luminosity function and total number of extremely bottom-heavy stellar initial mass functions (IMF) the GC systems. In Section 4 we look for correlations be- which do not vary with radius. This is consistent with the tween the determined GC system properties and host galaxy picture that this class of objects generally go on to form the properties from the literature, such as, stellar mass, specific central regions of massive ETGs (Mart´ın-Navarro et al. 2015). angular momentum, stellar velocity dispersion and metallic- Having accreted very few satelites, one might expect that relic ity. In Section 5 we discuss and summarise the results. galaxies would be found preferentially in relative isolation. However, a handful of relic candidates (Yıldırım et al. 2017, ) are found in the Perseus cluster. This result finds support in 2 DATA the work of Poggianti et al.(2013) and Peralta de Arriba et al. (2016) who find massive compact galaxies are preferentially In this work we analyze a sample of 15 massive, compact found in central regions of the most dense environments. This early-type galaxies identified in the Hobby-Eberly telescope may suggest that the conditions in early proto clusters may Massive Galaxy Survey (HetMGS; van den Bosch et al. have been especially favourable to preserve these systems. In 2015). Table1 contains basic properties of our sample galax- the particular case of NGC 1277 in Perseus, it is possible ies. These galaxies were initially selected in order to resolve −2 that its proximity to NGC 1275 (Perseus A), has allowed their black hole “sphere of influence”, ri ≡ GMσ , where M is NGC 1277 to evolve with little accretion. NGC 1275 may the black hole mass and σ is host galaxy velocity dispersion. have acted (and continues to act) as a main attractor for any Such a selection yields a strong bias in favour of massive, com- circumgalactic material. pact and high velocity dispersion systems. Of the 15 HetMGS Identification and characterization of relic galaxies is cru- galaxies considered here, 13 have been identified as good relic cial to test the two-phase model, and offers the opportunity to galaxy candidates on the basis of their compact morpholo- study red nugget galaxies in the nearby Universe. In addition gies, old stellar populations and stellar kinematics (Yıldırım to the chemo-dynamical study of galaxy stellar populations, et al. 2017; Ferré-Mateu et al. 2017). Their properties are very globular clusters (GCs) have proven to be uniquely powerful similar, though not as extreme, as the relic galaxy archetype tools to trace the structure and history of galaxies (Brodie & NGC 1277 (Trujillo et al. 2014, Mart´ın-Navarro et al. 2015, Strader 2006, Pfeffer et al. 2018, Beasley 2020). Beasley et al. 2018 ). We use archival Hubble Space Telescope (HST) data from GC systems are generally thought to be old (most of them the programme GO: 13050 (PI: van den Bosch). The observa- with ages > 10 Gyr, Strader et al. 2005, Chies-Santos et al. tions were taken with the WFC3 camera with the detectors 2011), and contain the imprints of the initial conditions of UVIS (FOV 162×162 arcsec) and IR (FOV 123×136 arcsec) galaxy formation. GC systems of ETGs in the local Uni- through filters F814W (≈ I) and F160W (≈ H), respectively. verse generally show complex colour distributions. Because The data is homogeneous and all the targets have total inte- GCs are generally old and co-eval, differences in color are gration time of 500 s for I and 1400 s for H. We downloaded attributed to differences in metallicity, such that metal-poor the data from The Hubble Legacy Archive1 which offers re- GCs have “blue” colours and metal-rich GCs are “red”. This duced data from HST following the standard procedure. correspondence has been confirmed with spectroscopy (e.g., The FWHM for I and H are 0.1 and 0.22 arcsec, respec- Beasley et al. 2008, Caldwell et al. 2011, Usher et al. 2012). tively. We use the AB photometric system, with zero-points Furthermore, the fraction of red GCs decreases as we move in I and H, zpI=25.12 and zpH=25.95 mag, respectively. to lower galaxy luminosities, reaching the extreme faint of The Galactic extinction toward each galaxy in both bands dwarfs that have predominantly blue GCs (e.g. Peng et al. are from Schlafly & Finkbeiner(2011). For consistency with 2006). This is explained by invoking the mass-metallicity re- Yıldırım et al.(2017), we adopt a cosmology with a Hub- lation where the metal-poor GCs are formed in low mass −1 −1 ble constant of H0 = 70.5km s Mpc , a matter density of galaxies, while the metal-rich GCs are formed in more mas- ΩM = 0.27, and dark energy density of ΩΛ = 0.73. sive proto-galaxies (Côtéet al. 1998; Strader et al. 2005). In the two-phase galaxy formation context, the red metal-rich GCs are thought formed predominantly in-situ, while an im- 2.1 Photometry portant fraction of blue, metal-poor GCs are accreted from In order to detect sources close to the centre of the galaxies, dwarf galaxies. first we need to subtract the galaxy light. This is because Recently, Beasley et al.(2018) found that NGC 1277 con- the steepness of the galaxy luminosity is reflected as dras- tains almost exclusively red GCs suggesting that the galaxy tic changes in the background, hampering the detection of has largely bypassed the second-phase of massive ETG for- sources. To create the galaxy model we use the tasks el- mation, where ETG assembly should be dominated by minor lipse and bmodel from IRAF (Tody 1986) and fit ellipti- merging events which would have brought in blue metal-poor cal isophotes to the surface brightness of the galaxies. For GCs. The GC results for NGC 1277 suggest an accreted mass fraction of ∼ 12% in this galaxy. By contrast, massive ETGs are generally estimated to have accreted somewhere between 1 https://hla.stsci.edu/

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 3 such procedure, we mask all the sources detected (except the galaxy to be ﬁtted) using the SEGMENTATION MAP from a ﬁrst SExtractor (Bertin & Arnouts 1996) run. We then create models for both I and H bands and subtract them from 10 1

the original images. ] When inspecting the subtracted images, we notice signif- 2 1Re 2Re c

icant residuals in the central regions of most of the sample e galaxies, this is mainly because of dust (disks or lanes) or s c complex structures like rings. Another manuscript is being r drafted with an in-depth structural analysis of this sample of a / galaxies (Flores-Freitas, in prep). # [ We perform source extraction on the galaxy subtracted Re, GCS =5.8 kpc image, by running SExtractor independently for each band C G n = 0.5 with a set of parameters optimized for point source detec- 10 2 GCS tion. We use a background grid size BACK SIZE=32 pix and FILTERSIZE=3, and an effective σ detection larger than 5 for both bands. Then, we apply a first cut to select objects with good quality in photometry by rejecting objects with 101 102 saturated pixels, truncated by being close to the edges of the R [arcsec] image, or, with magnitude error larger than 0.2 mag. More- over, we estimate the concentration parameter C4−10, which Figure 1. Surface number density of the GC candidates as func- is the difference in magnitude within an aperture of 4 and 10 tion of radius for the galaxy NGC 1270. The error bars represent pixels in diameter, as it seems to be a better indicator of the the poissonian error for the number of counts and weighted by the luminosity profile for the faintest objects in comparison to effective area of each annulus. The solid line shows the best Sér- sic fit. The blue shaded region shows the inner population which the SExtractor CLASS STAR parameter (Peng et al. 2011, contains mostly GCs with high certainty, while the yellow shaded Cho et al. 2016). region shows the outer population which might be strongly affected by contaminants. 2.2 Globular Cluster Candidates Selection We use SExtractor output MAG AUTO as the actual magni- function (Fleming et al. 1995) to the ratio of recovered to tude of the objects, but to estimate the color we use aperture created artificial stars for the I band, as it is the band with photometry within a radius of 4 pixels (0.1600) and apply reliable parameters available for GC populations (Peng et al. the respective aperture correction. The aperture correction 2011, Cho et al. 2016). As the observing strategy is the same is estimated by constructing the curve of growth for multi- for all the galaxies, the recovered parameters are similar but ple point sources, measuring the magnitude within different not exactly the same as the detection limit is affected by the apertures (radius of 2,4,5,8,11,14,16 pixels) until it reaches a brightness of the galaxy. The magnitude in the I-band where constant value, representing the total magnitude. Since our 50% of the artificial stars are recovered is in the range of 25.1 target galaxies are located at different distances, a fixed aper- and 25.5, and with slopes in the range 3-5 for all the sample. ture corresponds to a different physical size at the source distance. In Table1 we present the aperture corrections for each galaxy in the I and H bands. Finally, the sample of 3 ANALYSIS point sources that are taken as GC candidates are the ones detected independently in both bands (matching the coordi- 3.1 Spatial Distribution of Globular Cluster Candidates nates within a radius < 1 arcsec). Also, the GC candidates In order to estimate the amount of contaminants by Milky must have magnitudes according to the expected luminosity Way stars and background galaxies, and to quantify the spa- function of GCs (see Section 3.2 for more details), and color tial incompleteness, we parametrise the spatial distribution of -0.5 < I − H < 1.5 which is the expected color for GCs (Cho the GC candidates by determining the surface number den- et al. 2016). sity of the GC candidates as function of radius. We measure In order to have an accurate estimation of the GCs mag- the number of GC candidates inside circular concentric an- nitude distribution and the total number of GCs for each nuli with a constant width of 16 arcsec each, and normalise galaxy, we need to determine the detection completeness it by the effective area. We then fit a single Sérsic function curve as function of magnitude. To estimate the complete- (Sersic 1968) including a background component: ness curve we construct the point-spread function (PSF) using the Tiny Tim 2 web interface. We add 20,000 artificial     !1/nGCS  stars with a range in magnitude between 22 and 27 in both   r  ΣGC(r) = Σ0 exp−bn  − 1 + BGps (1) bands, and color I − H = 0. We mimic the source detection as   Re,GCS  in the original images by applying the same source detection criteria in each band independently, and then select the ones where Re,GCS is the radius that contains half of the GC pop- that match in coordinates. We proceed by fitting a Pritchet ulation; Σ0 is the surface number density at Re,GCS; nGCS is the Sérsic index; and BGps is the surface number density of background point sources. The fit is performed leaving all the 2 http://tinytim.stsci.edu/cgi-bin/tinytimweb.cgi parameters free but constraining nGCS to be between 0.5 and

MNRAS 000,1–11 (2019) 4 Alamo-Mart´ınezet al.

Table 1. Galaxy sample parameters: (1) Galaxy name. (2) Distance. (3) Environment estimate - galaxy number density (ρ) within the volume containing the two closest neighbours. (4) Environment according to NED. (5) Integrated Magnitude in the V-band. (6) Reddening. (7,8) Aperture corrections in the I and H bands.

3 Galaxy D [Mpc] ρ [#/Mpc ]E MV,GAL AV ap c I ap c H (1) (2) (3) (4) (5) (6) (7) (8)

NGC 0384 59 0.08 pair/group -21.17 0.17 -0.18 -0.27 NGC 0472 74 3.17 - -21.61 0.13 -0.15 -0.20 MRK 1216 94 0.11 - -22.12 0.09 -0.18 -0.19 NGC 1270 69 7.76 group/cluster Abell 426* -21.85 0.45 -0.16 -0.19 NGC 1271 80 7.32 group/cluster Abell 426 -22.04 0.45 -0.16 -0.18 NGC 1281 60 1.64 group/cluster Abell 426 -21.26 0.46 -0.17 -0.17 NGC 1282 31 0.35 group/cluster Abell 426 -20.32 0.46 -0.18 -0.20 UGC 2698 89 0.83 - -22.36 0.40 -0.17 -0.18 NGC 2767 74 0.96 group -21.06 0.05 -0.20 -0.21 UGC 3816 51 0.27 group -21.66 0.17 -0.33 -0.24 NGC 3990 15 1.37 pair/group -18.95 0.05 -0.19 -0.25 PGC 11179 94 4.86 group/cluster Abell 400 -21.70 0.51 -0.17 -0.24 PGC 12562 67 1.94 group/cluster Abell 426 -20.95 0.46 -0.18 -0.30 PGC 32873 112 0.43 pair -22.12 0.04 -0.31 -0.23 PGC 70520 72 0.01 - -21.75 0.26 -0.16 -0.19

* Perseus cluster

4, as are the expected values for disky and spheroidal galax- vary among bands (Kundu & Whitmore 2001) where for the GCLF ies (Kormendy et al. 2009), and Re,GCS to be larger than the most massive galaxies is σV ≈ 1.4. effective radius of the galaxy (Re,GAL) as the physical exten- We adopt a GCLF turnover and width (AB system) de- sion of the GC system is generally more extended than that pendent on the galaxy luminosity MV,GAL with the form: of the starlight (Rhode et al. 2007; Kartha et al. 2014). The error bars are estimated assuming a poissonian error for the 0 number of counts and weighted by the effective area. As an MI = −7.4 + 0.04(MV,GAL + 21.3) − 1.04 + 0.436 (2) example, in Figure1 we show the GC surface number density for the galaxy NGC 1270, and its best Sérsic fit. For all the GCLF galaxies we obtained Re,GCS between 2 and 3 times Re,GAL, σI = 1.2 − 0.1(MV,GAL + 21.3) (3) in agreement with the literature (Kartha et al. 2014; Forbes 2017; Hudson & Robison 2018). In Table2 we present the following (Jordán et al. 2006b, Villegas et al. 2010 and Harris 0 measured Re,GCS values. et al. 2013) on the dependency of MV as function of the 0 0 From inspection of the Sersic fits, we define two subsam- galaxy luminosity, and assuming MV − MI = 1.04 which is ples: an inner population (sources within 1Re,GCS, blue shaded a mean value measured for 28 ETGs according to Kundu & region in Fig.1), whose sources with high certainty are dom- Whitmore 2001, and finally to convert from Johnson-Cousins inated by GCs, and an outer population (sources out of to AB photometric system we add 0.436 (Sirianni et al. 2005). 2Re,GCS, yellow shaded region in Fig.1), which might be heav- Using this transformation, for a massive galaxy with 0 ily contaminated by Milky Way stars and background galax- MV,GAL ∼ −24 (as it is for M87) we recover MI = −8.112 in ies. These subsamples are defined so that the inner subsample agreement with Jordán et al.(2007b). On the other hand, for 0 is well above the level of background contaminants. dwarf galaxies with MV,GAL ∼ −18, we recover MI = −7.872 in agreement with Miller & Lotz(2007). As mentioned in Section 2.2, we selected point sources GCLF 0 fainter that 3σI from MI , together with a selection by color -0.5 < I − H < 1.5 (Cho et al. 2016), in order to re- 3.2 Luminosity Function and total GC number duce the contamination by Milky Way stars and background The globular cluster luminosity function (GCLF) is a prop- galaxies. erty that has been extensively studied among galaxies with To derive the GCLF of our studied galaxies, we estimate different morphological type, mass and environment, being the luminosity function for the inner and outer subpopula- well described by a Gaussian (Harris 1991), albeit some de- tions. This ultimately allows us to create an inner GCLF partures form gaussianity in the faint end (Jordán et al. clean from contaminants. The luminosity function of the 2007a), not relevant for this study. The peak or also called outer region (dominated by contaminants) is normalized to turnover (M0) and width (σGCLF) of the GCLF are known the area of the inner region, representing the luminosity func- to depend on the luminosity of the galaxy, where brighter tion of contaminants. Then, our final GCLF for each galaxy is turnover and broader distributions are observed in brighter the luminosity function of the inner population minus the lu- galaxies (Kundu & Whitmore 2001; Jordán et al. 2006a). For minosity function of contaminants within 1Re,GCS, multiplied 0 0 ETGs the values are MV ≈ −7.4 and MI ≈ −8.5 in Johnson- by two, as within 1Re we have half of the total population. Cousins photometric system. On the other hand, although As the GCLF that we recover is the convolution of the in- σGCLF varies with the luminosity of the galaxy, it does not trinsic GCLF and the incompleteness Pritchet function (de-

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 5

30 inner 25 outer 25

20 20

N 15

N 15 10 10 5 5 0 21 22 23 24 25 26 27 0 0.5 0.0 0.5 1.0 1.5 50 I H 40 Figure 3. GC candidates color I −H distributions for the population

N within 1R (solid blue), outside 2R (dashed yellow), and 30 e,GCS e,GCS from 0 to 2Re,GCS (solid gray), for the galaxy NGC 1270. 20 4 RESULTS 10 In this section we explore different correlations between the GC System (GCS) and host galaxy parameters derived in this 21 22 23 24 25 26 27 work and from the literature. I [mag] 4.1 GCs Color (I − H) correlations Figure 2. GC luminosity functions for galaxy NGC 1270. Top panel: Luminosity function for the inner and outer subpopulations. Bot- The colours of the GC populations contain significant tom panel: Luminosity function of the inner population minus the amounts of embedded information. They give us insights into luminosity function of contaminants within 1Re,GCS(corrected by ages and metallicities of the GCs (Brodie & Strader 2006), area), multiplied by two, as within 1Re we have half of the to- key parameters to infer the star-formation history of the host tal population. The dotted line shows the best Gaussian*Pritchet galaxy. Spectroscopic analyses indicate that most GCs are function, the solid line is the corresponding single Gaussian, and, old and co-eval (Cohen et al. 2003; Puzia et al. 2005; Beasley the gray dashed vertical line indicates the bright cut for selected et al. 2008; Caldwell et al. 2011), implying that color differ- sources (M 0-3σ GCLF). I I ences are mainly due to differences in metallicity. Unlike the relative homogeneity of the GCLF shape, the color distribution of GCs shows more variety among different galaxies. In optical colors, more massive galaxies exhibit more complex GC color distributions (dominated by bimodal distributions with different blue-to-red fractions, see Lee, Chung & Yoon termined in Sect 2.2), in order to obtain the total number 2019) and turn gradually unimodal with a blue dominant of GCs, we estimate the area under the expected Gaussian population as the mass of the galaxy decreases (Peng et al. GCLF by fitting the product of a Gaussian and the Pritchet 2006). GCLF 0 function, with the expected σI and MI . In Figure2 we Even though the optical colors of GC systems have been show the luminosity functions for the inner and outer subpop- extensively studied, their interpretation is still debated. Here, ulations (top panel), as well as the GCLF (bottom panel) in we do not attempt to study in detail the nature or the exis- the I-band. We also show the best Gaussian*Pritchet func- tence of bimodality of the near-IR color distribution of GCs tion (dotted curve), and the corresponding single Gaussian (for that, see Blakeslee et al. 2012, Chies-Santos et al. 2012, (solid curve) for the galaxy NGC 1270. Cho et al. 2016) mainly because we are not sampling the Although the data is relatively deep, it is not enough to entire population of GCs in any of the bands. Instead, we sample the whole range of the GCLF, the faint limit we perform a rough characterization of the I − H color distri- 0 reach is about ∼1 mag brighter than MI (depending on the bution of our sample by estimating the mean, the standard distance to the galaxy). In Table2 we show the total number deviation, and the skewness of the GC candidates for each of GCs corrected by incompleteness in area and photometry, galaxy. The rationale here is that even such simple metrics and the corresponding error propagating the uncertainty in can encode useful information about the GC systems and the fitted Gaussian amplitude. their host galaxies. In order to avoid outliers, we calculate the mean and standard deviation within interquartiles 1 and

MNRAS 000,1–11 (2019) 6 Alamo-Mart´ınezet al.

H 0.8 H 0.20

I 0.7 I n 0.15 d a

0.6 t e s m 0.5 S 0.10 C S C 0.4 G

G 0.05

0.2 0.0 0.2 0.4 10 11 12 0.2 0.3 0.4 0.5 Metallicity (Y17) log10 (M ) [M ] R (Y17)

Figure 4. Mean and standard deviation of I − H distributions within interquartiles 1 and 3 for all the GC candidate sources (i.e. without background contamination subtraction) within 2Re,GCS. Metallicity, M? and λR are from Yıldırım et al.(2017). The bottom right shows the typical error bars. The dots are the galaxies classiﬁed as relics and the diamonds as non-relics by Yıldırım et al.(2017). The arrow indicates the direction at which the “degree of relicness” of a given GC system increases (see text for details).

3 for all the GC candidate sources (i.e. without background

4 contamination subtraction), for the inner (within 1Re,GCS), 0 ×1 3.5 outer outside 2Re,GCS, and from 0 to 2Re,GCS. 1.5 =

5 1.0 0 ) ×1 5.5 N =

It is well known that the mean metallicity of a galaxy and S

( 0.5 5 0 0 its GCs increases for more massive galaxies (Kundu & Whit- 1 ×1 1.0 g 0.0 =

more 2001; Usher et al. 2012 – and see the compilation in o l Beasley et al. 2019); together with the fact that the fraction 0.5 of red GCs increases for brighter galaxies (Peng et al. 2006), we expect redder GCS colors for brighter galaxies. However, 1.0 for a single galaxy, inner GCs have higher metallicities than 24 22 20 18 16 14 the outer ones (Geisler, Lee & Kim 1996; Harris 2009), thus, MV in order to avoid a bias for selecting only the inner GCs, the 1.0 GC color of our sample is determined using the population 0.5 from 0 to 2Re,GCS where we have ∼90% of the detected GC candidates. In Figure3 we show the color I − H distribution 0.0 ) for galaxy NGC 1270, plotting the inner, outer and from 0 to M

S 0.5 2R subpopulations. ( e,GCS 0 1 1.0 g o l 1.5 The skewness values reflect moderately skewed I − H color distributions for five galaxies, while for the rest of the sam- 2.0 ple galaxies, the color distributions seem symmetrical (see 2.5 Table2). In Figure4 we plot the mean I − H GCS color ver- 12 11 10 9 8 log (M /M ) sus galaxy metallicity and galaxy stellar mass (M?) obtained 10 dyn from Yıldırım et al.(2017) where we can see a trend that more massive and metal-rich galaxies have GCs with on average Figure 5. Upper panel: The specific frequency S N as function of MV redder mean I − H colours, mimicking the effect of the GC with magenta squares representing our sample galaxies classified peak metallicity, galaxy luminosity relation (see eg. Brodie & as relics and the diamonds as non-relics by Yıldırım et al.(2017), Strader 2006). We also explore any dependence of the stan- the gray dots are galaxies from literature (Harris et al. 2013), and dard deviation of the I − H GC color with galaxy properties, the blue star is the galaxy NGC 1277 from Beasley et al.(2018). identifying an interesting possible correlation when plotting it The dashed cyan lines represent predictions from Georgiev et al. (2010) assuming fixed GC formation efficiency η per total halo mass versus the stellar angular momentum, λR, from Yıldırım et al. MHalo. Bottom panel: The specific mass S M versus dynamical mass (2017). We can see tantalizing evidence for an anti-correlation as derived from Eq.6 (see text). between λR and I − H color standard deviation. This trend may be explained in a hierarchical scenario where successive . merging events decrease λR (Rodriguez-Gomez et al. 2017) while the final merged system in turn will tend to have a more complex, wider GC color distribution. In this sense, 4.2 GC total number correlations the right hand panel of Figure4 may show a progression of the “degree of relicness” of a system, where the least evolved One of the first parameters defined to quantify the richness of (most relic-like) systems will be located to the right of the a GC population is the called specific frequency, S N (Harris plot with higher λR and a narrower colour width. & van den Bergh 1981), which is the number of GCs per unit

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 7 galaxy luminosity, normalised to a galaxy with absolute V and then Mbaryonic ∼M?, valid for our sample of early-type magnitude of -15: galaxies. As we know the total number of GCs, we just have to multiply by the mean GC mass, hMGCi. As mentioned in Section 3.2, the mean and standard deviation of the GCLF 0.4(MV,GAL+15) S N = 10 . (4) depend on the luminosity of the galaxy, being brighter and Harris & van den Bergh(1981) found values in the range broader as the galaxy luminosity increases. This is reflected in larger hM i for more luminous galaxies. By using the re- 2< S N <10 for elliptical galaxies, noticing that the number of GC 0 GCs do not scale with the luminosity of the galaxy. Since lation MV = −7.4 + 0.04(MV,GAL + 21.3) and (M/L)V = 2 from Harris et al.(2013), we derive hM i. To estimate the dy- then, the S N has been extensively studied among galaxies GC with different masses, morphological types and environments namical mass, we use: (Harris & Harris 2001; Peng et al. 2008; Georgiev et al. 2010, 2 Harris et al. 2013 Alamo-Mart´ınez & Blakeslee 2017), where 4R , σ M = e GAL e (6) the behaviour of S N as function of MV,GAL can be described dyn G by an U-shape, where S N increases with luminosity on the bright side, and increases as the luminosity decreases on the where Re,GAL is the effective radius of the galaxy, and σe is the ? stellar velocity dispersion within Re,GAL, both obtained from faint side with a minimum of S N ∼ 1 for galaxies around LV , and large scatter on the edges. Yıldırım et al.(2017). In Figure5 (bottom) we show S M vs. M for our sample and Harris et al.(2013) compilation. The fact that the number of GCs seems to scale lin- dyn early with the halo mass of the host galaxy (Blakeslee Similar to the results for S N , the relic galaxy sample lies 1999; Kravtsov & Gnedin 2005; Spitler & Forbes 2009; Hud- below the relation for ”normal” mass-matched ETGs in the M son, Harris & Harris 2014; Harris, Blakeslee & Harris 2017; S M– dyn plot. Again, this reinforces the notion that relic Boylan-Kolchin 2017; Choksi & Gnedin 2019; El-Badry et al. galaxies are maximally efficient in forming stars relative to GCs, and the process that might be responsible for lower this 2019) suggests that S N scales inversely with the stellar-to- halo mass relation, or the total star-formation efficiency, efficiency (i.e, satellite accretion) are less important in these where high star-formation efficiencies would imply low val- galaxies. By exploring the relation between NGC and Mdyn for differ- ues of S N . On the other hand, because S N can be high in both giants and dwarf galaxies, but is uniformly low at the ent morphological types, Harris et al.(2013) found that for ellipticals with M 10 the number of GCs increases al- intermediate-mass regime, an explanation for the high S > 10 M N M values in giant galaxies is that the large amounts of GCs are most in direct proportion to dyn, while S0s and spirals show an accreted population that once belonged to dwarf galax- an offset of 0.2 and 0.3 dex, respectively, below the trend ies. Recently, Beasley et al.(2018) reported that the GCS of of ellipticals. They claim that for the same mass, the disky NGC 1277, in the Perseus cluster is made up of almost ex- galaxies (higher angular momentum) have a lower fraction clusively red GCs, with only a small (<10%) fraction of blue of GCs, or have higher fraction of field stars. Furthermore, Harris et al.(2013) found that ( )1.3 is an accurate GCs by studying the optical color g−z with deep HST imag- Re,GALσe ing. This finding supports the idea from other studies based predictor of the total number of GCs over the entire mass on the age of its stellar population (Ferré-Mateu et al. 2018) range, from dwarfs to giants. M and its IMF (Mart´ın-Navarro et al. 2015) that this galaxy In Figure6 we show NGC versus dyn, Re,GAL, σe, and Re,GALσe for our sample and Harris et al.(2013) compilation is a relic. Furthermore, the S N of NGC 1277 is low (< 2), in accordance with a high star-formation efficiency as would without applying any offset according the morphological type be for a rapidly early dissipative formation and a lack of a as their Figure 9. We can see that indeed, our sample, which is biased towards very high velocity dispersions, is dominated accretion of high-S N , low-mass satellites. by low S N values, which is a consequence of either a smaller In Figure5 (upper panel) we show S N vs. MV,GAL for our sample and the compilation of galaxies from Harris et al. fraction of GCs, or a higher fraction of field stars. Again, the (2013), which comprises a sample of 422 ETGs, S0s and late- minimal accretion of low mass, high S N satellites could result in this higher fraction of field stars. Nevertheless, it is type galaxies with −24 < Mv < −14. We find low values of S N worthwhile mentioning that the offset N versus M for for our sample, < 2.5 with a median of 1. Assuming that the GC dyn late-type galaxies vs. ETGs could also be a direct result of behaviour of the bright side of S N vs. MV,GAL plot is dominated by accretion, and that the faint side is consequence of using such a virial mass estimator. Late-type galaxies have dissipative processes, then, relic galaxies would be the largest far more of their orbital energy tied up in rotationally sup- seeds formed by dissipative processes. A massive galaxy with ported orbits, so by using Eq. 6 we are likely to bias their dynamical mass estimates to the low side if we do not correct low S N could also be the consequence of a post-starburst due to a recent gas accretion with high luminosity dominated by for this in a more detailed dynamical model. young stellar population, as it seems to be the case for the second brightest galaxy in Fornax cluster (Liu et al. 2019). 4.3 GCS effective radius correlations A quantity harder to derive than S N but with more physical meaning is the specific mass, S M (Peng et al. 2008), which is Numerical simulations predict that accreted stars are prefer- the fraction of baryonic mass turned into GCs (MGCS ): entially deposited at large galactocentric distances (Naab, Jo- hansson & Ostriker 2009; Font et al. 2011; Navarro-González et al. 2013). This has been supported observationally from MGCS S M = 100 (5) metallicity and age radial gradients (Greene et al. 2015; Pa- M baryonic storello et al. 2014), as well as kinematics and low surface where for non-star forming galaxies we can assume Mgas ∼ 0 brightness structures (e.g., Mackey et al. 2013). As the ac-

MNRAS 000,1–11 (2019) 8 Alamo-Mart´ınezet al.

8 4 )

C 6 G 3 N N ( 0 S

1 2 4 g o l 1 2

7 8 9 10 11 12 1.2 1.6 2.0 2.4 0.5 0.0 0.5 1.0 1.5 1 2 3 4 log10(Mdyn/M ) log10( e)[km/s] log10(Re, GAL)[kpc] log10(Re, GAL e)

Figure 6. Number of GCs versus dynamical mass, velocity dispersion and eﬀective radii of their host galaxies. Circles are from Harris et al. 2013, while the squares (relics) and diamonds (non-relics) are the galaxies studied in this work. The colour-code indicates the S N .

2.5 This work Forbes+2017 ]

c 2.0 Kartha+2013 p

k Liu+2019 [ )

S 1.5 C G , e 1.0 R ( 0 1 0.5 g o l 0.0

10 11 12 0.5 0.0 0.5 1.0 1.5 log10 (M ) [M ] log10 (Re, GAL) [kpc]

Figure 7. GCS effective radius, Re,GCS as function of: Re,GAL (left) and stellar mass of the galaxy (right). creted galaxies not only contain stars but also GCs, the de- extension of the GCS is proportional to galaxy stellar mass position of stars and GCs at large galactocentric distances and Re,GAL but with a closer distribution to ETGs in the causes increases in both Re,GCS and Re,GAL. Fornax galaxy cluster (Liu et al. 2019). We note that there is no evidence for stripping in these relic candidates, i.e., all Although R is commonly measured to correct for spa- e,GCS of the correlations between the GC and system sizes reflect tial incompleteness, it is a GCS property little explored. Stud- the co-evolution of both due to merging (or lack thereof) ies of the spatial extension of the GCS, measured as the ra- modulating the orbits/sizes of both the field stars and GCs. dial distance at which the GC surface density reaches the background levels (Rhode et al. 2007; Rhode, Windschitl & Young 2010; Kartha et al. 2014) showed that the extension of the GCS is proportional to the host galaxy stellar mass 5 CONCLUSIONS and Re,GAL(but see also Saifollahi et al.(2020) for the case of ultra-diffuse galaxies). However, as pointed out by Kartha In this study we analyze the GC systems of a sample of 15 et al.(2014), the extension of the GCS is strongly depen- massive compact early-type galaxies from which 13 are relic dent on the quality of the data and the width of FOV, and galaxy candidates (Yıldırım et al. 2017). By using archival claimed that the correlations should be considered more as a HST imaging in the I and H bands, we determine the GCLF, general trend than a quantitative relation. Similarly, studies NGC, color and spatial distribution of the GCS, S N , S M and, of Re,GCS scaling relations (Forbes 2017; Hudson & Robison look for correlations with host galaxy properties from the M M 2018) reported not unexpectedly correlations between Re,GCS literature, such as, ?, dyn, λR, stellar velocity dispersion and host galaxy properties. However, although is consistent and metallicity. Our main findings are: the claim that R scales with R , the scaling factor is e,GCS e,GAL (i) The compact galaxy sample has low GC specific fre- significantly different among authors. quencies, S N < 2.5 with a median of S N = 1, whereas normal In Figure7 we show Re,GCS as function of Re,GAL and stellar ETGs of the same mass typically have 2 < S N < 10. This is in mass of the host galaxy for our sample and data from the agreement with the picture that the galaxies in our sample literature. Our data follow the general trend where the spatial experienced high star-formation efficiencies as would be the

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 9

Table 2. Globular cluster system parameters: (1) Galaxy name. (2) Total number of GCs. (3) The radius that contains half of the GC population. (4) Surface number density of GCs at Re,GCS. (5) S´ersic index. (6) Surface number density of background point sources. (7) Speciﬁc frequency. (8) Mean I − H. (9) Standard deviation of I − H. (10) Skewness of I − H. (11) Fraction of detected to total GC number (after correction by incompleteness in area and photometry).

* * *,a Galaxy NGC Re,GCS[kpc] Σ0 nmGCS BGps S N I − H σI−H skewness detected/total (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

NGC 0384 356 ± 47 6.04 ± 8.7 0.015 1.1 0.009 1.21 0.64 0.09 - 0.28 NGC 0472 328 ± 37 6.52 ± 0.8 0.021 0.5 0.003 0.74 0.59 0.11 - 0.23 MRK 1216 1013 ± 80 8.24 ± 0.7 0.034 0.5 0.003 1.43 0.59 0.10 -0.66 0.11 NGC 1270 485 ± 64 5.82 ± 0.8 0.032 0.5 0.008 0.88 0.78 0.13 -0.67 0.22 NGC 1271 180 ± 84 5.23 ± 1.1 0.018 0.7 0.003 0.27 0.69 0.09 - 0.22 NGC 1281 360 ± 30 4.5 ± 0.5 0.035 0.7 0.004 1.13 0.70 0.09 - 0.27 NGC 1282 184 ± 27 4.04 ± 1.5 0.017 0.6 0.005 1.37 0.58 0.11 - 0.82 UGC 2698 547 ± 100 8.57 ± 1.4 0.026 0.5 0.004 0.62 0.64 0.14 -0.59 0.18 NGC 2767 389 ± 49 7.96 ± 2.5 0.017 0.8 0.002 1.47 0.49 0.11 - 0.27 UGC 3816 253 ± 20 6.31 ± 2.5 0.017 0.8 0.004 0.55 0.51 0.09 0.47 0.49 NGC 3990 6 ± 2 1.6 ± 1.4 0.002 0.5 0.001 0.17 0.54 0.09 - 1.00 PGC 11179 200 ± 43 8.42 ± 3.0 0.005 0.5 0.003 0.42 0.65 0.10 -0.70 0.09 PGC 12562 31 ± 13 5.6 ± 8.8 0.004 0.5 0.007 0.13 0.84 0.21 - 0.44 PGC 32873 745 ± 238 18.4 ± 119.5 0.004 1.5 0.000 1.06 0.42 0.07 - 0.06 PGC 70520 183 ± 70 8.52 ± 2.4 0.007 0.5 0.003 0.36 0.51 0.08 - 0.26

* Measurments using all the GC candidate sources from 0 to 2Re,GCS, withouth background contamination subtraction. a Values significantly different from zero at 95% confidence level. Empty spaces are consistent with zero skew values. case for a rapid, early dissipative formation, together with (MINECO) and from the Severo Ochoa Excellence scheme relatively low levels of accretion of high-S N , low-mass satel- (SEV-2015-0548). CF acknowledges the financial support lites. from CNPQ (processes 433615/2018-4 and 311032/2017-6), (ii) The GCS spatial distributions are similar to those MT thanks the support of CNPq-307675/2018-1 and the in normal ETGs in that they are more extended than the program L’Oréal UNESCO ABC Para Mulheres na Ciência. starlight, and Re,GCS correlates with the galaxy properties ASM acknowledges CNPq-308306/2018-0. We acknowledge Re,GAL, M? and MHalo. discussions with Schoennell, Fabr´ıcio Ferrari and Rogério (iii) Intriguingly, we find a mild, but significant anti- Riffel. We acknowledge the reception of a fruitful week in correlation between the standard deviation of the I −H colour the peaceful countryside of Pueblo Mariana. This research distribution and the galaxy specific angular momentum, λR. has made use of the NASA/IPAC Extragalactic Database, While the present dataset is relatively small, if confirmed which is funded by the National Aeronautics and Space this result might be expected from hierarchical merging Administration and operated by the California Institute of models whereby galaxies which have undergone less accre- Technology. tion/merging activity might be expected to preserve their initial λR and have less complex GCS colour distributions. Future simulations can help constrain the diagnostic power DATA AVAILABILITY of λ when allied to the width of the colour distributions of R The data underlying this article are available from the corre- GC systems for understanding of merger histories of galaxies. sponding author, upon reasonable request. Moreover, quantification of the globular cluster color distributions of this sample with optical HST photometry would be extremely valuable to better constrain the accreted mass fractions in these systems. REFERENCES Alamo-Mart´ınez K. A., Blakeslee J. P., 2017, ApJ, 849, 6 Beasley M. A., 2020, Globular Cluster Systems and Galaxy For- ACKNOWLEDGEMENTS mation. pp 245–277, doi:10.1007/978-3-030-38509-5 9 Beasley M. A., Bridges T., Peng E., Harris W. E., Harris G. L. H., KAM acknowledges funding from CAPES/PNPD and Forbes D. A., Mackie G., 2008, MNRAS, 386, 1443 CONACyT. ACS acknowledges funding from the brazilian Beasley M. A., Trujillo I., Leaman R., Montes M., 2018, Nature, agencies Conselho Nacional de Desenvolvimento Cient´ı- 555, 483 fico e Tecnológico (CNPq) and the Rio Grande do Sul Beasley M. A., Leaman R., Gallart C., Larsen S. S., Battaglia G., Monelli M., Pedreros M. H., 2019, MNRAS, 487, 1986 Research Foundation (FAPERGS) through grants CNPq- Bertin E., Arnouts S., 1996, A&AS, 117, 393 403580/2016-1, CNPq-11153/2018-6, PqG/FAPERGS- Blakeslee J. P., 1999, AJ, 118, 1506 17/2551-0001, FAPERGS/CAPES 19/2551-0000696-9 and Blakeslee J. P., Cho H., Peng E. W., Ferrarese L., JordánA., Mar- L’Oréal UNESCO ABC Para Mulheres na Ciência. MAB tel A. R., 2012, ApJ, 746, 88 acknowledges support from grant AYA2016-77237-C3-1-P Boylan-Kolchin M., 2017, MNRAS, 472, 3120 from the Spanish Ministry of Economy and Competitiveness Brodie J. P., Strader J., 2006, ARA&A, 44, 193

MNRAS 000,1–11 (2019) 10 Alamo-Mart´ınezet al.

Buitrago F., Trujillo I., Conselice C. J., Bouwens R. J., Dickinson Liu Y., Peng E. W., JordánA., Blakeslee J. P., CôtéP., Ferrarese M., Yan H., 2008, ApJ, 687, L61 L., Puzia T. H., 2019, ApJ, 875, 156 Caldwell N., Schiavon R., Morrison H., Rose J. A., Harding P., Mackey A. D., et al., 2013, MNRAS, 429, 281 2011, AJ, 141, 61 Mart´ın-Navarro I., La Barbera F., Vazdekis A., Ferré-Mateu A., Chies-Santos A. L., Larsen S. S., Kuntschner H., Anders P., Trujillo I., Beasley M. A., 2015, MNRAS, 451, 1081 Wehner E. M., Strader J., Brodie J. P., Santos J. F. C., 2011, McConnell N. J., Ma C.-P., 2013, ApJ, 764, 184 A&A, 525, A20 Miller B. W., Lotz J. M., 2007, ApJ, 670, 1074 Chies-Santos A. L., Larsen S. S., Cantiello M., Strader J., Naab T., Johansson P. H., Ostriker J. P., 2009, ApJ, 699, L178 Kuntschner H., Wehner E. M., Brodie J. P., 2012, A&A, 539, Navarro-GonzálezJ., Ricciardelli E., Quilis V., Vazdekis A., 2013, A54 MNRAS, 436, 3507 Cho H., Blakeslee J. P., Chies-Santos A. L., Jee M. J., Jensen J. B., Oser L., Ostriker J. P., Naab T., Johansson P. H., Burkert A., Peng E. W., Lee Y.-W., 2016, ApJ, 822, 95 2010, ApJ, 725, 2312 Choksi N., Gnedin O. Y., 2019, MNRAS, 488, 5409 Pastorello N., Forbes D. A., Foster C., Brodie J. P., Usher C., Cohen J. G., Blakeslee J. P., CôtéP., 2003, ApJ, 592, 866 Romanowsky A. J., Strader J., Arnold J. A., 2014, MNRAS, CôtéP., Marzke R. O., West M. J., 1998, ApJ, 501, 554 442, 1003 Daddi E., et al., 2005, ApJ, 626, 680 Peng E. W., et al., 2006, ApJ, 639, 95 Damjanov I., et al., 2009, Red Nuggets at z ˜1.5: Compact Pas- Peng E. W., et al., 2008, ApJ, 681, 197 sive Galaxies and the Formation of the Kormendy Relation Peng E. W., et al., 2011, ApJ, 730, 23 (arXiv:0807.1744), doi:10.1088/0004-637X/695/1/101 Peralta de Arriba L., Quilis V., Trujillo I., Cebrián M., Balcells El-Badry K., Quataert E., Weisz D. R., Choksi N., Boylan-Kolchin M., 2016, MNRAS, 461, 156 M., 2019, MNRAS, 482, 4528 Pfeffer J., Kruijssen J. M. D., Crain R. A., Bastian N., 2018, MN- Ferrarese L., Merritt D., 2000, ApJ, 539, L9 RAS, 475, 4309 Ferré-Mateu A., Trujillo I., Mart´ın-Navarro I., Vazdekis A., Poggianti B. M., Moretti A., Calvi R., D’Onofrio M., Valentinuzzi Mezcua M., Balcells M., Dom´ınguez L., 2017, MNRAS, 467, T., Fritz J., Renzini A., 2013, ApJ, 777, 125 1929 Puzia T. H., Kissler-Patig M., Thomas D., Maraston C., Saglia Ferré-Mateu A., Forbes D. A., Romanowsky A. J., Janz J., Dixon R. P., Bender R., Goudfrooij P., Hempel M., 2005, A&A, 439, C., 2018, MNRAS, 473, 1819 997 Fleming D. E. B., Harris W. E., Pritchet C. J., Hanes D. A., 1995, Rhode K. L., Zepf S. E., Kundu A., Larner A. N., 2007, AJ, 134, AJ, 109, 1044 1403 Font A. S., McCarthy I. G., Crain R. A., Theuns T., Schaye J., Rhode K. L., Windschitl J. L., Young M. D., 2010, AJ, 140, 430 Wiersma R. P. C., Dalla Vecchia C., 2011, MNRAS, 416, 2802 Rodriguez-Gomez V., et al., 2017, MNRAS, 467, 3083 Forbes D. A., 2017, MNRAS, 472, L104 Saifollahi T., Trujillo I., Beasley M. A., Peletier R. F., Knapen Fukugita M., Hogan C. J., Peebles P. J. E., 1998, ApJ, 503, 518 J. H., 2020, MNRAS, Furlong M., et al., 2017, MNRAS, 465, 722 Salvador-Rusiñol N., Vazdekis A., La Barbera F., Beasley M. A., Geisler D., Lee M. G., Kim E., 1996,AJ, 111, 1529 Ferreras I., Negri A., Dalla Vecchia C., 2020, Nature Astron- Georgiev I. Y., Puzia T. H., Goudfrooij P., Hilker M., 2010, MN- omy, 4, 252 RAS, 406, 1967 Schlafly E. F., Finkbeiner D. P., 2011, ApJ, 737, 103 Greene J. E., Janish R., Ma C.-P., McConnell N. J., Blakeslee J. P., Schreiber C., et al., 2018, A&A, 618, A85 Thomas J., Murphy J. D., 2015, ApJ, 807, 11 Sersic J. L., 1968, Atlas de Galaxias Australes Harris W. E., 1991, ARA&A, 29, 543 Sirianni M., et al., 2005, PASP, 117, 1049 Harris W. E., 2009, ApJ, 699, 254 Spiniello C., et al., 2020, arXiv e-prints, p. arXiv:2011.05347 Harris W. E., Harris G. L. H., 2001, AJ, 122, 3065 Spitler L. R., Forbes D. A., 2009, MNRAS, 392, L1 Harris W. E., van den Bergh S., 1981,AJ, 86, 1627 Strader J., Brodie J. P., Cenarro A. J., Beasley M. A., Forbes Harris W. E., Harris G. L. H., Alessi M., 2013, ApJ, 772, 82 D. A., 2005,AJ, 130, 1315 Harris W. E., Blakeslee J. P., Harris G. L. H., 2017, ApJ, 836, 67 Thomas D., Maraston C., Bender R., Mendes de Oliveira C., 2005, Hill A. R., et al., 2017, ApJ, 837, 147 ApJ, 621, 673 Hilz M., Naab T., Ostriker J. P., Thomas J., Burkert A., Jesseit Tody D., 1986, Society of Photo-Optical Instrumentation Engi- R., 2012, MNRAS, 425, 3119 neers (SPIE) Conference Series, 627, 733 Hilz M., Naab T., Ostriker J. P., 2013, MNRAS, 429, 2924 Trager S. C., Faber S. M., Worthey G., GonzálezJ. J., 2000,AJ, Hopkins P. F., Bundy K., Murray N., Quataert E., Lauer T. R., 119, 1645 Ma C.-P., 2009, MNRAS, 398, 898 Trujillo I., et al., 2006, ApJ, 650, 18 Hudson M. J., Robison B., 2018, MNRAS, 477, 3869 Trujillo I., Cenarro A. J., de Lorenzo-Cáceres A., Vazdekis A., de Hudson M. J., Harris G. L., Harris W. E., 2014, ApJ, 787, L5 la Rosa I. G., Cava A., 2009, ApJ, 692, L118 Johansson P. H., Naab T., Ostriker J. P., 2009, ApJ, 697, L38 Trujillo I., Ferré-Mateu A., Balcells M., Vazdekis A., Sánchez- JordánA., et al., 2006a, ApJ, 651, L25 Blázquez P., 2014, ApJ, 780, L20 JordánA., et al., 2006b, ApJ, 651, L25 Usher C., et al., 2012, MNRAS, 426, 1475 JordánA., et al., 2007a, ApJS, 171, 101 Valentino F., et al., 2020, ApJ, 889, 93 JordánA., et al., 2007b, ApJS, 171, 101 Villegas D., et al., 2010, ApJ, 717, 603 Kartha S. S., Forbes D. A., Spitler L. R., Romanowsky A. J., Wellons S., et al., 2015, MNRAS, 449, 361 Arnold J. A., Brodie J. P., 2014, MNRAS, 437, 273 Yıldırım A., van den Bosch R. C. E., van de Ven G., Mart´ın- Kormendy J., Fisher D. B., Cornell M. E., Bender R., 2009, ApJS, Navarro I., Walsh J. L., Husemann B., Gultekin¨ K., Gebhardt 182, 216 K., 2017, MNRAS, 468, 4216 Kravtsov A. V., Gnedin O. Y., 2005, ApJ, 623, 650 Zolotov A., et al., 2015, MNRAS, 450, 2327 Kundu A., Whitmore B. C., 2001,AJ, 121, 2950 van Dokkum P. G., Conroy C., 2010, Nature, 468, 940 La Barbera F., Ferreras I., Vazdekis A., de la Rosa I. G., de Car- van Dokkum P. G., et al., 2010, ApJ, 709, 1018 valho R. R., Trevisan M., Falcón-Barroso J., Ricciardelli E., van den Bosch R. C. E., Gebhardt K., Gultekin¨ K., Yıldırım A., 2013, MNRAS, 433, 3017 Walsh J. L., 2015, ApJS, 218, 10 Lee S.-Y., Chung C., Yoon S.-J., 2019, ApJS, 240, 2

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 11

APPENDIX A: INDIVIDUAL GC SYSTEMS In Figures A1 to A15 we show for each individual GC system several derived properties: the spatial distribution of the GC candidates, the surface number density of the GC candidates as function of radius with the best Sérsic fit, the I − H color distributions for the population at different galactocentric radii, the I-band luminosity function, the H-band luminosity function of the GC candidates within 2Re and the I −H color magnitude diagram of the GC candidates within 2Re.

This paper has been typeset from a TEX/LATEX ﬁle prepared by the author.

MNRAS 000,1–11 (2019) 12 Alamo-Mart´ınezet al.

NGC0384

(a) 10 1 (b) (c) 25

1Re 2.0Re ]

2 20 c e s c r 15 a N / Y[pix] # [ C

G 10

5 10 2

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H 60 35 (d) (e) 22.5 (f) 50 30 23.0 25 40 23.5 20 24.0 I N 30 N

15 24.5 20 10 25.0 10 5 25.5

0 0 26.0 22 24 26 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A1. Derived parameters for the individual GC system of NGC 384 (a) the spatial distribution of the GC candidates highlighting with blue and yellow the sources belonging to the inner and outer population according to the Sérsic profile (panel b). The gray regions show masked areas due to bright stars, galaxies and pixels with bad quality. The circles show the annuli on which the surface number density of GCs was determined. (b) Surface number density of the GC candidates as function of radius. The solid line shows the best Sérsicfit. (c) I − H color distributions for the population within 1Re,GCS (solid blue), outer to 2Re,GCS (dashed yellow), and within 2Re,GCS (solid gray). (d) I-band luminosity function of the inner population corrected for contaminants. The dotted line shows the best Gaussian*Pritchet function, the solid line is the corresponding single Gaussian. (e) H-band luminosity function of the GC candidates within 2Re. (f) I − H vs. I color magnitude diagram of the GC candidates within 2Re with the mean error bars per magnitude bin.

NGC0472

(a) (b) 17.5 (c)

1Re 2.0Re 15.0 ] 2 12.5 c e s c

r 10.0 a N /

Y[pix] 2 # [ 10 7.5 C G 5.0

2.5

0.0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

(d) (e) 23.0 (f) 50 12 23.5 10 40 24.0 8 I

N 30 N 24.5 6 20 4 25.0

10 2 25.5

0 0 26.0 22 24 26 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A2. Same as in Fig A1.

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 13

MRK1216

1 (a) 10 (b) 25 (c)

1Re 2.0Re 20 ] 2 c e

s 15 c r a N / Y[pix] #

[ 2 10 10 C G

0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

140 (d) (e) 23.0 (f) 20 120 23.5

100 15 24.0 80 I N N 24.5 60 10

40 25.0 5 20 25.5

0 0 22 24 26 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A3. Same as in Fig A1.

NGC1270

(a) 10 1 (b) (c) 25

1Re 2.0Re ]

2 20 c e s c r 15 a N / Y[pix] # [ C

G 10

2 10 5

0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H 35 60 (d) (e) 22.5 (f) 30 50 23.0 25 40 23.5 20 I N N 24.0 30 15 24.5 20 10 25.0 10 5 25.5 0 0 22 24 26 22 24 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A4. Same as in Fig A1.

MNRAS 000,1–11 (2019) 14 Alamo-Mart´ınezet al.

NGC1271 (a) (b) (c) 10 1Re 2.5Re ]

2 8 c e s c r 6 a 2 N / 10 Y[pix] # [ C

G 4

0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

30 (d) (e) 23.0 (f) 8 25 23.5

20 6 24.0 I N 15 N 4 24.5 10 25.0 2 5 25.5 0 0 22 24 26 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A5. Same as in Fig A1.

NGC1281 20.0 (a) 10 1 (b) (c) 1Re 2.0Re 17.5

] 15.0 2 c e

s 12.5 c r a N

/ 10.0 Y[pix] # [ 2 C 10 7.5 G

5.0

2.5

0.0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H 70 17.5 (d) (e) 23.0 (f) 60 15.0 50 23.5 12.5 40 24.0 10.0 I N N 30 7.5 24.5

20 5.0 25.0 10 2.5 25.5 0 0.0 22 24 26 21 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A6. Same as in Fig A1.

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 15

NGC1282

(a) (b) 35 (c)

30 1Re 2.0Re ] 2 25 c e s c

r 20 a N / Y[pix] # [ 15 C G 2 10 10

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H 21 (d) (e) (f) 50 40 22

40 30 23

30 I N N 20 24 20

10 25 10

26 0 0 22 24 26 20 22 24 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A7. Same as in Fig A1.

UGC2698 30 10 1 (a) (b) (c) 25 1Re 2.0Re ] 2

c 20 e s c r a N 15 / Y[pix] # [ C

G 10 2 10

0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

100 (d) 20 (e) 23.0 (f)

23.5 80 15 24.0 60 I

N N 24.5 10 40 25.0

5 25.5 20

26.0 0 0 22 24 26 22 23 24 25 26 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A8. Same as in Fig A1.

MNRAS 000,1–11 (2019) 16 Alamo-Mart´ınezet al.

NGC2767 10 1 (a) (b) 25 (c)

1Re 2.0Re 20 ] 2 c e s

c 15 r a N / Y[pix] # [ 2 C 10 10 G

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

(d) 20 (e) (f) 50 23.5

24.0 40 15

24.5

30 I N N 10 25.0 20

5 25.5 10 26.0 0 0 22 24 26 23 24 25 26 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A9. Same as in Fig A1.

UGC3816 10 1 (a) (b) 35 (c)

1Re 2.0Re 30 ] 2 25 c e s c

r 20 a N / Y[pix] # [ 15 C G 10 2 10

0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

35 30 (d) (e) 22 (f) 30 25 23 25 20 20 I

N N 24 15 15 10 10 25

5 5 26 0 0 22 24 26 22 24 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A10. Same as in Fig A1.

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 17

NGC3990 10 2 8 (a) (b) (c) 7

] 6

2 1Re 2.0Re c e

s 5 c r a N

/ 4 Y[pix] # [

C 3 G

1 10 3 0 X[pix] 101 102 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

5 4 (d) (e) 21 (f)

4 22 3

3 23 I N N 2 2 24

1 25 1

26 0 0 22 24 26 20 22 24 26 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A11. Same as in Fig A1.

PGC11179 (a) (b) (c) 14

12 ]

2 1Re 2.0Re c 2 10 e 10 s c r

a 8 N / Y[pix] # [ 6 C G

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H 25 (d) 6 (e) 23.5 (f)

20 5 24.0 4 15

I 24.5 N N 3 10

2 25.0 5 1 25.5 0 0 22 24 26 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A12. Same as in Fig A1.

MNRAS 000,1–11 (2019) 18 Alamo-Mart´ınezet al.

PGC12562 (b) (c) 10 (a) 2 × 10 2 ]

2 8 c e s

c 1Re 2.0Re r 6 a N / Y[pix] # 2

[ 10 C

G 4

2 6 × 10 3 X[pix] 0 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

23.0 (d) 6 (e) (f) 15.0 5 23.5 12.5 4 24.0 10.0 I N N 3 24.5 7.5

2 5.0 25.0

2.5 1 25.5

0.0 0 22 24 26 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A13. Same as in Fig A1.

PGC32873 (a) (b) 14 (c)

12 1Re 1.5Re ]

2 10 c e s

c 8 r 2 a 10 N / Y[pix] #

[ 6 C G 4

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

140 (d) (e) 23.5 (f) 12 120

10 24.0 100 8 80 24.5 I N N 60 6 25.0 40 4

20 2 25.5

0 0 22 24 26 23 24 25 26 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A14. Same as in Fig A1.

MNRAS 000,1–11 (2019) Globular Cluster Systems of Relic Galaxies 19

PGC70520

(a) (b) 16 (c)

14 1Re 2.0Re ]

2 12 c

e 2

s 10

c 10 r a N / 8 Y[pix] # [ C

G 6

0 X[pix] 101 0.5 0.0 0.5 1.0 1.5 R [arcsec] I H

(d) (e) (f) 40 15.0 23.0

12.5 23.5 30 10.0 24.0 I N N 20 7.5 24.5

5.0 25.0 10 2.5 25.5

0 0.0 22 24 26 22 23 24 25 0.5 0.0 0.5 1.0 1.5 I [mag] H [mag] I H

Figure A15. Same as in Fig A1.

MNRAS 000,1–11 (2019)