11institutetext: Universidad Andres Bello, Facultad de Ciencias Exactas,
Departamento de Ciencias Físicas - Instituto de Astrofísica, Fernández Concha
700, Las Condes, Santiago, Chile.
11email<EMAIL_ADDRESS>22institutetext: European
Southern Observatory, Alonso de Cordova 3107, Vitacura, Casilla 19001,
Santiago de Chile 19, Chile. 33institutetext: Universidad Andres Bello,
Facultad de Ciencias Exactas, Departamento de Ciencias Físicas - Instituto de
Astrofísica, Autopista Concepción-Talcahuano, 7100, Talcahuano, Chile.
44institutetext: Observatoire de Paris - PSL, GEPI, F-92195 MEUDON, France.

# The galaxy cluster AC114
III. The role of galaxy clusters in the mass-metallicity relation

A. Andrade 1122 I. Saviane 22 L. Monaco 33 I. Yegorova 22 D. Proust 44

(Received XX XX, 2024; accepted XX XX, 2024)

###### Abstract

Context. The mass-metallicity relation (MZR) is a powerful tool to constrain
internal physical processes that drive the chemical evolution of galaxies.
However, the construction of this relation is carried out with field star-
forming galaxies in big data surveys where environmental effects are either
negligible or not studied in detail.

Aims. We study the role of galaxy clusters in the MZR and its evolution at
z=0.317 with star-forming members of AC114 (ABELL S1077). The purpose of this
work is to understand how both the environmental effects and dynamical events
modify the chemical evolution in this galaxy cluster.

Methods. Spectroscopic VIMOS/VLT data was used to select cluster members and
classify the galaxy sample in star-forming and passive galaxies. Gas-phase
metallicities were estimated by using the strong-line method O3N2 calibrated
on Te-based oxygen abundances. Available optical and near-infrared (NIR)
photometry from DECaLS DR10 and the VIKING DR4 ESO survey was used to derive
the stellar mass of the galaxy sample.

Results. AC114 is dominated by passive galaxies located in the central region
of the cluster, whereas the star-forming members tend to be located outside
this region. The constructed MZR from the latter indicates that star-forming
galaxies have a lower metal content than foreground galaxies (spanning
redshifts up to z=0.28), and the same or even lower metallicities with respect
to background galaxies (spanning redshifts 0.34 to 0.70). Additionally, it
shows a higher scatter of $\sigma=0.17$ dex, consistent with MZRs of galaxy
clusters reported in the literature. The MZR at z=0.317 is downshifted by 0.19
dex on average with respect to local galaxies. Comparing the AC114-MZR with
the field MZR at the same redshift, two galaxies are found to be more metal-
rich than the field ones by $\sim 0.10$ dex. Likely as a result of ram-
pressure stripping, star-forming galaxies deviate more from the MZR than field
galaxies at the same redshift. Star-forming galaxies in the cluster are in
general metal-poorer than field galaxies at the same redshfit up to $\sim
0.22$ dex, and show a MZR that is slightly shallower in slope compared with
that of field galaxies. With a redshift analysis, three substructures were
identified: star-forming galaxies in the main component show a higher scatter
of 0.20 dex in metallicity than both the front and back ones, with a scatter
of 0.07 and 0.11 dex, respectively. Star-forming galaxies located outside the
central region of AC114 are driving the shallower slope of the cluster MZR.

Conclusions. The slightly shallower slope and high scatter of AC114 with
respect to foreground and background galaxies in the mass-metallicity plane
indicates that galaxies are suffering from environmental and dynamical
effects. Ram-pressure stripping and strangulation are likely the main drivers
in increasing the metallicities of at least two star-forming members with
respect to the field MZR at the same redshift. However, the lower
metallicities of the star-forming members, which drive the flatter slope of
the AC114-MZR, can be explained by strong metal-poor inflows triggered by
galaxy-galaxy interactions. In fact, the downshift reported for these galaxies
is consistent with other observations and simulations, as a result of mergers
and/or flybys, which dilute the gas-phase metallicities from metal-poor
inflows. The mass of a galaxy cluster appears to be a key variable in
determining the importance of environmental effects in the evolution of
cluster members, where massive galaxy clusters ($M_{vir}>10^{15}M_{\odot}$)
show changes in the slope of the MZR.

###### Key Words.:

chemical evolution of galaxies – mass-metallicity relation – galaxy clusters –
intermediate redshift

##  1 Introduction

The evolution of galaxies is associated with global features, such as
morphology and kinematics, as well as properties that drive the evolution of
the stellar populations that they have (e.g., chemical composition, star
formation rates (SFRs), initial mass, and luminosity functions). Physical
phenomena such as inflow and outflow processes are also known to be key in
driving the chemical evolution of galaxies.

Seminal works in the 70s showed that supernovae (SNe) explosions and stellar
winds play a significant role in the chemical evolution. Supernovae explosions
bring enough energy to ionize and accelerate particles in the interstellar
medium, heating the environment and expelling the gas component through
galactic winds. This process is more efficient in low-mass galaxies, where
reaching the escape velocity is easier because of their shallow potential
wells (Larson 1974, Lequeux et al. 1979). In addition, inflows of pristine gas
can dilute metals, increasing star formation and leading to the synthesis of
new heavy elements (Finlator & Davé, 2008). The balance between these
processes naturally produces the mass-metallicity relation (MZR), according to
which high-mass galaxies present high gas-phase metallicities.

In the last two decades, the MZR has shown itself to be a powerful tool to
constrain the chemical evolution of galaxies. Tremonti et al. (2004), using a
large sample of star-forming (SF) galaxies, constructed the MZR of the local
Universe, showing statistically robust evidence of the existence of this
relation and confirming the suggestion introduced by Larson (1974) that low
abundances and a tight ($\pm 0.1$dex) MZR are driven by efficient gas loss. On
the other hand, the MZR tends to flatten for massive galaxies with $M\geq
3\times 10^{10}M_{\odot}$ (Kauffmann et al. 2004) because of galactic
downsizing, where the closed-box-like behavior begins (Cowie et al. 1996,
Neistein et al. 2006, Sánchez et al. 2013, Spitoni et al. 2020). The MZR also
evolves in redshift: both the gas-phase metal content and stellar masses of
galaxies increase across cosmic time, where the higher-redshift MZR ($z<3.5$)
presents a higher downshift with respect to the local Universe (Savaglio et
al. 2005, Erb et al. 2006, Maiolino et al. 2008, Moustakas et al. 2011, Zahid
et al. 2014, Gao et al. 2018). Evidence of smooth metallicity gradients and
the weak dependence on the SFRs in SF galaxies at $z\sim 3$ show that
processes involving material flows are stronger at higher redshifts, naturally
resulting in a shallower slope across cosmic time (Troncoso et al. 2014). On
the other hand, the formation processes of galaxies in the hierarchical growth
scenario and the key role of SNe feedback, which acts as the main regulator of
the star formation and morphology of the galaxies, proves that mergers
depending on the gas fractions of their galaxies drive changes in the
evolution of the MZR (Tissera et al. 2005, de Rossi et al. 2007, Kobayashi et
al. 2007, Scannapieco et al. 2008).

The internal phenomena of SF galaxies that drive the MZR have been extensively
studied (see Maiolino & Mannucci 2019 for a detailed review). However, a
similar investigation of the physical processes intervening in the chemical
evolution of galaxies in dense environments such as groups and galaxy clusters
is missing. Therefore, constructing the MZRs in a galaxy cluster allows the
exploration of the chemical evolution of its members in a broad range of
masses at a given redshift, under a variety of dynamical and environmental
effects.

Clusters of galaxies present deep potential wells originating in the
interaction of smaller-scale structures or the evolution of overdensities in
the early Universe (Press & Schechter 1974, Springel et al. 2005). In the
former scenario, the “preprocessing” can affect galaxies’ chemical evolution
as well as their morphology and kinematics (Fujita 2004). In a recent work,
Kim et al. (2022) showed that in galaxy clusters with ongoing dynamical
activity, early infallers will stop the star formation activity due to strong
strangulation processes, while the recent infallers will suffer from ram-
pressure stripping (RPS) when galaxies interact with the intracluster medium
(ICM). Moreover, the scenario will be even more chaotic when infall makes
physical mechanisms such as accretion, tidal interactions, and mergers more
likely (Barton et al. 2000, Alonso et al. 2007, Ellison et al. 2008, 2019).

Up to date, the general picture of the role of the physical phenomena driving
the evolution of galaxies in clusters is still unclear. However, the virial
mass of galaxy clusters plays a crucial role, underlying differences in the
chemical content of cluster members with respect to field galaxies
(Petropoulou et al., 2012). This allows the exploration of environmental
mechanisms that affect the chemical evolution of galaxies and to investigate
the origin of the quenching of galaxies in more detail. For example, in high-
mass-density environments, galaxies found at the cluster center or group
center will experience enhancements in the gas-phase abundances up to $\sim
0.05$ dex (Ellison et al., 2009). This could be produced (i) by a metal-poor
inflow suppression toward the galactic center, (ii) preprocessed gas from the
ICM, (iii) tidal interactions producing starbursts, (iv) strangulation, and
(v) RPS (Gunn & Gott 1972) acting on galaxies with nonzero metallicity
gradients (Ellison et al. 2009, Petropoulou et al. 2011, 2012, Gupta et al.
2016). On the other hand, although galaxy clusters with $M\sim
10^{14}M_{\odot}$ also contain SF galaxies suffering environmental effects,
these do not seem to be strong enough to produce significant changes in the
chemical content of the cluster’s members. However, a weak metallicity
dependence on clustercentric radii is seen (Petropoulou et al. 2012, Gupta et
al. 2016,Vaughan et al. 2020, Lara-López et al. 2022), showing the relevance
of galaxy cluster masses in the exploration of the phenomena that shape the
chemical evolution of galaxies.

In this work, we study the role of galaxy clusters in the MZR, by using SF
galaxies at redshift $z\sim 0.3$ belonging to AC114 (ABELL S1077). AC114
($\alpha=22^{h}58^{m}52^{s}.3$, $\delta=-34^{o}46^{\prime}55^{\prime\prime}$;
J2000) has been widely studied near the cluster core,
$r_{core}=0.27h^{-1}\mathrm{Mpc}$ (Couch & Sharples 1987). The cluster core
shows strong lensing arcs produced by the central dominant (cD) galaxy of
AC114 (Smail et al. 1995, Natarajan et al. 1998, Campusano et al. 2001). AC114
hosts a higher fraction of blue, late-type galaxies than lower-redshift galaxy
clusters (Couch et al. 1998, Sereno et al. 2010), which is a typical symptom
of the Butcher-Oemler effect (Butcher & Oemler, 1978). Roughly $60\%$ of
galaxies are found outside the core region, and its red sequence is separated
from the blue galaxies (Proust et al. 2015). A soft extended X-ray tail
originates close to the cluster core, extending $\sim 1.5^{\prime}$ toward the
southeast ($\sim 400$ kpc), suggesting that the substructure could be part of
an ongoing merger event (De Filippis et al., 2004).

This is the third paper in a series. In paper I, Proust et al. (2015)
revisited the dynamical state of AC114. They find that the large velocity
dispersion of $1893_{-82}^{+73}\ \mathrm{km\ s^{-1}}$ and the shape of its
infalling pattern is indicative of AC114 being in a radial relaxation phase,
showing a very elongated radial filament structure spanning $12000$ km s-1.
From the dynamical activity, they find that AC114 is a massive galaxy cluster
with a virial mass of $M_{vir}=(4.3\pm 0.7)\times 10^{15}h^{-1}M_{\odot}$. In
paper II, Saviane et al. (2023), by studying stellar populations of passive
galaxies and emission line galaxies (ELGs), find that the stellar MZR is
steeper than the local Universe analogue. Moreover, the stellar evolution of
galaxies in the center is faster than that found in those on the outskirts of
AC114, where the latter are still forming stars, a signal that strangulation
processes are stronger in the central region of AC114.

In this work, we study the AC114-MZR through a chemical analysis of the gas-
phase component of its SF galaxies. In Section 2, we present the spectroscopic
and photometric observations used, together with the data reduction. In
section 3, we describe the data analysis, including the redshift, mass, and
metallicity measurements and estimates. In section 4, we present the MZRs
constructed for the foreground, cluster members, and background galaxies,
together with their properties. In Sections 5 and 6 we discuss the results
that we obtain and presents our conclusions.

In this paper, we adopt the following cosmological parameters: $H_{0}=69.6\
\mathrm{km\ s^{-1}\ Mpc^{-1}}$, $\Omega_{M}=0.286$, and
$\Omega_{\Lambda}=0.714$ in a flat Universe according to Wright (2006).

##  2 Observations and data reduction

###  2.1 VIMOS spectroscopic data

In this work, we use the same spectroscopic data as Proust et al. (2015) and
Saviane et al. (2023), hereafter P15 and S23. The data was obtained with the
VIsible MultiObject Spectrograph (VIMOS, Le Fèvre et al. 2003) mounted on the
ESO Very Large Telescope (VLT), under the program 083.A-0566 (PI: I. Saviane),
between August 16 and September 25, 2009. VIMOS was a visible (360 to 1000 nm)
wide field imager and multi-object spectrograph mounted on the Nasmyth focus B
of UT3 Melipal. The instrument is made of four identical arms with a field of
view (FOV) of $7^{\prime}\times 8^{\prime}$ with a $0.205^{\prime\prime}$
pixel size and a gap between each quadrant of $\sim 2^{\prime}$. Seven
exposures each for the HR-red and MR grisms (630 - 870 nm, $R=2500$ and 500 -
1000 nm, $R=580$, respectively, for a $1^{\prime\prime}$ slit) were obtained,
for a total observing time of $\sim 14$h.

The galaxy selection was made from the pre-imaging frames of the cluster.
Nonstellar objects in the region were selected by eye in order to punch the
maximum number of slits into each of the four quadrants. Such a visual
inspection allowed us to discriminate between extended objects and stars.

The VIMOS Pipeline in the EsoReflex environment
111https://www.eso.org/sci/software/pipelines/vimos/ (Freudling et al. 2013)
was used to perform bias subtraction, flat normalization and cosmic ray
removal in each scientific frame. Then, sky subtraction was done, taking the
median of the sky spectrum located between the galaxy spectra in the two-
dimensional frames. The spectral flux was calibrated by using two standard
stars from Hamuy et al. (1992, 1994): the F-type LTT1788 ($V=13.16$,
$B-V=0.47$) and DA-type LTT7987 ($V=12.23$, $B-V=0.05$).

Once the galaxy spectra were reduced, we proceeded with emission line
corrections to get proper flux measurements. We subtracted stellar continuum
spectra by fitting Chebyshev polynomials with the Specutils package (Astropy-
Specutils Development Team, 2019). Emission line fluxes from collisional de-
excitation ($O^{+},O^{++},N^{+},S^{++}$) were then measured with a Gaussian
fitting. To correct for dust and reddening effects, H$\alpha$ and H$\beta$
fluxes were measured by Gaussian fitting as well, and the observed hydrogen
line ratio ($F_{H\alpha}/F_{H\beta}$) was compared with the theoretical
expectations. The H line ratio, $I_{H\alpha}/I_{H\beta}$= 2.85, was adopted
from case B ($T_{e}\simeq 10000$K) following Hummer & Storey (1987). The
reddening constant was calculated as
$C_{H\beta}=[\log{(I_{H\alpha}/I_{H\beta})}-\log{(F_{H\alpha}/F_{H\beta})}]/[f(\lambda)-f(H\beta)]$,
where $f(\lambda)=\langle A(\lambda)/A(V)\rangle$ is the extinction law at a
given wavelength of the modified version of Cardelli et al. (1989) in the
optical domain, obtained from O’Donnell (1994). We also assumed that
$R_{V}=3.1$. Finally, emission line measurements were corrected by applying
$I_{\lambda}/I_{H\beta}=(F_{\lambda}/F_{H\beta})\times
10^{C_{H{\beta}}[f(\lambda)-f_{H\beta}]}$.

Recombination H lines can be affected by underlying stellar absorption,
producing changes in the metallicity estimations due to the use of Balmer
lines in the most common calibrators. However, the spectra of our sample are
contaminated by fringing patterns in $\lambda>7500\AA$, so it is difficult to
make an appropriate correction for the stellar absorption at $z\sim 0.3$, the
H$\alpha$ emission line falls at $\sim 8500\AA$).
To evaluate a proper correction of this effect, we employed the Hopkins et al.
(2003) correction, which was tested in galaxies of the SDSS survey. The
authors show that an appropriate stellar absorption correction is about
$\mathrm{EW=1.3\AA}$, which in this work is translated in a flux correction of
$F_{\lambda}\sim 0.001$ and $\sim 0.002\times 10^{-16}$ erg s-1 cm-2 on
average for H$\alpha$ and H$\beta$, respectively. Therefore, these corrections
were applied to the emission line measurements of the Balmer lines.

Our sample consists of 184 spectra of galaxies, where 25 ($13\%$) are not
reported in earlier works with the same data, because in this paper the
observations were reduced with the latest version (4.1.8) of the VIMOS
pipeline. The sample is listed in Table 2, with galaxies labeled according to
the quadrant and slit of extraction. Additional galaxies are listed in Table 2
with the syntax $\\#$quadrant-A$\\#$. Our sample is shown on top of an image
of AC114 in Figure 1.

Applying the same criteria as in S23, a manual inspection of the reduced
spectra was conducted to classify the sample into passive galaxies and ELGs,
based on the presence or absence of the [OII]$\lambda\lambda 3727$,
[OIII]$\lambda\lambda 4959,5007$, and/or H$\gamma$, H$\beta$ emission lines.
Figure 2 shows the difference between a passive galaxy and an ELG in the
sample. We identified 103 ($56\%$) passive and 81 ($44\%$) ELGs. The top panel
shows the spectrum of the passive galaxy Q4-31 ($\\#quadrant\ \\#slit$). Only
absorption features can be identified in the spectrum, such as CaII H $\&$ K,
the CH G band, the Mg triplet, and the Na D doublet, shown with red lines from
left to right, respectively. The bottom panel of Figure 2 shows the spectrum
of the ELG Q4-14. In this case, only emission lines are present, such as
[OII]$\lambda\lambda 3727$, H$\gamma$,$\mathrm{[OIII]\lambda 4363}$, H$\beta$,
[OIII]$\lambda\lambda 4959,5007$, H$\alpha$, [NII]$\lambda 6584$, and
[SII]$\lambda\lambda 6716,6731$ shown with blue lines from left to right,
respectively.

Most of the galaxies are in Q4 (62 galaxies, bottom right in Figure 1), which
covers the central region of AC114. The other 35, 41, and 46 galaxies are
grouped in the Q1, Q2, and Q3 quadrants, respectively (counterclockwise). The
clumps are produced by the VIMOS CDD-chips gap of $\sim 2^{\prime}$.

Figure 1: Observed galaxies (colored circles) on top of an image taken from
the DECaLS DR10 viewer for the AC114 cluster. Quadrants Q1, Q2, Q3, and Q4 are
counterclockwise, with Q4 in the bottom right clump.

Figure 2: Reduced spectra of a passive galaxy (top panel) and an ELG (bottom
panel). Red lines indicate absorption features, whereas blue lines indicate
emission features.

###  2.2 Optical and near-infrared photometric data

To construct the MZR, photometric data is needed to compute the stellar masses
of the galaxies. Optical photometry was found for the VIMOS FoV of AC114 in
the DECaLS DR10 Survey (see Dey et al. 2019 for an overview of the DESI Legacy
Imaging Surveys). The DECaLS program made use of the Dark Energy Camera
(DECam) on the Blanco 4m telescope, located at the Cerro Tololo Inter-American
Observatory. DR10 covers the South Galactic Cap region at Dec$\leq
34^{\mathrm{o}}$ in the $g,r,z,i$ bands. 121 ($66\%$) and 139 ($76\%$)
galaxies in our sample have available photometry in the $g$ and $i$ bands,
respectively. However, no photometry is available in the $r$ and $z$ bands.

Figure 3: Top panel: Distribution of photometric data collected from DECaLS
DR10 survey. The blue line indicates the distribution of $g-$band magnitudes
and the orange line indicates the distribution of $i-$band magnitudes. Bottom
panel: Distribution of photometric data collected by the VIKING DR4 survey.
The blue line indicates the distribution of $H-$band magnitudes and the orange
line indicates the distribution of $K_{s}-$band magnitudes.

The top panel of Figure 3 shows the distribution of apparent magnitudes for
both $g$ and $i$ band passes with blue and orange lines, respectively.
Galaxies observed in the $g$ band cover a magnitude range from 18.83 to 25.10,
with a clear peak at 22.46, while the respective $i$ band magnitudes cover a
range of 16.67 to 23.77, with three prominent clumps centered on 22.24, 20.76,
and 19.32.

Bell & de Jong (2001), studying stellar mass-to-light ratios in optical and
near-infrared (NIR) band passes, found that NIR luminosities are less
sensitive to the past star formation history, smoothing out variations with
respect to the color. Therefore, they concluded that NIR luminosities lead to
more accurate stellar masses. With this motivation, we also searched for
available NIR photometric data, which we found in the VIKING DR4 ESO survey.
The VISTA Kilo-degree Infrared Galaxy Survey
(VIKING)222https://www.eso.org/rm/api/v1/public/releaseDescriptions/135 is a
wide-area (covering a final area of 1350 square degrees), intermediate-depth
($5\sigma$ detection limit $J\sim 21$ on Vega system) NIR imaging survey in
the five broadband filters, $Z$, $Y$, $J$, $H$, and $K_{s}$. The sky coverage
is at high galactic latitudes and includes two main stripes of
$\leavevmode\nobreak\ \sim 70\times 70^{\mathrm{o}}$ each: one in the South
Galactic cap near Dec$\simeq-30^{\mathrm{o}}$ and one near Dec$\sim
0^{\mathrm{o}}$. A cone search of $25^{\prime}$ was conducted, centered on the
cluster, and 121 ($66\%$) of the galaxies in our data set were found. Near-
infrared photometry in VIKING DR4 was only available in the $H$ and $K_{s}$
bands.

The bottom panel of Figure 3 shows the distribution of apparent magnitudes for
our galaxy sample for both $H$ and $K_{s}$ bands, shown with blue and orange
lines, respectively. Galaxies observed in the $H$ and $K_{s}$ bands cover a
range of magnitudes from 14.90 to 20.60 and from 14.10 to 19.79, respectively.

As is discussed in P15 and S23, our galaxy sample reaches luminosities as
faint as $R\sim 21$, but it starts to suffer incompleteness at $R\sim 20$. We
searched in the galaxy sample for objects with values $R\sim 20$ and found
that the galaxy sample is incomplete at $g\sim 21.4$ and $i\sim 19.8$ mags in
the optical bands, whereas the same is seen at $H\sim 17.7$ and $K_{s}\sim
17.3$ mags in the NIR band passes. The photometry is used to compute the
stellar masses via mass-to-light ratios in the galaxy sample. The
incompleteness starts to be significant in galaxies with $\sim
10^{10}M_{\odot}$.

The cluster members in the galaxy sample are well distributed in terms of
mass, spanning values from $\sim 10^{9}M_{\odot}$ to $\sim 10^{11}M_{\odot}$,
as is expected for a construction of the MZR. Therefore, the incompleteness
does not affect our results.

##  3 Data analysis

###  3.1 Redshift estimations

The galaxies’ redshift, $z$, was measured by cross-correlation (Tonry & Davis,
1979) between the VIMOS spectra and synthetic ones at $z=0$ in the wavelength
range from 3700$\AA$ to 8800$\AA$. In this work, we made use of the Bagpipes
models333Bagpipes is a state of the art Python code for modelling galaxy
spectra and fitting spectroscopic and photometric observations.
https://bagpipes.readthedocs.io/en/latest/ (Carnall et al., 2019) to generate
a standard passive and a SF synthetic spectrum, shown in Figure 4 with blue
and orange, respectively. We considered a galaxy whose spectrum presents a
evolved stellar continuum with relevant absorption lines typically found in
old stellar populations to represent a passive galaxy. We achieved this,
generating a synthetic spectrum of a galaxy with stellar mass
$M^{*}=10^{10}M_{\odot}$ and 10 Gyr since the star formation began by using
the exponential$-\tau$ model . On the other hand, an SF galaxy has a small
stellar continuum with prominent emission lines: we calculated the spectrum of
a galaxy with a stellar mass of $M^{*}=10^{8}M_{\odot}$, 1Gyr after the star
formation began, by using the exponential$-\tau$ model, and an ionization
parameter, log($U$)=$-2.5$.

Figure 4: Synthetic spectra reproduced with the Bagpipes models. The blue
spectrum represents a passive galaxy. The orange spectrum represents an SF
galaxy.

Once the synthetic spectra were ready to use, we cross-correlated them with
the VIMOS spectra. We used the IRAF 444IRAF is distributed by the National
Optical Astronomy Observatories, which are operated by the Association of
Universities for Research in Astronomy, Inc., under cooperative agreement with
the National Science Foundation. task “fxcor” to estimate the redshift of
galaxies. The galaxies of the sample have $\sim 0.1<z<0.7$, with uncertainties
of $0.0014$ on average. The redshift distribution of the sample is shown in
Figure 5. Emission line galaxy and passive galaxy distributions are shown with
blue and red lines, respectively. The distribution reveals that passive
galaxies are found at the cluster redshift, meaning $0.28<z<0.34$ according to
P15. In this region, 58 ($73\%$) of a total of 80 galaxies are passive, while
22 ($27\%$) are ELGs. Outside the cluster redshift, it is clear that there is
an additional structure that is dominated by ELGs centered on $z\sim 0.41$.
According to P15, this background structure has a probability of $\sim 60\%$
of being a group.

Figure 5: Redshift distribution of the galaxy sample. Upper panel:
Distribution of passive galaxies (red line) and ELGs (blue line). Lower panel:
Redshift distribution of the complete sample.

###  3.2 Stellar mass estimates

Figure 6: Comparison between DECaLS DR10 (on the x axis) and those from
artificial magnitudes (on the y axis). Colors are the same as in Figure 5. The
gray line is an identity line. Top panel: Comparison between synthetic and
DECaLS magnitudes in the $i$ band. Bottom panel: Comparison between synthetic
and DECaLS magnitudes in the $i$ band with the applied correction. Figure 7:
Central panel: Comparison between $i$ and $Ks-$based masses. Blue and red dots
represent ELGs and passive galaxies, respectively. The gray line corresponds
to the 1:1 line ratio. Upper panel: Distribution of optical luminosity based
stellar masses. The black line shows the mass distribution of the complete
sample, whereas the blue and red areas indicate the distribution of ELGs and
passive galaxies, respectively. Right panel: Distribution of near-infrared
luminosity based stellar masses.

####  3.2.1 Synthetic photometry

The masses of the galaxies were obtained by using stellar mass-to-light
ratios. The data acquired from DECaLS DR10 give us photometry for $66\%$ and
$76\%$ of the galaxies in the sample in the $g$ and $i$ bands, respectively.
For galaxies without photometry, we obtained synthetic photometry by
integrating the spectral flux of the galaxies. Optical stellar mass estimates
are done via the theoretical mass-to-light ratio in the $i$ band. Therefore,
synthetic photometry was estimated for this filter only because it has
available photometry for more galaxies than the $g$ band does.

We made use of the PYPHOT555https://mfouesneau.github.io/pyphot/ (Fouesneau,
2022) Python package. As a first step, we calculated the synthetic photometry
of the LTT7987 standard star. We obtain magnitudes underestimated by $\Delta
M_{i}=M_{standard,i}-M_{pyphot,i}=0.16$. Therefore, this amount was applied as
a correction when the artificial magnitudes were computed. In addition, the
$1^{\prime\prime}$ slits used in the VIMOS observations do not entirely cover
the projected area for most of the galaxies of the sample, which is $\sim
3^{\prime\prime}$. Therefore, we expect that synthetic photometry will present
overestimated apparent magnitudes (underestimated luminosities). In fact, this
is seen as an offset in the top panel of Figure 6, which presents a comparison
between the artificial magnitudes and those collected from DECaLS DR10.
Synthetic magnitudes are $\sim 1.49$ larger in the i band, with a scatter of
$\sigma=0.46$. Hence, overestimations were corrected by subtracting this
offset from the artificial magnitudes. The resulting correction is shown in
the bottom panel of Figure 6. We adopted the scatter, $\sigma_{i}$, as a
statistical error of the artificial magnitudes. This is similar to the optical
magnitudes from DECaLS, which present a mean uncertainty of $0.47$ mags.

####  3.2.2 Optical-based stellar masses

To compute the absolute magnitudes, we followed the same procedure reported in
S23, which converts apparent magnitudes to absolute ones, with
$i-M_{i}=5\log{D_{L}}-5$. Here, $D_{L}$ is the luminosity distance, which is a
function of the redshift. A relation was computed for a few select values
following Wright (2006). Interpolating a second-degree polynomial it was found
that the luminosity distances expressed in Mpc obey $D_{L}=2245.7\
z^{2}+4682.4\ z-20.838$, valid only in $z\in[0.05,0.7]$ (see their Figure 11,
S23).

Absolute magnitudes in the $i$ band were converted to luminosities, with
$L=10^{-0.4(M_{i}-M_{i,\odot})}L_{\odot}$. Following S23, for ELGs and passive
galaxies we adopted ages of 2Gyr and 10Gyr, respectively. By using the
theoretical age-mass-to-light relation from E-MILES models (Vazdekis et al.
2012,2016, Ricciardelli et al. 2012), the corresponding ages gives:
$M/L_{i}=0.75\ \pm\ 0.20$ (ELGs) and $2.48\ \pm\ 0.52$ (passive). These models
adopt evolutionary tracks from Girardi et al. (2000), assuming a sub-solar
metallicity of $[M/H]=-0.4$ and a Chabrier initial mass function (IMF).
Finally, mass-to-light ratios together with the luminosities were converted
into the stellar masses of the galaxies. Uncertainties were propagated
according to the expression $\delta f=\sqrt{\sum_{i}(\partial f/\partial
x_{i})^{2}\delta x_{i}^{2}}$, where $f$ is the propagated function, $x_{i}$,
and $\delta x_{i}$ are the parameters with their respective uncertainties.
Optical-based mass estimations shows mean uncertainties of $\sim 2\%$. Table
3.3 presents absolute magnitudes in the optical band used in this work,
together with the respective mass estimations. The distribution of masses is
shown in the upper panel of Figure 7. Masses of ELGs are distributed between
$\sim 10^{8}$ and $\sim 10^{11}M_{\odot}$, whereas those of passive ones lie
from $\sim 10^{9}$ to $\sim 10^{12}M_{\odot}$. From the upper panel of Figure
7 it is easy to see that, in general, ELGs are less massive than passive
galaxies: masses are more concentrated at $\sim 10^{9.5}$ and $\sim
10^{10.5}M_{\odot}$ for the ELGs and passive components, respectively.

####  3.2.3 Near-infrared-based stellar masses

Given that we were able to obtain NIR luminosities for $66\%$ of the galaxy
sample, optical-based and NIR-based stellar masses can be compared. Bell & de
Jong (2001), by using spectro-photometric models of galaxy evolution, found
that there are substantial variations in the stellar mass-to-light ratios
within and among galaxies as a function of the color, showing variations of a
factor of three and seven in optical band passes and two in the NIR ones.
These findings drive to a natural conclusion that NIR-based mass estimations
are the best way to obtain the stellar masses of galaxies, because recent star
formation can generate optical light that dominates the SED, leading to
underestimates of the stellar mass, whereas recent star formation does not
affect much NIR light.

E-MILES models were used one more time to compute mass-to-light ratios as a
function of the age, resulting in $M/L_{Ks}=0.26\ \pm\ 0.09$ (ELGs) and
$M/L_{Ks}=0.91\ \pm\ 0.13$ (passive). $K_{s}$ absolute magnitudes, together
with NIR-based stellar mass estimations, are presented in Table 3.3. The mass
distribution is also shown in the right panel of Figure 7. Emission line
galaxies span values from $\sim 10^{9}$ to $\sim 10^{11}M_{\odot}$, and
passives ones from $\sim 10^{10}$ and $\sim 10^{12}M_{\odot}$. Despite the
lack of NIR photometry for $34\%$ of the sample, the feature that passive
galaxies are more massive in general than ELGs is clearly seen.

The central panel of Figure 7 shows a comparison between optical-based and
NIR-based stellar masses. The comparison shows that the mass estimations
agree, following a $1:1$ relation, for galaxies with $M^{*}<10^{10.5}$, where
the sample is mostly dominated by ELGs. On the other hand, at masses
$M^{*}>10^{10.5}$, galaxies tend to fall above the 1:1 relation by 0.23 orders
of magnitude on average. This region is mostly dominated by passive galaxies.
However, this offset is within the uncertainty of the mass estimates, which is
$\sigma=0.29$ mags. Therefore, it does not change our conclusions about the
MZR construction.

###  3.3 Metallicity estimations

####  3.3.1 Classification of star-forming galaxies

In section 2.1 we define ELGs by the presence of emission lines in their
spectra. However, the ionization sources that trigger emission lines can be
produced by active galactic nuclei (AGNs) and/or SF activity. To discriminate
the actual nature of our galaxies, we made use of the emission line ratios,
$\mathrm{[NII]\lambda 6584/H\alpha}$ and $\mathrm{[OIII]\lambda 5007/H\beta}$,
in the Baldwin-Philips-Terlevich (BPT) diagram (Baldwin et al., 1981). In
fact, the BPT diagram is a useful tool with which to identify the dominant
ionization source of emission line galaxies. Figure 8 shows the ELGs of the
sample in the diagram. The red dots are cluster members and the black diamonds
correspond to foreground and background galaxies. The dashed black line is the
Kewley limit (KL). Galaxies found below the KL have dominant ionization from
HII regions, where ongoing star formation is present. However, ELGs can have
ionization from both HII regions and AGN activity, i.e. they are composite
galaxies. Therefore, we used the Kauffmann et al. (2003) demarcation limit to
select pure SF galaxies and also study the possible effects of composite
galaxies in the MZR. Composite galaxies are shown in Figure 8 with open blue
diamonds. Two composite galaxies are present in AC114, two belong to the
foreground, and three belong to the background galaxies.

The fact that there is not a significant number of composite galaxies
contaminating the galaxy sample allows us to make a direct and homogeneous
comparison of the MZR for AC114, together with the foreground and background
structures, without any other kind of contamination regarding the ionization
sources.

####  3.3.2 Gas-phase metallicities

The first half of the construction of the MZR was done with optical and NIR
luminosities to estimate the stellar mass of the galaxies. We now continued to
estimate the metallicities of the SF galaxies in the sample.

The best technique to estimate gas-phase metallicities is through measuring
intensities of emission line ratios sensitive to the electron temperature,
$T_{e}$, together with the computation of line emissivities. This technique is
the so-called “direct method” (Peimbert 1967, Aller 1984). However,
$T_{e}-$sensitive emission line ratios involve lines such as the auroral
$\mathrm{[OIII]}\lambda 4363$, $\mathrm{[NII]}\lambda 5755$, or
$\mathrm{[SII]}\lambda\lambda 4068,4076$. These lines are $\sim 3-4$ orders of
magnitude fainter than Balmer emission lines (Maiolino & Mannucci, 2019).
Therefore, auroral lines can be well measured in metal-poor or high-
temperature environments. Otherwise, auroral lines get lost in the noise of
the galactic spectra.

Some alternative methods of estimating metallicities have been proposed; the
so-called “strong-line methods,” calibrated on $T_{e}$-based oxygen abundances
or photoionization models (e.g., Pilyugin 2001, Kobulnicky & Kewley 2004,
Edmunds & Pagel 1984, Ferland et al. 1998, Pérez-Montero 2015). In this work,
we chose the well-known strong-line O3N2 index, defined as
$\mathrm{O3N2}=\log{\left(\frac{\mathrm{[OIII]}\lambda
5007/H\beta}{\mathrm{[NII]}\lambda 6584/H\alpha}\right)}$, which correlates
linearly with oxygen abundances in this way:
$12+\log{(\mathrm{O/H})}=8.73-0.32\times\textup{O3N2}$ (Pettini & Pagel,
2004). There exist at least ten different calibrators in the literature
regarding gas-phase metallicity estimations (see Kewley & Ellison 2008 for a
detailed analysis of the most common calibrators and comparisons between
them). Despite the significant differences between some calibrators (up to 0.7
dex), the authors also provide consistent conversions between different
calibrators within uncertainties of 0.2 dex. Those will also be used in
section 4 to make comparisons with the MZRs reported in the literature.

Figure 8: Baldwin-Philips-Terlevich diagram of the sample. The dashed black
line is the KL at z=0 (Kewley et al. 2001), which excludes pure AGNs. The
solid black line is the Kauffmann et al. (2003) limit, which excludes
composite galaxies (ionization from star formation and AGNs). The red points
are galaxies at the cluster redshift. Black diamonds correspond to foreground
and background galaxies. According to both demarcation limits, all ELGs are SF
galaxies. Data points with blue open diamonds are galaxies classified as
composite galaxies, with two of them being composite galaxies at the cluster
redshift and five of them found outside the cluster redshift.

We chose to estimate metallicities with the O3N2 index for several reasons:
(i) This index is calibrated with $T_{e}-$based oxygen abundances, which is
the most reliable method despite its intrinsic biases such as temperature
fluctuations, underestimations in the high metallicity range, and the way of
estimating the electron temperature (Kobulnicky & Skillman 1996, Pilyugin &
Grebel 2016, Cameron et al. 2023). (ii) The relation between O3N2 and oxygen
abundances is not bi-valued, at odds with, for instance, the R23 index; (iii)
the emission lines used in the O3N2 calibrator are closer together
(H$\beta-\mathrm{[OIII]}\lambda 5007$ in $\sim 150\AA$ and
H$\alpha-\mathrm{[NII]}\lambda 6584$ at $\sim 20\AA$); hence, there are no
significant noise changes in the observed spectra, the internal absorption
does not affect the measurements, and the flux calibration is also less of a
concern. (iv) Our constructed MZRs with field-foreground and field-background
galaxies show oxygen abundances estimates consistent with those expected at
their respective redshifts, despite the intrisic bias of the O3N2 index with
the ionization.

Oxygen abundances of the sample of galaxies are shown in Table 4.4. The
estimated oxygen abundances have values from $8.10\ \pm
0.06<12+\log{(\mathrm{O/H})}_{O3N2}<8.77\ \pm 0.19$ for 54 ($67\%$) SF
galaxies. The other SF galaxies do not have all these four emission lines to
compute their respective metallicities.

##  4 Results

The reported statistical parameters relative to the analysis presented in this
section are listed in Table 1

###  4.1 The MZR of AC114, foreground and background galaxies

Figure 9: Mass-metallicity relations constructed with the SF galaxies of the
sample compared with the local Universe MZR from Tremonti et al. (2004). The
left panel shows the foreground MZR (fMZR) with blue dots and background MZR
(bMZR) with red dots. Lines correspond to linear fits. The shaded area
corresponds to the $1\sigma$ scatter for the fMZR and bMZR. Right panel: MZR
with the SF members of AC114 (cMZR). The black line and shaded area are the
linear fit and the respective $1\sigma$ scatter. The dashed blue and red lines
are the fMZR and bMZR linear fits. The open circles (left) and open circles
(right) show galaxies whose stellar mass was estimated using synthetic
photometry. Figure 10: Comparison between the MZRs constructed in this work
and the literature. Left panel: Comparison between the fMZR, Cresci et al.
(2012) MZR, and the Maiolino parameterization, both at redshift $z\sim 0.25$.
Middle panel: Comparison between the bMZR, Savaglio et al. (2005), Lamareille
et al. (2009), and the Maiolino parameterization at $z\sim 0.7$, respectively.
Right panel: Comparison between the cMZR, Vaughan et al. (2020), and the
Maiolino parameterization at $z\sim 0.3$. Data points with open diamonds show
the galaxies classified as composite in the BPT diagram of Fig. 8.

We constructed the MZRs with 54 SF galaxies for three subsamples labeled:
foreground ($0.1<z<0.28$) with 19 SF galaxies, AC114 ($0.28\leq z\leq 0.34$)
with 20 SF members, and background ($0.34<z<0.7$) with 15 SF galaxies. The
redshift boundaries used were adopted from P15. In Figure 9, the MZRs are
compared with the local Universe MZR from Tremonti et al. (2004). To do the
comparison, we used the Kewley & Ellison (2008) conversion to get the local
Universe MZR in O3N2-based oxygen abundances. The left panel of Figure 9 shows
the MZRs of the foreground and background galaxies. Foreground and background
galaxies’ oxygen abundances correlate with the stellar mass, showing the
existence of foreground and background MZRs (hereafter fMZR and bMZR). The
non-parametric Spearman correlation test was performed for galaxies with
$<1\sigma$ scatter, showing correlation coefficients of $r=0.97$ (p-value
$2.6\times 10^{-8}$) and $r=0.90$ (p-value $1.5\times 10^{-4}$). The $1\sigma$
scatter is $\sigma=0.118$ and $\sigma=0.120$, showing that both the fMZR and
the bMZR are tightly correlated, respectively. Additionally, they are
downshifted by 0.09 and 0.20 dex in metallicities with respect to the local
MZR, a clear sign of evolution with redshift of the global MZR: at a given
mass, higher-redshift galaxies will present lower metal content.

The shallower slope of the fMZR ($0.236\ \pm\ 0.003$) with respect to the bMZR
($0.312\ \pm\ 0.009$) is produced mainly by two physical phenomena: (i)
Galaxies grow hierarchically across the cosmic time, and therefore wet mergers
(i.e., mergers between low-mass galaxies with significant gas fractions) can
enhance the gas-phase metal content, while low-mass galaxies evolve, due to
the production of stars that pollute the ISM with processed material in the
last stages of their evolution (Tissera et al., 2005). (ii) Outflow processes
are stronger at higher redshift, making it easier for gas particles to get
expelled in shallower potential wells (Troncoso et al., 2014). Hence, the
evolution in redshift of the MZR in the low-mass range is stronger than in the
high-mass range, where deeper potential wells will produce a more efficient
star formation. The different mass range of the fMZR and bMZR is a natural
consequence of seeing galaxies in a range of distances with a fixed exposure
time, as is the case with the DECaLS survey and AC114.

We ignored evolution effects (galaxies at higher redshift are in different
stages of their evolution) because we focused our analysis on studying
differences in the shape and the evolution of the MZR. The evolution effects
mainly affect the construction of the bMZR because it represents galaxies at
redshift $0.34<z<0.7$. If we take into account the evolution effects, the
scatter of the bMZR will decrease. However, we would not be able to produce a
significant bMZR because there are not enough galaxies in our sample.

The right panel of Figure 9 presents the MZR constructed at $z\sim 0.3$ with
SF galaxies of the AC114 galaxy cluster (hereafter cMZR). The first clear
feature in the cMZR is that the slope of the linear fit ($0.241\ \pm\ 0.008$)
is slightly shallower than both the fMZR and bMZR slopes (shown with the black
line), with a larger scatter of $\sigma=0.17$ and a Spearman rank of $r=0.65$
(p-value $=0.009$). These values suggest that physical phenomena are
suppressing the chemical evolution of high-mass galaxies, increasing the
observed scatter and weakening the correlation between mass and metallicity.
The second important feature seen is that the high scatter of the cMZR and the
effect in the high-mass range of the shallower slope with respect to the bMZR
indicates that SF members of AC114 are either similar to or metal-poorer than
the background galaxies; the opposite of the expected evolution of the MZR.

Classically, the MZR and its evolution in redshift reported in the literature
is constructed with (i) field SF galaxies and (ii) statistically complete
samples of SF galaxies at a given redshift, where the role of galaxy cluster
environments is negligible. It is well known that at a given mass, gas-phase
metallicities are more metal-poor at higher redshift (or at a given oxygen
abundance, galaxies are less massive at higher redshift). Several physical
phenomena, such as SNe and galactic winds, the infall of pristine gas, outflow
processes, IMF variations, and galactic downsizing, together with the
formation of galaxies through dry or wet mergers, robustly explain the shape
of the MZR. However, all of these are internal physical processes. In dense
environments, such as massive galaxy clusters, galaxies can suffer harassment,
interaction with closer neighbours (galaxy-galaxy interaction), and/or
interaction with the ICM. These external physical processes can change the
gas-mass fraction, modifying the gas-phase metal content. Therefore, these
effects can change the MZR and may explain the cMZR in Figure 9.

###  4.2 Comparison of the fMZR, bMZR, and cMZR with the literature

As a sanity check of the MZRs found above, we proceeded to compare them with
those reported in the literature. The fMZR was compared with Maiolino et al.
(2008) and Cresci et al. (2012). The bMZR was compared with Savaglio et al.
(2005), Maiolino et al. (2008), and Lamareille et al. (2009). Finally, the
cMZR was compared with Maiolino et al. (2008) and Vaughan et al. (2020).

Savaglio et al. (2005), Cresci et al. (2012), and Maiolino et al. (2008) use
the $R_{23}$ parameter to estimate metallicities, whereas Lamareille et al.
(2009) and Vaughan et al. (2020) use the N2 parameter. Therefore, we followed
Kewley & Ellison (2008) to convert $R_{23}$ and N2 to O3N2.

In Maiolino et al. (2008), the authors parameterize the MZR with the
expression $12+\mathrm{log(O/H)}=-0.0864(\log{M_{*}/M_{0}})^{2}+K_{0}$ at
redshifts 0.07, 0.7, 2.2, and 3.5, with $M_{0}$ and $K_{0}$ free variables. We
interpolated both variables as a function of the redshift to get their
parameterization at redshifts 0.25, 0.3, and 0.7.

The left panel of Figure 10 shows the fMZR compared with field MZRs from (i)
Cresci et al. (2012) at $z\sim 0.25$, (ii) the Maiolino parameterization at
$z\sim 0.25$, and (iii) the local Universe MZR of Tremonti et al. (2004). As
we can see, there is an agreement between the fMZR and the literature. The
galaxies that are not in agreement with the MZRs from the literature are, in
fact, those which are beyond the $1\sigma$ scatter. Those foreground galaxies
that are metal-poor with respect to the MZRs in the literature seem to follow
a trend. We discarded that the feature seen is an evolutionary effect because
the galaxies that fall in the MZR have redshifts up to $0.28$, covering the
same range as the outlier galaxies. Three of these four outlier foreground
galaxies are at the same redshift: Q4-7, Q4-8, and Q4-35, at 0.169, 0.169, and
0.170, respectively. Here, Q4-7 and Q4-8 are closer neighbors, sharing the
same region of the FoV. Q4-35 is part of a crowded region in the FoV. On the
other hand, Q3-11 at redshift 0.21 has a closer companion in the FoV but
without available spectroscopic data. The fact that these galaxies are closer
to other ones may indicate that galaxy-galaxy interactions are responsible for
the metal-poor values with respect to the fMZR. This will be discussed in
Section 5.

The middle panel of Figure 10 shows the bMZR compared with field MZRs from (i)
Savaglio et al. (2005), (ii) Lamareille et al. (2009), and (iii) the Maiolino
parameterization at $z\sim 0.7$. In this panel, our measurements are
consistent with those reported in the literature in the high-mass range of the
MZRs. On the other hand, the low-mass galaxies in our sample tend to follow
the Savaglio et al. (2005) MZR. Again, the background galaxies that fall below
the MZRs compared are those that are beyond the $1\sigma$ scatter. From these
two panels, it is clear that the fMZR and bMZR follow the field MZRs at their
respective redshift ranges.

In the right panel of Figure 10, we compare the AC114-MZR (cMZR) with the
Maiolino parameterization and the MZR reported in Vaughan et al. (2020,
hereafter V20), with the dotted and dash-dotted green lines, respectively. V20
studies a sample of four galaxy clusters at $0.3<z<0.6$ and compares their
cluster members with respect to field galaxies in the mass-metallicity plane
at the same redshift. They did not find any difference between those MZRs (see
Figure 7 in V20).

To compare the V20 data with this work, two of the four galaxy clusters were
found at a similar redshift of AC114, MS2137, and MACS1931 at z=0.313 and
z=0.352, respectively. We find that just seven and two galaxies have oxygen
abundances estimated, belonging to MS2137 and MACS1931, respectively. The
field galaxies in V20 at the redshift of AC114 ($0.28<z<0.35$) span masses
from $\sim 10^{10}$ to $\sim 10^{11}M_{\odot}$, whereas our mass estimates in
AC114 cover two orders of magnitude starting from $\sim 10^{9}M_{\odot}$.
Therefore, that sample is not appropriate to compare with our results.

In the right panel of Figure 10, the linear fit of the AC114 galaxy sample
presents a higher downshift than the Maiolino parameterization and V20 with
respect to the local Universe MZR. The cMZR is downshifted 0.19 dex with
respect to the local Universe MZR, and the scatter of the cMZR is 0.17 dex.

The fact that both the fMZR and bMZR are in agreement with field MZRs at their
respective redshifts, together with the cMZR showing a slightly shallower
slope, a downshift similar to the bMZR, and a high scatter of 0.17 dex,
indicates that there are physical phenomena behind those features, which are
likely related to environmental and/or dynamical effects.

###  4.3 Structure of AC114 and consequences for the chemical evolution of its
members

We explored the spatial distribution to gain insights into the changes seen in
the cMZR with respect to the fMZR and the bMZR. We first converted the
projected RA,Dec and redshift coordinates of the cluster members to physical
coordinates. Wright (2006) was used to estimate the respective arcsecond per
kiloparsec scale conversion as a function of the redshift for a few select
values. A second-degree polynomial was fitted, parameterizing the expression:
$\frac{\mathrm{Kpc}}{{}^{\prime\prime}}(z)=-9.800(\pm 0.300)\ z^{2}+16.700(\pm
0.200)\ z+0.335(\pm 0.007)$, with $z\in[0.1,0.7]$. At the cluster distance
$D_{L}=1670\ \pm\ 17$ Mpc, the corresponding scale is $\sim 4.6$ Kpc/′′, and
at the cluster range $0.28<z<0.34$ the scale spans values from $\sim
4.3$Kpc/′′ to $\sim 4.9$Kpc$/^{\prime\prime}$.

AC114 has a nonspherical shape, being elongated in the southeast-northwest
direction (Couch et al. 2001, De Filippis et al. 2004). The dynamical study of
P15 shows also that AC114 is a very elongated radial filament, spanning $12\
000\ \mathrm{km\ s^{-1}}$ with a broad velocity dispersion of $\sim
1893_{-82}^{73}\ \mathrm{km\ s^{-1}}$. These dimensions correspond to $\sim
330\ \mathrm{Mpc}$ in the radial direction and $\sim 9\ \mathrm{Mpc}$ in the
perpendicular component, the latter being a lower limit, as the calculations
are restricted to the FoV of the VIMOS observations.

The three-dimensional representation of the cluster members is shown in Figure
11 for SF and passive galaxies with blue and red dots, respectively. Figure 11
shows that the center of the cluster (at 0,0,0 in X,Y,Z) is populated mostly
by passive galaxies; SF galaxies tend to be found at the outskirts.

The mass and metallicity profiles are presented in Figure 12. The top panel
shows the mass profile of AC114. Just as in Figure 12, we observe a high
concentration of galaxies toward the cluster center, which is dominated by
passive galaxies. A negative radial mass gradient is detected. Black diamonds
are the mean stellar mass of the galaxies in bins of $\sim 23\ $Mpc. The slope
of the mass profile of $-0.005\pm 0.002$ (Spearman rank is $-0.57$, p-value
$=0.005$) shows a weak but statistically significant trend to find massive
galaxies in the inner regions of the cluster. This is consistent with AC114
being in an early stage of radial relaxation, as is also suggested by the
large velocity dispersion estimated in P15. Furthermore, passive galaxies
present a slightly flatter slope (-0.004 $\pm$ 0.003, red linear fit) compared
with SF galaxies (-0.007 $\pm$ 0.003, blue linear fit), which is indicative of
ongoing dynamical activity in the galaxy cluster. The bottom panel of Figure
12 presents a weak, non-statistically significant (Spearman rank of $-0.38$
with a p-value $=0.11$) metallicity gradient of the SF galaxies, with a slope
of $-0.002\ \pm\ 0.002$.

Figure 11: Three-dimensional projection of the AC114 members, expressed in Mpc
with respect to the cluster center. The x, y, and z axes correspond to the
RA,Dec coordinates and to the redshift, respectively. Blue and red points are
SF and passive galaxies, respectively. Colored crosses are the projected
distribution of the cluster sample in the xz plane. The black cross indicates
the center of the galaxy cluster.

Figure 12: Radial profiles of AC114. Top panel: Stellar masses of galaxies as
a function of the clustercentric radius. Blue and red crosses are SF and
passive galaxies. Black diamonds represent mean mass bins of $\sim 23\
\mathrm{h^{-1}\ Mpc}$. Black, blue, and red lines are the linear fits that
show a negative mass-gradient as a function of the clustercentric radius for
the complete sample, SF, and passive galaxies, respectively. Bottom panel:
Metallicity profile of the SF galaxies with available mean metallicity
estimations. Black diamonds are mean metallicities in bins of $\sim 33\
\mathrm{h^{-1}\ Mpc}$, and the black line is the linear fit that shows a weak
negative gradient.

We applied a kernel density estimator (KDE) to the redshift distribution of
the galaxy cluster to search for possible substructures and construct the MZR
of the sub-components. We made use of the machine-learning KernelDensity
algorithm from the Scikit-learn package666https://scikit-
learn.org/stable/index.html and used a linear kernel model. Three
substructures were identified in the redshift distribution with this
procedure. The red lines in the top panel of Figure 13 show the redshift
limits of the substructures, namely SS1 ($0.2850\leq z<0.3029$) being the
front part of the galaxy cluster with three SF galaxies, SS2 ($0.3029\leq
z<0.3243$) for the main component of AC114 with ten SF galaxies, and SS3
($0.3243\leq z<0.3380$) being the back part of the galaxy cluster with six SF
galaxies.

Once the substructures were identified, we went ahead to construct the
respective MZRs. The bottom panel of Figure 13 shows the SF galaxies of the
substructures in the mass-metallicity plane. Sky blue, black, and red are
colors for SS1, SS2, and SS3, respectively. From SS1, only three SF galaxies
were identified, grouped in the same region of the mass-metallicity plane. A
statistically significant positive correlation is detected for SS3 (slope of
0.26 $\pm$ 0.14, Spearman rank $r=0.860$, and p-value $=0.019$, black dots).
Furthermore, most of the galaxies in the sub-sample lie below the cMZR,
suggesting that outskirt galaxies of AC114 are slowly evolving due to external
processes that are suppressing the chemical evolution. On the other hand, the
main component of AC114 (SS2) shows more scatter (0.28 and 0.33 for SS3 and
SS2, respectively) in the mass-metallicity plane (red dots). The slope of the
fit of SS2 is 0.19 $\pm$ 0.13, and no statistically significant trend is seen
(Spearman rank of = 0.54, p-value = 0.13). The central region of AC114
consists of ten SF galaxies and 42 passive galaxies. Therefore, SF galaxies
closer to the central region of AC114 are suffering not only from interaction
with the ICM, but also more likely to be suffering from interaction with their
neighbors.

In the previous subsection we were able to estimate clustercentric radial
distances, so we repeated the same KDE procedure but applying it to the
clustercentric radial distribution of AC114 galaxies. We divided the galaxies
according to the following radial ranges (blue lines in the top panel of
Figure 14): the central region at $r\leq 32.5\ h^{-1}$Mpc with four SF
galaxies, the intermediate region between $32.5\leq r<57.4\ $Mpc with seven SF
galaxies, and the outskirts of AC114 in $r>57.4\ $Mpc with eight SF galaxies.

The bottom panel of Figure 14 shows the SF galaxies of AC114 in the mass-
metallicity plane colored with green, black, and blue for the central,
intermediate, and external regions, respectively. Despite the central region
only having four galaxies, two of them are the metal-richer ones of the galaxy
cluster. On the other hand, the intermediate and outskirt regions of AC114
show an increase in oxygen abundances with the increase in the stellar mass,
with a slope of 0.35 $\pm$ 0.08, Spearman rank $r=0.86$, and $p-$value
$=0.014$, and a slope of 0.162 $\pm$ 0.09, Spearman rank $r=0.40$, and
$p-$value $=0.319$, respectively.

Figure 13: Top panel: Kernel density estimator in the redshift distribution of
the galaxy cluster region: $0.28\leq z\leq 0.34$. Red lines show the redshift
cuts of the three substructures identified: SS1 in $0.2850\leq z<0.3029$, SS2
with $0.3029\leq z<0.3243$, and SS3 covering $0.3243\leq z<0.3380$. Vertical
black segments are the clustercentric radial distance of the galaxies. Bottom
panel: Galaxies of the three substructures in the mass-metallicity plane. Sky-
blue triangles, black dots, and red dots represent SS1, SS2, and SS3,
respectively. The black line is the cMZR.

Figure 14: Same as Figure 13, but in this instance the KDE was applied in the
radial distribution. Top panel: Kernel density estimator in the radial
distribution of the galaxy cluster. Blue lines show radial cuts at $r=32.5$,
$r=57.4$, and $r=140\ $Mpc. The vertical black segments are the clustercentric
radial distances of the galaxies. Bottom panel: Galaxies in the mass-
metallicity plane of the three radial regions. Green triangles, black dots,
and blue dots represent the central, intermediate, and outskirt regions,
respectively.

##  5 Discussion

P15 and S23 studied the dynamical state of AC114 and the stellar populations
of the cluster members. The radial profiles in Figure 12 show a negative mass
gradient as a function of the clustercentric radius, consistent with the
cluster being in an early stage of radial relaxation, as is also suggested by
P15. The steeper mass gradient up to $r\sim 130\ \mathrm{Mpc}$ of SF members
suggests that these galaxies are more sensitive to the ongoing dynamical
processes of AC114 because of their lower masses with respect to the passive
ones. Both the cMZR and the bMZR shown in Figure 9 are downshifted with
respect to the local Universe MZR, showing that AC114 SF members are more
metal-poor than the field galaxies at the same redshift, and similar in terms
of metallicity to background galaxies at a given mass.

S23, studying stellar populations of SF and passive galaxies, has shown that
the stellar MZR of AC114 is steeper than for galaxies in the local Universe.
However, the gas-phase cMZR in Figure 9 has a shallower slope than galaxies in
the local Universe. This could be due to galaxies quenching by (i)
strangulation (Larson et al. 1980, Peng et al. 2015), where the gas is
consumed faster when there is no fresh supply, and (ii) the ICM is boosting
the metal-poor inflows. By adding our analysis to that reported in S23,
stellar metallicities are lower than gas-phase metallicities because those
metals were produced in the past, while the gas-phase metallicities are
present-day ones. Therefore, the SF galaxies should be in an early stage of
the quenching.

When cluster members were separated into substructures, important imprints of
environmental effects were revealed. Figures 13 and 14 shows that galaxies
located outside the central region set the slope of the cMZR (red and black
dots in Figure 13, and blue and black dots in Figure 14). Star-forming
galaxies within the main component of AC114 and the central region do not show
a correlation between mass and gas-phase metallicity, with a large scatter.

The MZRs of SF galaxies in massive clusters ($>10^{14}M_{\odot}$) appear to
follow those of field galaxies at their corresponding redshift. For example,
Vaughan et al. (2020), studying four CLASH clusters, namely MACS2129,
MACS1311, MACS1931, and MS2131 ($M_{200}\sim 10^{14}-10^{15}\ M_{\odot}$;
Tiley et al. 2020), in the redshift range $z\sim 0.2-0.6$, indicate that in
these clusters the MZRs do not show any changes with respect to that
constructed with field SF galaxies. Additionally, Lara-López et al. (2022) and
Gupta et al. (2016), by using SF members of the Fornax cluster ($M_{vir}\sim
7\times 10^{13}M_{\odot}$; Drinkwater et al. 2001) and the RX J1532$+$30
($z\sim 0.35$, $M_{vir}\sim 6.4\times 10^{14}M_{\odot}$) galaxy cluster,
respectively, are also consistent, with no variations with respect to the
field MZR. However, these works report flatter galactic metallicity gradients,
negative cluster metallicity gradients, and a negative trend in the residuals
of the MZRs as a function of the clustercentric radius. Several physical
processes are discussed, but the main physical phenomena that drive those
trends are strangulation and RPS.

It is well known that RPS is the physical result of the galaxy-ICM interaction
that affects the outskirts of galaxy disks: in the presence of negative
metallicity gradients, the stripped-out gas is metal-poorer than their nuclei,
which leads to increased oxygen abundances.

Strangulation is produced when the pristine gas inflow ends and the gas
reservoir is consumed faster, increasing the SFR until the quenching begins.
Therefore, the H$\alpha$ disks become smaller than the stellar disks, and
oxygen abundances are more metal-rich than galaxies that do not experience
galaxy-ICM interactions at the same mass.

On the other hand, galaxy clusters such as Coma, Hercules (A2151),
MACSJ1115+01, and those in the SDSS DR4 survey, show enhanced metallicities
with respect to the field MZR, up to $\sim 0.05$ dex in galaxies affected by
RPS and/or galaxy-galaxy interactions inside the virial radius of their host
dark matter halos (Ellison et al. 2009, Petropoulou et al. 2011, Petropoulou
et al. 2012, Gupta et al. 2016). This indicates that extremely dense
environments, such as galaxy clusters with $M_{vir}>10^{15}M_{\odot}$, may
show variations in the cluster MZRs with respect to the field ones.

The MZR of AC114 also shows this feature for at least two cluster members when
it is compared with the field MZR at $z\sim 0.3$, as is indicated in Figure
10. In this case, we used the Maiolino parameterization at redshift $0.3$ to
compare with the AC114-MZR. However, the two galaxies are more metal-rich,
$\sim 0.10$ dex, which is more than that reported by Ellison et al. (2009).
Additionally, the other galaxies (below the linear fit of the cMZR with the
red line) drive the shallower slope and have lower metallicities than the
field SF galaxies at the same redshift up to $\sim 0.22$ dex. The striking
feature is that these galaxies are located outside the central region of AC114
(see Figure 14). Several reasons can explain this feature: (i) the AGN
feedback, which is important at low $z$, can expel the metal-rich gas
component in the central region of SF members with negative metallicity
gradients (De Rossi et al. 2017, Wang et al. 2023); (ii) the presence of
strong metal-poor inflows (Finlator & Davé 2008, Ceverino et al. 2016), where
galaxies accreting metal-poor gas decrease their average metallicities; and
(iii) mergers and tidal interactions, where the interaction with closer
companions can dilute the gas-phase metallicities.

In order to understand the main physical phenomena behind the metal-poor
content of the SF galaxies of AC114 with respect to the field MZR at the same
redshift, the AGN feedback can be discarded because our cluster sample has
just two composite galaxies. One of them is over the local Universe MZR, and
the other shows the largest deviation below the MZR in the cluster sample.
According to Kauffmann et al. (2003), the location of these two composite
galaxies in the mass-metallicity plane can be explained as the former being a
LINER-composite galaxy and the latter a Seyfert-composite galaxy.
Additionally, Seyfert galaxies have stronger [OIII]$\lambda 5007$ emission
lines than SF galaxies. The O3N2 index anticorrelates linearly with the oxygen
abundances, so it may explain the location of this galaxy in the mass-
metallicity plane. The same applies to the LINER galaxy in our cluster sample,
but in this case, LINERS have strong [NII]$\lambda 6584$ emission lines.
According to observation and simulations from Zahid et al. (2014) and Wang et
al. (2023), despite the AGN feedback being important at low redshift, for
satellite galaxies (non-cDs in galaxy clusters) this effect is negligible.

On the other hand, a strong metal-poor inflow and dynamical events can explain
the observed feature. Montuori et al. (2010), simulating mergers and flybys
between disk galaxies, showed that galaxy-galaxy interactions can dilute gas-
phase metallicities and also increase the SFR, due to the accretion of metal-
poor gas from galaxies with negative metallicity gradients. The estimated
dilution agrees with Kewley et al. (2006), which reports that galaxy pair
interaction dilutes gas-phase metallicities up to $\sim 0.2-0.3$ dex. Those
values are also in line with the downshifts of the outlier foreground galaxies
with respect to the fMZR, which are $\sim 0.18$ on average. Additionally,
Montuori et al. (2010) also explain that galaxy-galaxy interaction increases
the gas-phase metallicities after the dilution due to the increase in the
SFRs. Therefore, this mechanism increases the scatter of the MZR, as is also
seen in Rupke et al. (2008).

This scenario is also supported by ongoing dynamical activity (P15) and by the
fact that this galaxy cluster has an extended soft X-ray tail, together with
the hardness ratio map, which suggests that this cluster has an ongoing merger
activity with a smaller structure (De Filippis et al. 2004).

##  6 Summary and conclusions

We explored the role of galaxy clusters in the MZR through SF galaxies of the
AC114 galaxy cluster. We analyzed optical, intermediate-resolution VIMOS/VLT
spectra for a sample of 182 galaxies in the FOV of AC114.

The search in photometric catalogues allowed us to get optical and NIR
luminosities for $76\%$ and $66\%$ of the galaxies of the sample from the
DECaLS DR10 and VIKING DR4 ESO surveys, respectively. Synthetic photometry was
performed using the VIMOS spectra when optical photometry was missing. Optical
and NIR-based stellar masses of the galaxies were estimated via theoretical
stellar mass-to-light ratios computed from the E-MILES models by considering
the age dependence for both sdss$-i$ and $K_{s}$ band passes. A comparison
between optical and NIR-based mass estimations shows agreement between them
for SF galaxies, but there is a slight deviation in massive, passive galaxies
of 0.23 dex. However, the offset is within the propagated uncertainties of
$\sigma=0.29$ mags, so it does not change our results.

We classified the galaxies into ELGs and passive galaxies, based on the
presence or absence of $\mathrm{[OII]\lambda 3727}$,
$\mathrm{[OIII]\lambda\lambda 4959,5007}$, H$\beta$, and H$\alpha$ emission
lines, respectively. Using the BPT diagram, together with the Kewley et al.
(2001) and Kauffmann et al. (2003) demarcation limits, we found that the
galaxy sample has seven composite galaxies, where two of them (a Seyfert
composite and a LINER composite) are cluster members. The remaining galaxies
in the sample are, in fact, pure SF galaxies.

Gas-phase metallicities were estimated from the O3N2, which are calibrated on
$T_{e}-$based metallicities.

Our main conclusions can be summarized as follows:

  * •

Foreground and background MZRs span masses from $10^{8.7}$ to
$10^{10.3}M_{\odot}$ and $10^{9.4}$ to $10^{10.7}M_{\odot}$, respectively,
with both the fMZR and the bMZR showing a scatter of $\sim$0.12 dex. The fMZR
was constructed with less-massive galaxies than bMZR due to an observational
bias. However, the downshifts reported show a coherent evolution in redshift
of the MZR, where foreground galaxies are 0.09 dex metal-poorer, and
background galaxies are 0.20 dex metal-poorer on average with respect to the
local Universe galaxies.

  * •

The AC114-MZR presents different features with respect to field galaxies at
similar redshifts. The cMZR span masses from $10^{9.2}$ to
$10^{10.8}M_{\odot}$, with 0.17 dex of scatter. A downshift of 0.19 dex on
average and a slightly shallower slope is seen with respect to both the fMZR
and the bMZR. This shows that, in general, AC114 SF galaxies have lower
metallicities at the same mass than field galaxies at the same redshift. The
metallicity measurements of the SF cluster members are comparable to the
background galaxies in our galaxy sample. Besides, star-forming galaxies
within the main component of AC114 and the central region do not show a
correlation between mass and gas-phase metallicity, with a large scatter. This
gives important clues about the environmental effects that are suppressing the
chemical evolution of these galaxies.

  * •

The mass and metallicity profiles as a function of the clustercentric radius
show that AC114 started its radial relaxation phase, in agreement with Proust
et al. (2015). The negative mass gradient suggests that SF galaxies are the
most sensitive to the dynamical state of the galaxy cluster. Additionally, the
negative (although not statistically significant) metallicity gradient can be
a sign that massive galaxies located near the central region of AC114 are
slightly more metal-rich than those found in external regions.

  * •

The substructures identified with the KDE show that for SF galaxies in the
outskirts of the galaxy cluster the metallicity is dependent on the stellar
mass. Moreover, these galaxies are responsible for the shallower slope of the
cMZR (compared with the field MZR at $z\sim 0.3$), which means that these
galaxies are also the more metal-poor ones.

  * •

When the cMZR is compared with the field MZR at $z\sim 0.3$, two galaxies are
located above the field MZR by $\sim 0.10$ dex. This feature is consistent
with the literature, which suggests that galaxies are suffering from RPS,
strangulation, and/or galaxy-galaxy interactions.

  * •

Galaxies falling below the linear fit of the cMZR are the drivers of the
shallower slope. These galaxies are also found outside the central region of
AC114. This means that outskirt galaxies are evolving slowly in terms of their
chemical content, showing metallicities up to $0.22$ dex lower than the local
Universe galaxies and on average $0.17$ dex lower than the field MZR at $z\sim
0.3$. Strong metal-poor inflows produced by dynamical events such as galaxy-
galaxy interactions may explain the strikingly low metallicities of the SF
members of AC114. This scenario is also supported by the dynamical state of
the cluster and the ongoing merger event between the main component of AC114
and a smaller structure, observed in the X-rays.

  * •

We emphasize the role of the mass of a galaxy cluster. Environmental and
dynamical effects drive the chemical evolution of members in a unique way with
respect to field galaxies. However, only galaxy clusters with
$M>10^{15}M_{\odot}$ appear to show observable changes in the MZR.

###### Acknowledgements.

We thank to the anonymous referee for their useful comments which improved the
quality of the paper. A special thanks goes to the Dr. Piercarlo Bonifacio for
the feedback presented in the early stage of this research. Additionally, we
want to thanks Felipe Vivanco and Gustavo Worner, for the opportunity to
discuss our results and for the valuable contributions to the development of
the Python scripts used in this work. This publication is based on
observations collected at the European Southern Observatory under ESO
programme ID 083.A-0566. Also, this program has made use of data from the
VIKING survey from VISTA at the ESO Paranal Observatory, programme ID
179.A-2004. Data processing has been contributed by the VISTA Data Flow System
at CASU, Cambridge and WFAU, Edinburgh.

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##  Appendix A Tables:

Table 1: Compilation of all statistical parameters of the fits performed in Figures 9, 12, 13, and 14. First column: Corresponding figure. Second column: Fitted structure (e.g., the cluster MZR, or the SF mass profile). Third column: Slope of the linear fit. Fourth column: 1$\sigma$ scatter of the distribution. Fifth column: Spearman correlation test. Sixth column: $p-$value of the Spearman correlation test. Figure | Structure | Slope | $\sigma$ |  $r$ (Spearman rank) |  $p-$value
---|---|---|---|---|---
9 | fMZR | 0.236 $\pm$ 0.003 | 0.118 | 0.97 | 2.6 $\times\ 10^{-8}$
9 | bMZR | 0.312 $\pm$ 0.009 | 0.120 | 0.90 | 1.5 $\times\ 10^{-4}$
9 | cMZR | 0.241 $\pm$ 0.008 | 0.170 | 0.65 | 0.009
12 | Mass profile | -0.005 $\pm$ 0.002 | 0.540 | -0.57 | 0.005
12 | SF mass profile | -0.007 $\pm$ 0.003 | 0.470 | -0.50 | 0.020
12 | Pasive mass profile | -0.004 $\pm$ 0.003 | 0.520 | -0.24 | 0.090
12 | Metallicity profile | -0.002 $\pm$ 0.002 | 0.190 | -0.38 | 0.110
13 | SS2 (cMZR) | 0.192 $\pm$ 0.129 | 0.330 | 0.54 | 0.125
13 | SS3 (cMZR) | 0.269 $\pm$ 0.135 | 0.280 | 0.86 | 0.019
14 | Middle region (cMZR) | 0.352 $\pm$ 0.078 | 0.270 | 0.86 | 0.014
14 | External region (cMZR) | 0.162 $\pm$ 0.096 | 0.350 | 0.40 | 0.319
Table 2: Compilation of photometric data collected from DECaLS DR10 and VIKING DR4. Column one indicates the IDs of the galaxies, labeled according to $\\#$quadrant$-\\#$slit. Galaxies that were not identified in previous works with the same spectroscopic VIMOS data are labeled with $\\#$quadrant$-A$(Additional). RA and Dec coordinates are shown in columns two and three. Redshift estimates in column four. Optical apparent magnitudes are listed in columns five and six. NIR apparent magnitudes are listed in column seven. Column eight indicates the classification of passive galaxies and ELGs: passive galaxies are listed with 0 and ELGs with 1. ID | RA | Dec | z | $i$ | $g$ | $K_{s}$ | ELGs
---|---|---|---|---|---|---|---
Q1-3 | 344.889 | -34.711 | 0.057330$\pm$0.000014 |  |  |  | 1
Q1-A1 | 344.877 | -34.713 | 0.277520$\pm$0.000054 |  |  |  | 1
Q1-5 | 344.884 | -34.716 | 0.057850$\pm$0.000012 |  |  |  | 1
Q1-A2 | 344.815 | -34.721 | 0.289160$\pm$0.000022 |  |  |  | 0
Q1-8 | 344.902 | -34.724 | 0.379530$\pm$0.000015 |  |  |  | 1
Q1-9 | 344.858 | -34.726 | 0.416980$\pm$0.000011 | 22.2$\pm$0.6 |  | 17.80$\pm$0.16 | 0
Q1-10 | 344.827 | -34.729 | 0.219600$\pm$0.000017 | 18.7$\pm$0.5 | 20.3$\pm$0.8 | 15.78$\pm$0.03 | 1
Q1-11 | 344.823 | -34.733 | 0.282340$\pm$0.000007 | 21.6$\pm$0.6 | 23.7$\pm$1.1 | 18.46$\pm$0.24 | 0
Q1-12 | 344.833 | -34.736 | 0.220480$\pm$0.000016 | 19.6$\pm$0.4 | 20.4$\pm$0.8 | 17.13$\pm$0.15 | 1
Q1-A3 | 344.800 | -34.740 | 0.271680$\pm$0.000007 |  |  |  | 1
Q1-15 | 344.867 | -34.741 | 0.071500$\pm$0.000013 | 21.5$\pm$0.6 | 21.9$\pm$1.0 |  | 1
Q1-16 | 344.870 | -34.746 | 0.408880$\pm$0.000021 | 21.7$\pm$0.5 | 23.7$\pm$1.0 | 18.16$\pm$0.24 | 0
Q1-17 | 344.910 | -34.748 | 0.342210$\pm$0.000007 |  |  |  | 0
Q1-18 | 344.846 | -34.751 | 0.312460$\pm$0.000020 | 21.2$\pm$0.6 | 22.4$\pm$1.1 | 18.31$\pm$0.18 | 1
Q1-19 | 344.827 | -34.754 | 0.408190$\pm$0.000009 | 21.4$\pm$0.5 | 22.5$\pm$1.0 | 18.97$\pm$0.34 | 1
Q1-20 | 344.918 | -34.756 | 0.231980$\pm$0.000016 |  |  |  | 0
Q1-A4 | 344.897 | -34.757 | 0.357780$\pm$0.000010 |  |  |  | 0
Q1-22 | 344.853 | -34.760 | 0.409870$\pm$0.000019 | 19.0$\pm$0.4 | 21.5$\pm$0.8 | 15.92$\pm$0.04 | 1
Q1-24 | 344.869 | -34.764 | 0.333100$\pm$0.000005 | 19.3$\pm$0.4 | 20.8$\pm$0.8 | 16.52$\pm$0.06 | 0
Q1-25 | 344.896 | -34.766 | 0.414380$\pm$0.000192 | 20.5$\pm$0.5 | 22.1$\pm$1.0 | 17.73$\pm$0.17 | 1
Q1-26 | 344.883 | -34.770 | 0.417650$\pm$0.000038 | 21.3$\pm$0.5 | 22.9$\pm$1.0 | 17.91$\pm$0.14 | 0
Q1-27 | 344.884 | -34.773 | 0.390830$\pm$0.000017 | 22.1$\pm$0.5 | 23.5$\pm$0.9 |  | 0
Q1-28 | 344.859 | -34.776 | 0.343650$\pm$0.000011 | 19.1$\pm$0.3 | 19.8$\pm$0.6 | 17.15$\pm$0.12 | 0
Q1-30 | 344.900 | -34.779 | 0.318050$\pm$0.000014 | 19.1$\pm$0.4 | 21.1$\pm$0.8 | 15.30$\pm$0.02 | 1
Q1-31 | 344.890 | -34.780 | 0.331760$\pm$0.000021 | 20.6$\pm$0.6 | 22.6$\pm$1.0 | 17.34$\pm$0.12 | 0
Q1-34 | 344.855 | -34.785 | 0.301330$\pm$0.000011 | 20.3$\pm$0.6 | 22.4$\pm$1.0 | 17.04$\pm$0.08 | 0
Q1-36 | 344.892 | -34.789 | 0.498080$\pm$0.000010 | 20.7$\pm$0.5 | 22.2$\pm$0.8 | 18.75$\pm$0.20 | 0
Q1-37 | 344.849 | -34.791 | 0.315480$\pm$0.000042 | 19.5$\pm$0.6 | 21.2$\pm$1.0 | 16.51$\pm$0.05 | 1
Q1-A5 | 344.799 | -34.793 | 0.343630$\pm$0.000018 | 21.0$\pm$0.4 | 22.8$\pm$0.7 | 16.96$\pm$0.09 | 0
Q1-38 | 344.825 | -34.794 | 0.485360$\pm$0.000018 |  |  |  | 1
Q1-40 | 344.847 | -34.799 | 0.323390$\pm$0.000019 | 19.1$\pm$0.3 |  | 16.29$\pm$0.05 | 1
Q1-41 | 344.820 | -34.802 | 0.576610$\pm$0.000008 |  |  | 17.09$\pm$0.08 | 0
Q1-A6 | 344.871 | -34.808 | 0.289270$\pm$0.000014 |  |  |  | 0
Q1-44 | 344.816 | -34.812 | 0.576030$\pm$0.000009 | 21.6$\pm$0.4 | 23.1$\pm$0.7 |  | 1
ID | RA | Dec | z | $i$ | $g$ | $K_{s}$ | ELGs
---|---|---|---|---|---|---|---
Q2-1 | 344.817 | -34.561 | 0.259580$\pm$0.000022 |  |  |  | 1
Q2-2 | 344.825 | -34.564 | 0.334680$\pm$0.000010 |  |  |  | 0
Q2-3 | 344.824 | -34.566 | 0.409690$\pm$0.000012 |  |  |  | 1
Q2-4 | 344.806 | -34.570 | 0.408470$\pm$0.000019 |  |  |  | 1
Q2-5 | 344.812 | -34.573 | 0.256670$\pm$0.000559 |  |  |  | 0
Q2-6 | 344.849 | -34.576 | 0.423330$\pm$0.000025 | 18.9$\pm$0.4 | 21.0$\pm$0.7 | 15.80$\pm$0.05 | 0
Q2-7 | 344.839 | -34.578 | 0.242100$\pm$0.000610 | 22.1$\pm$0.7 | 25.2$\pm$1.1 | 19.45$\pm$0.52 | 0
Q2-8 | 344.803 | -34.580 | 0.445090$\pm$0.000009 | 21.6$\pm$0.6 | 22.7$\pm$1.0 | 18.88$\pm$0.29 | 0
Q2-9 | 344.823 | -34.582 | 0.370950$\pm$0.000048 | 22.1$\pm$0.6 | 23.2$\pm$1.1 |  | 1
Q2-10 | 344.828 | -34.584 | 0.408990$\pm$0.000012 | 21.3$\pm$0.7 | 23.4$\pm$1.1 | 17.04$\pm$0.12 | 1
Q2-11 | 344.820 | -34.586 | 0.298630$\pm$0.000016 | 22.1$\pm$0.4 | 22.9$\pm$0.8 |  | 1
Q2-12 | 344.886 | -34.590 | 0.370700$\pm$0.000016 | 21.1$\pm$0.5 | 22.9$\pm$0.9 | 17.69$\pm$0.19 | 0
Q2-13 | 344.859 | -34.592 | 0.360210$\pm$0.000047 |  |  |  | 0
Q2-14 | 344.834 | -34.595 | 0.373620$\pm$0.000044 | 20.7$\pm$0.4 | 22.6$\pm$0.9 | 17.73$\pm$0.15 | 0
Q2-15 | 344.815 | -34.598 | 0.410010$\pm$0.000133 | 21.7$\pm$0.6 | 23.9$\pm$1.1 | 18.37$\pm$0.20 | 0
Q2-16 | 344.829 | -34.600 | 0.573910$\pm$0.000024 | 21.3$\pm$0.4 | 23.5$\pm$0.9 | 18.48$\pm$0.27 | 1
Q2-A1 | 344.833 | -34.605 | 0.267590$\pm$0.000278 |  |  |  | 0
Q2-18 | 344.800 | -34.608 | 0.345920$\pm$0.000037 | 21.1$\pm$0.5 | 23.2$\pm$0.9 | 17.98$\pm$0.17 | 0
Q2-19 | 344.830 | -34.611 | 0.377380$\pm$0.000030 | 19.3$\pm$0.4 | 21.5$\pm$0.8 | 16.37$\pm$0.05 | 0
Q2-A2 | 344.855 | -34.612 | 0.466710$\pm$0.000057 |  |  |  | 0
Q2-21 | 344.840 | -34.615 | 0.413680$\pm$0.000105 | 20.5$\pm$0.5 | 22.5$\pm$0.8 | 17.45$\pm$0.11 | 0
Q2-22 | 344.903 | -34.615 | 0.391390$\pm$0.000022 |  |  |  | 1
Q2-23 | 344.839 | -34.619 | 0.413930$\pm$0.000038 | 19.5$\pm$0.5 | 22.1$\pm$0.9 | 16.31$\pm$0.04 | 0
Q2-24 | 344.903 | -34.623 | 0.380780$\pm$0.000055 | 22.1$\pm$0.6 | 23.2$\pm$1.0 |  | 1
Q2-A3 | 344.834 | -34.625 | 0.429260$\pm$0.000014 |  |  |  | 0
Q2-26 | 344.801 | -34.627 | 0.487890$\pm$0.000018 | 21.5$\pm$0.5 | 23.2$\pm$0.9 | 19.30$\pm$0.48 | 1
Q2-27 | 344.837 | -34.629 | 0.497530$\pm$0.000033 | 20.3$\pm$0.5 | 22.1$\pm$0.9 | 17.11$\pm$0.11 | 1
Q2-28 | 344.814 | -34.633 | 0.613460$\pm$0.000019 | 20.4$\pm$0.3 | 21.7$\pm$0.6 | 17.36$\pm$0.17 | 1
Q2-29 | 344.823 | -34.634 | 0.523020$\pm$0.000010 | 20.6$\pm$0.2 |  | 17.90$\pm$0.21 | 1
Q2-31 | 344.852 | -34.638 | 0.497110$\pm$0.000022 |  |  |  | 0
Q2-A4 | 344.866 | -34.638 | 0.497370$\pm$0.000008 |  |  |  | 1
Q2-32 | 344.854 | -34.643 | 0.308930$\pm$0.000018 |  |  | 18.13$\pm$0.23 | 1
Q2-33 | 344.819 | -34.645 | 0.579620$\pm$0.000006 |  |  | 17.52$\pm$0.11 | 1
Q2-A5 | 344.926 | -34.648 | 0.345720$\pm$0.000017 |  |  |  | 0
Q2-35 | 344.919 | -34.651 | 0.313670$\pm$0.000056 | 19.7$\pm$0.6 | 21.9$\pm$1.1 | 16.51$\pm$0.04 | 0
Q2-36 | 344.857 | -34.653 | 0.465160$\pm$0.000210 | 20.2$\pm$0.6 | 22.2$\pm$1.0 | 17.42$\pm$0.11 | 1
Q2-37 | 344.808 | -34.659 | 0.139900$\pm$0.000017 | 20.4$\pm$0.4 | 21.2$\pm$0.7 |  | 1
Q2-38 | 344.846 | -34.663 | 0.298510$\pm$0.000033 | 21.5$\pm$0.6 | 22.7$\pm$1.0 | 19.46$\pm$0.46 | 1
Q2-39 | 344.912 | -34.665 | 0.371870$\pm$0.000021 | 20.6$\pm$0.6 | 21.7$\pm$1.1 | 17.88$\pm$0.16 | 1
Q2-40 | 344.901 | -34.666 | 0.420140$\pm$0.000154 | 20.9$\pm$0.6 | 23.0$\pm$1.0 | 18.49$\pm$0.31 | 0
Q2-41 | 344.932 | -34.669 | 0.540080$\pm$0.000014 | 21.3$\pm$0.6 | 23.3$\pm$1.0 | 18.04$\pm$0.22 | 0
ID | RA | Dec | z | $i$ | $g$ | $K_{s}$ | ELGs
---|---|---|---|---|---|---|---
Q3-1 | 344.673 | -34.555 | 0.329830$\pm$0.000060 | 21.4$\pm$0.6 | 22.5$\pm$1.1 | 19.04$\pm$0.40 | 1
Q3-2 | 344.672 | -34.557 | 0.330890$\pm$0.000003 | 18.8$\pm$0.5 | 20.1$\pm$0.8 | 15.78$\pm$0.04 | 1
Q3-3 | 344.667 | -34.559 | 0.331850$\pm$0.000079 | 19.1$\pm$0.6 | 21.3$\pm$1.0 | 15.96$\pm$0.03 | 0
Q3-4 | 344.667 | -34.561 | 0.212750$\pm$0.000021 | 20.9$\pm$0.7 | 22.1$\pm$1.1 | 18.49$\pm$0.26 | 1
Q3-5 | 344.671 | -34.563 | 0.331820$\pm$0.000056 | 21.0$\pm$0.5 | 22.2$\pm$1.0 | 18.49$\pm$0.36 | 1
Q3-6 | 344.641 | -34.564 | 0.495360$\pm$0.000019 |  |  |  | 0
Q3-A1 | 344.695 | -34.566 | 0.315910$\pm$0.000481 |  |  |  | 0
Q3-8 | 344.678 | -34.573 | 0.400050$\pm$0.000009 |  |  |  | 1
Q3-10 | 344.594 | -34.576 | 0.308500$\pm$0.000136 | 18.5$\pm$0.3 | 19.4$\pm$0.5 | 16.83$\pm$0.13 | 0
Q3-11 | 344.650 | -34.579 | 0.212680$\pm$0.000023 | 20.8$\pm$0.7 | 21.5$\pm$1.1 | 18.78$\pm$0.34 | 1
Q3-12 | 344.654 | -34.582 | 0.310390$\pm$0.000230 | 20.0$\pm$0.5 | 21.2$\pm$0.8 | 17.49$\pm$0.21 | 1
Q3-A2 | 344.685 | -34.587 | 0.497010$\pm$0.000009 |  |  |  | 0
Q3-15 | 344.671 | -34.589 | 0.415820$\pm$0.000014 |  |  |  | 0
Q3-16 | 344.691 | -34.591 | 0.176550$\pm$0.000028 | 21.9$\pm$0.5 | 22.7$\pm$1.1 |  | 1
Q3-17 | 344.702 | -34.594 | 0.497500$\pm$0.000019 | 22.6$\pm$0.6 | 24.8$\pm$1.1 | 19.42$\pm$0.44 | 1
Q3-18 | 344.735 | -34.596 | 0.221070$\pm$0.000019 | 19.5$\pm$0.4 | 20.5$\pm$0.8 | 17.24$\pm$0.14 | 1
Q3-19 | 344.597 | -34.599 | 0.159050$\pm$0.000011 | 18.6$\pm$0.4 | 19.6$\pm$0.6 | 15.88$\pm$0.06 | 0
Q3-20 | 344.635 | -34.602 | 0.354770$\pm$0.000036 | 23.1$\pm$0.5 | 24.3$\pm$1.0 |  | 1
Q3-21 | 344.635 | -34.604 | 0.353350$\pm$0.000020 | 19.3$\pm$0.4 | 20.8$\pm$0.7 | 16.48$\pm$0.08 | 1
Q3-23 | 344.596 | -34.607 | 0.353750$\pm$0.000046 | 19.9$\pm$0.6 | 21.6$\pm$1.0 | 16.89$\pm$0.07 | 0
Q3-24 | 344.621 | -34.609 | 0.271760$\pm$0.000016 | 22.4$\pm$0.7 | 24.2$\pm$1.1 | 18.57$\pm$0.27 | 0
Q3-25 | 344.670 | -34.611 | 0.595430$\pm$0.000085 | 20.5$\pm$0.5 | 23.2$\pm$0.8 | 17.07$\pm$0.07 | 0
Q3-26 | 344.618 | -34.613 | 0.315900$\pm$0.000024 | 20.2$\pm$0.7 | 22.1$\pm$1.1 | 17.36$\pm$0.09 | 0
Q3-27 | 344.623 | -34.615 | 0.593510$\pm$0.000068 | 22.0$\pm$0.7 | 23.4$\pm$1.1 | 19.74$\pm$0.48 | 1
Q3-28 | 344.601 | -34.617 | 0.258540$\pm$0.000026 | 18.1$\pm$0.5 | 20.1$\pm$0.8 | 15.05$\pm$0.02 | 0
Q3-29 | 344.635 | -34.618 | 0.462490$\pm$0.000004 | 20.2$\pm$0.6 | 21.0$\pm$0.9 | 18.27$\pm$0.22 | 1
Q3-30 | 344.616 | -34.621 | 0.402360$\pm$0.000025 |  |  |  | 1
Q3-31 | 344.685 | -34.623 | 0.332340$\pm$0.000228 | 20.8$\pm$0.5 | 22.0$\pm$0.9 | 17.89$\pm$0.20 | 1
Q3-A3 | 344.643 | -34.626 | 0.319970$\pm$0.000009 | 23.8$\pm$0.7 | 24.7$\pm$1.1 | 19.79$\pm$0.67 | 0
Q3-33 | 344.663 | -34.631 | 0.112810$\pm$0.000010 | 22.3$\pm$0.4 | 22.9$\pm$0.6 |  | 1
Q3-34 | 344.665 | -34.634 | 0.351610$\pm$0.000046 |  |  | 18.38$\pm$0.18 | 1
Q3-35 | 344.640 | -34.638 | 0.060200$\pm$0.000009 |  |  |  | 1
Q3-36 | 344.631 | -34.640 | 0.202140$\pm$0.000016 |  |  | 17.70$\pm$0.20 | 1
Q3-A4 | 344.668 | -34.642 | 0.345010$\pm$0.000078 |  |  |  | 0
Q3-38 | 344.672 | -34.644 | 0.432870$\pm$0.000022 |  |  | 18.63$\pm$0.28 | 1
Q3-39 | 344.694 | -34.646 | 0.399430$\pm$0.000059 |  |  | 18.19$\pm$0.22 | 1
Q3-40 | 344.642 | -34.648 | 0.318120$\pm$0.000081 | 19.5$\pm$0.5 | 21.7$\pm$0.8 | 16.26$\pm$0.04 | 0
Q3-A5 | 344.610 | -34.649 | 0.479200$\pm$0.000065 |  |  |  | 0
Q3-A6 | 344.588 | -34.651 | 0.325310$\pm$0.000167 |  |  |  | 1
Q3-43 | 344.664 | -34.653 | 0.509810$\pm$0.000015 | 21.1$\pm$0.5 | 22.3$\pm$0.9 |  | 1
Q3-44 | 344.664 | -34.656 | 0.224270$\pm$0.000168 | 19.6$\pm$0.5 | 21.2$\pm$0.8 | 16.40$\pm$0.07 | 1
Q3-45 | 344.681 | -34.659 | 0.327200$\pm$0.000073 | 21.3$\pm$0.5 | 22.9$\pm$0.9 | 18.64$\pm$0.34 | 0
Q3-46 | 344.678 | -34.661 | 0.309010$\pm$0.000041 | 21.0$\pm$0.5 | 22.6$\pm$0.9 | 18.70$\pm$0.32 | 0
Q3-A7 | 344.585 | -34.662 | 0.345340$\pm$0.000153 | 19.9$\pm$0.5 | 21.3$\pm$0.8 | 17.01$\pm$0.11 | 0
Q3-A8 | 344.620 | -34.665 | 0.412960$\pm$0.000773 |  |  |  | 0
Q3-49 | 344.655 | -34.668 | 0.309000$\pm$0.000033 | 18.0$\pm$0.3 | 19.2$\pm$0.5 | 15.62$\pm$0.05 | 0
ID | RA | Dec | z | $i$ | $g$ | $K_{s}$ | ELGs
---|---|---|---|---|---|---|---
Q4-A1 | 344.669 | -34.704 | 0.133610$\pm$0.000008 |  |  |  | 1
Q4-2 | 344.646 | -34.706 | 0.318380$\pm$0.000216 | 20.0$\pm$0.6 | 22.0$\pm$1.0 | 16.91$\pm$0.08 | 0
Q4-3 | 344.688 | -34.708 | 0.412180$\pm$0.000024 | 20.7$\pm$0.6 | 22.2$\pm$1.1 | 18.05$\pm$0.18 | 1
Q4-4 | 344.648 | -34.709 | 0.310170$\pm$0.000273 | 21.3$\pm$0.7 | 23.0$\pm$1.0 | 18.57$\pm$0.25 | 0
Q4-5 | 344.677 | -34.711 | 0.411570$\pm$0.000089 | 21.2$\pm$0.6 | 22.6$\pm$1.0 | 18.47$\pm$0.32 | 1
Q4-A2 | 344.660 | -34.712 | 0.268420$\pm$0.000033 |  |  |  | 0
Q4-7 | 344.635 | -34.715 | 0.169450$\pm$0.000183 | 19.5$\pm$0.5 | 20.1$\pm$0.8 | 17.62$\pm$0.20 | 1
Q4-8 | 344.636 | -34.717 | 0.169800$\pm$0.000028 | 21.4$\pm$0.7 | 22.2$\pm$1.1 | 19.17$\pm$0.32 | 1
Q4-9 | 344.632 | -34.721 | 0.256730$\pm$0.000144 | 18.9$\pm$0.6 | 20.8$\pm$0.9 | 15.69$\pm$0.02 | 0
Q4-10 | 344.605 | -34.723 | 0.311730$\pm$0.000114 |  |  |  | 0
Q4-11 | 344.635 | -34.725 | 0.291170$\pm$0.000046 | 22.4$\pm$0.7 | 24.0$\pm$1.1 |  | 0
Q4-13 | 344.611 | -34.728 | 0.316650$\pm$0.000101 | 21.3$\pm$0.6 | 23.2$\pm$1.0 | 18.69$\pm$0.30 | 0
Q4-14 | 344.673 | -34.729 | 0.304220$\pm$0.000072 | 21.4$\pm$0.7 | 22.1$\pm$1.1 | 19.63$\pm$0.65 | 1
Q4-15 | 344.608 | -34.731 | 0.306580$\pm$0.000008 | 21.9$\pm$0.7 | 22.7$\pm$1.1 |  | 1
Q4-16 | 344.623 | -34.732 | 0.318090$\pm$0.000212 | 20.1$\pm$0.7 | 22.1$\pm$1.2 | 16.79$\pm$0.06 | 0
Q4-A3 | 344.596 | -34.733 | 0.362090$\pm$0.000022 |  |  |  | 1
Q4-18 | 344.608 | -34.735 | 0.290200$\pm$0.000282 | 21.4$\pm$0.8 | 24.2$\pm$1.2 | 18.08$\pm$0.16 | 0
Q4-19 | 344.609 | -34.736 | 0.309670$\pm$0.000160 | 21.0$\pm$0.6 | 21.8$\pm$1.0 | 17.97$\pm$0.18 | 1
Q4-20 | 344.664 | -34.738 | 0.306440$\pm$0.000191 | 19.9$\pm$0.6 | 22.0$\pm$1.1 | 16.67$\pm$0.05 | 0
Q4-21 | 344.711 | -34.737 | 0.314790$\pm$0.000241 |  |  |  | 0
Q4-22 | 344.666 | -34.741 | 0.317210$\pm$0.000205 | 21.4$\pm$0.7 | 22.3$\pm$1.2 | 19.57$\pm$0.58 | 1
Q4-23 | 344.646 | -34.742 | 0.320540$\pm$0.000446 | 21.0$\pm$0.7 | 23.0$\pm$1.1 | 18.05$\pm$0.24 | 0
Q4-24 | 344.638 | -34.744 | 0.314080$\pm$0.000204 | 20.7$\pm$0.7 | 22.6$\pm$1.2 | 18.02$\pm$0.16 | 0
Q4-25 | 344.626 | -34.745 | 0.297410$\pm$0.001417 | 22.5$\pm$0.8 | 24.3$\pm$1.2 |  | 0
Q4-26 | 344.675 | -34.747 | 0.324030$\pm$0.000127 | 19.7$\pm$0.5 | 20.4$\pm$0.9 | 17.66$\pm$0.17 | 1
Q4-27 | 344.624 | -34.748 | 0.323200$\pm$0.000040 | 21.9$\pm$0.6 | 24.7$\pm$1.0 | 19.01$\pm$0.34 | 0
Q4-28 | 344.612 | -34.750 | 0.314550$\pm$0.000265 | 20.8$\pm$0.7 | 22.7$\pm$1.2 | 17.83$\pm$0.17 | 0
Q4-A4 | 344.600 | -34.751 | 0.358350$\pm$0.000065 | 21.6$\pm$0.5 | 22.8$\pm$0.8 | 19.53$\pm$0.45 | 1
Q4-A5 | 344.625 | -34.752 | 0.427510$\pm$0.000011 |  |  |  | 0
Q4-31 | 344.652 | -34.754 | 0.317740$\pm$0.000258 | 19.5$\pm$0.6 | 21.7$\pm$1.0 | 16.39$\pm$0.04 | 0
Q4-32 | 344.658 | -34.756 | 0.316410$\pm$0.000275 | 16.7$\pm$0.1 | 18.9$\pm$0.3 | 14.08$\pm$0.02 | 0
Q4-33 | 344.672 | -34.758 | 0.101960$\pm$0.000016 | 19.8$\pm$0.4 | 20.6$\pm$0.7 | 18.33$\pm$0.19 | 1
Q4-A6 | 344.599 | -34.759 | 0.295250$\pm$0.000024 |  |  |  | 1
Q4-35 | 344.700 | -34.762 | 0.170350$\pm$0.000007 | 20.7$\pm$0.5 | 21.4$\pm$1.1 | 17.46$\pm$0.15 | 1
Q4-36 | 344.650 | -34.763 | 0.312860$\pm$0.000277 | 17.6$\pm$0.3 | 19.4$\pm$0.5 | 14.66$\pm$0.01 | 1
Q4-37 | 344.624 | -34.765 | 0.273050$\pm$0.000022 | 22.8$\pm$0.5 | 24.5$\pm$0.9 |  | 1
Q4-38 | 344.618 | -34.767 | 0.310670$\pm$0.000239 | 19.2$\pm$0.5 | 21.2$\pm$0.9 | 16.28$\pm$0.04 | 0
Q4-39 | 344.661 | -34.769 | 0.312550$\pm$0.001159 |  |  |  | 0
Q4-40 | 344.595 | -34.771 | 0.316250$\pm$0.000482 |  |  |  | 1
Q4-41 | 344.616 | -34.773 | 0.317970$\pm$0.000324 | 20.5$\pm$0.7 | 22.5$\pm$1.1 | 17.59$\pm$0.13 | 0
Q4-42 | 344.624 | -34.775 | 0.497280$\pm$0.000614 | 21.1$\pm$0.6 | 22.7$\pm$1.0 | 18.42$\pm$0.34 | 0
Q4-43 | 344.620 | -34.777 | 0.317200$\pm$0.000339 | 20.9$\pm$0.6 | 22.6$\pm$1.0 | 18.57$\pm$0.32 | 0
Q4-44 | 344.671 | -34.779 | 0.315630$\pm$0.000309 | 18.8$\pm$0.5 | 21.0$\pm$0.9 | 15.38$\pm$0.02 | 0
Q4-45 | 344.652 | -34.780 | 0.314980$\pm$0.000326 | 20.6$\pm$0.6 | 22.5$\pm$1.0 | 17.85$\pm$0.21 | 0
Q4-46 | 344.712 | -34.783 | 0.328510$\pm$0.000097 | 19.5$\pm$0.3 | 20.5$\pm$0.6 | 17.61$\pm$0.13 | 0
Q4-47 | 344.645 | -34.785 | 0.316340$\pm$0.000236 | 20.0$\pm$0.7 | 21.9$\pm$1.1 | 17.08$\pm$0.09 | 0
Q4-48 | 344.621 | -34.786 | 0.314460$\pm$0.000288 | 19.6$\pm$0.5 | 21.5$\pm$0.8 | 16.45$\pm$0.07 | 0
Q4-49 | 344.665 | -34.788 | 0.317640$\pm$0.000297 | 18.9$\pm$0.5 | 21.1$\pm$0.8 | 15.76$\pm$0.04 | 0
Q4-50 | 344.700 | -34.789 | 0.330460$\pm$0.000464 | 22.0$\pm$0.7 | 23.4$\pm$1.2 |  | 0
Q4-51 | 344.693 | -34.792 | 0.309450$\pm$0.000221 | 18.8$\pm$0.4 | 20.9$\pm$0.8 | 15.92$\pm$0.03 | 0
Q4-52 | 344.609 | -34.793 | 0.313230$\pm$0.000288 | 20.5$\pm$0.7 | 22.5$\pm$1.1 | 17.54$\pm$0.12 | 0
Q4-54 | 344.641 | -34.796 | 0.350100$\pm$0.000059 | 20.4$\pm$0.5 | 21.9$\pm$0.6 | 17.44$\pm$0.17 | 0
Q4-55 | 344.642 | -34.798 | 0.318480$\pm$0.000254 | 20.9$\pm$0.4 | 22.4$\pm$0.5 | 17.74$\pm$0.19 | 0
Q4-56 | 344.684 | -34.799 | 0.324800$\pm$0.000005 |  |  |  | 1
Q4-57 | 344.707 | -34.800 | 0.313880$\pm$0.000143 |  |  | 18.17$\pm$0.18 | 0
Q4-58 | 344.674 | -34.801 | 0.311070$\pm$0.000131 |  |  | 15.90$\pm$0.03 | 0
Q4-59 | 344.690 | -34.804 | 0.316080$\pm$0.000118 |  |  |  | 0
Q4-60 | 344.685 | -34.805 | 0.312500$\pm$0.000122 |  |  | 17.87$\pm$0.13 | 0
Q4-61 | 344.659 | -34.807 | 0.717580$\pm$0.000108 |  |  | 17.34$\pm$0.13 | 0
Q4-62 | 344.678 | -34.809 | 0.309600$\pm$0.000172 |  |  | 17.94$\pm$0.21 | 0
Q4-63 | 344.719 | -34.810 | 0.318810$\pm$0.000127 |  |  | 17.33$\pm$0.13 | 0
Q4-64 | 344.631 | -34.814 | 0.314870$\pm$0.000135 | 20.6$\pm$0.7 | 22.6$\pm$0.9 | 17.10$\pm$0.11 | 0
Table 3: Optical and NIR-bases stellar mass estimations. Columns 2,3 and 4 show absolute magnitudes in the selected optical and NIR band passes, respectively. Columns 5 and 6 show optical and NIR-based stellar mass estimations in logarithmic scale. The last column shows ELGs and passive galaxies with the same definition than Table 2. ID | $M_{i}$ | $M_{g}$ | $M_{Ks}$ | log(M${}^{*}_{i}$/M⊙) | log(M${}^{*}_{Ks}$/M⊙) | ELGs
---|---|---|---|---|---|---
Q1-1 | -22.3$\pm$0.5 | -21.2$\pm$0.5 |  | 11.1$\pm$0.2 |  | 0
Q1-3 | -18.8$\pm$0.5 | -18.8$\pm$0.5 |  | 9.2$\pm$0.2 |  | 1
Q1-A1 | -19.4$\pm$0.5 | -18.7$\pm$0.5 |  | 9.5$\pm$0.2 |  | 1
Q1-5 | -17.5$\pm$0.5 | -17.6$\pm$0.5 |  | 8.7$\pm$0.2 |  | 1
Q1-A2 | -19.4$\pm$0.5 | -19.0$\pm$0.5 |  | 10.0$\pm$0.2 |  | 0
Q1-8 | -22.6$\pm$0.5 | -21.3$\pm$0.5 |  | 10.7$\pm$0.2 |  | 1
Q1-9 | -19.6$\pm$0.6 | -18.4$\pm$0.5 | -24.01$\pm$0.16 | 10.0$\pm$0.2 | 10.84$\pm$0.06 | 0
Q1-10 | -21.5$\pm$0.5 | -20.0$\pm$0.8 | -24.44$\pm$0.03 | 10.3$\pm$0.2 | 10.51$\pm$0.01 | 1
Q1-11 | -19.2$\pm$0.6 | -17.2$\pm$1.1 | -22.38$\pm$0.24 | 9.9$\pm$0.3 | 10.18$\pm$0.10 | 0
Q1-12 | -20.6$\pm$0.4 | -19.8$\pm$0.8 | -23.10$\pm$0.15 | 10.0$\pm$0.2 | 9.97$\pm$0.06 | 1
Q1-A3 | -20.0$\pm$0.5 | -19.5$\pm$0.5 |  | 9.7$\pm$0.2 |  | 1
Q1-15 | -16.0$\pm$0.6 | -15.6$\pm$1.0 |  | 8.1$\pm$0.2 |  | 1
Q1-16 | -20.0$\pm$0.5 | -18.1$\pm$1.0 | -23.61$\pm$0.24 | 10.2$\pm$0.2 | 10.67$\pm$0.10 | 0
Q1-17 | -21.0$\pm$0.5 | -19.3$\pm$0.5 |  | 10.6$\pm$0.2 |  | 0
Q1-18 | -19.9$\pm$0.6 | -18.7$\pm$1.1 | -22.77$\pm$0.18 | 9.7$\pm$0.2 | 9.84$\pm$0.07 | 1
Q1-19 | -20.3$\pm$0.5 | -19.2$\pm$1.0 | -22.79$\pm$0.34 | 9.8$\pm$0.2 | 9.85$\pm$0.13 | 1
Q1-20 | -22.7$\pm$0.5 | -21.6$\pm$0.5 |  | 11.3$\pm$0.2 |  | 0
Q1-A4 | -19.8$\pm$0.5 | -19.2$\pm$0.5 |  | 10.1$\pm$0.2 |  | 0
Q1-22 | -22.8$\pm$0.4 | -20.3$\pm$0.8 | -25.85$\pm$0.04 | 10.8$\pm$0.2 | 11.07$\pm$0.01 | 1
Q1-24 | -21.9$\pm$0.4 | -20.4$\pm$0.8 | -24.72$\pm$0.06 | 11.0$\pm$0.1 | 11.12$\pm$0.03 | 0
Q1-25 | -21.3$\pm$0.5 | -19.7$\pm$1.0 | -24.07$\pm$0.17 | 10.2$\pm$0.2 | 10.36$\pm$0.07 | 1
Q1-26 | -20.6$\pm$0.5 | -18.9$\pm$1.0 | -23.91$\pm$0.14 | 10.4$\pm$0.2 | 10.79$\pm$0.05 | 0
Q1-27 | -19.6$\pm$0.5 | -18.1$\pm$0.9 |  | 10.0$\pm$0.2 |  | 0
Q1-28 | -22.2$\pm$0.3 | -21.5$\pm$0.6 | -24.17$\pm$0.12 | 11.1$\pm$0.1 | 10.90$\pm$0.05 | 0
Q1-30 | -22.1$\pm$0.4 | -20.0$\pm$0.8 | -25.83$\pm$0.02 | 10.5$\pm$0.2 | 11.06$\pm$0.01 | 1
Q1-31 | -20.6$\pm$0.6 | -18.6$\pm$1.0 | -23.90$\pm$0.12 | 10.4$\pm$0.2 | 10.79$\pm$0.05 | 0
Q1-34 | -20.7$\pm$0.6 | -18.6$\pm$1.0 | -23.96$\pm$0.08 | 10.5$\pm$0.2 | 10.81$\pm$0.03 | 0
Q1-36 | -21.5$\pm$0.5 | -20.1$\pm$0.8 | -23.52$\pm$0.20 | 10.8$\pm$0.2 | 10.64$\pm$0.08 | 0
Q1-37 | -21.6$\pm$0.6 | -19.9$\pm$1.0 | -24.60$\pm$0.05 | 10.3$\pm$0.2 | 10.57$\pm$0.02 | 1
Q1-A5 | -20.3$\pm$0.4 | -18.5$\pm$0.7 | -24.36$\pm$0.09 | 10.3$\pm$0.2 | 10.97$\pm$0.04 | 0
Q1-38 | -21.3$\pm$0.5 | -20.8$\pm$0.5 |  | 10.2$\pm$0.2 |  | 1
Q1-40 | -22.8$\pm$0.5 | -19.8$\pm$0.5 | -24.89$\pm$0.05 | 10.8$\pm$0.2 | 10.68$\pm$0.02 | 1
Q1-41 | -22.6$\pm$0.5 | -21.3$\pm$0.5 | -25.57$\pm$0.08 | 11.2$\pm$0.2 | 11.46$\pm$0.03 | 0
Q1-A6 | -18.8$\pm$0.5 | -18.8$\pm$0.5 |  | 9.7$\pm$0.2 |  | 0
Q1-44 | -21.1$\pm$0.4 | -19.6$\pm$0.7 |  | 10.1$\pm$0.1 |  | 1
ID | $M_{i}$ | $M_{g}$ | $M_{Ks}$ | log(M${}^{*}_{i}$/M⊙) | log(M${}^{*}_{Ks}$/M⊙) | ELGs
---|---|---|---|---|---|---
Q2-1 | -20.7$\pm$0.5 | -20.3$\pm$0.5 |  | 10.0$\pm$0.2 |  | 1
Q2-2 | -19.4$\pm$0.5 | -19.1$\pm$0.5 |  | 10.0$\pm$0.2 |  | 0
Q2-3 | -20.2$\pm$0.5 | -19.8$\pm$0.5 |  | 9.8$\pm$0.2 |  | 1
Q2-4 | -19.7$\pm$0.5 | -19.5$\pm$0.5 |  | 9.6$\pm$0.2 |  | 1
Q2-5 | -19.2$\pm$0.5 | -18.5$\pm$0.5 |  | 9.9$\pm$0.2 |  | 0
Q2-6 | -22.9$\pm$0.4 | -20.9$\pm$0.7 | -26.05$\pm$0.05 | 11.4$\pm$0.2 | 11.65$\pm$0.02 | 0
Q2-7 | -18.3$\pm$0.7 | -15.3$\pm$1.1 | -21.01$\pm$0.52 | 9.5$\pm$0.3 | 9.63$\pm$0.21 | 0
Q2-8 | -20.4$\pm$0.6 | -19.3$\pm$1.0 | -23.11$\pm$0.29 | 10.4$\pm$0.2 | 10.47$\pm$0.12 | 0
Q2-9 | -19.4$\pm$0.6 | -18.3$\pm$1.1 |  | 9.4$\pm$0.2 |  | 1
Q2-10 | -20.4$\pm$0.7 | -18.4$\pm$1.1 | -24.72$\pm$0.12 | 9.9$\pm$0.3 | 10.62$\pm$0.05 | 1
Q2-11 | -18.8$\pm$0.4 | -18.1$\pm$0.8 |  | 9.2$\pm$0.2 |  | 1
Q2-12 | -20.4$\pm$0.5 | -18.6$\pm$0.9 | -23.83$\pm$0.19 | 10.4$\pm$0.2 | 10.76$\pm$0.07 | 0
Q2-13 | -19.2$\pm$0.5 | -19.7$\pm$0.5 |  | 9.9$\pm$0.2 |  | 0
Q2-14 | -20.8$\pm$0.4 | -18.9$\pm$0.9 | -23.81$\pm$0.15 | 10.5$\pm$0.2 | 10.75$\pm$0.06 | 0
Q2-15 | -20.0$\pm$0.6 | -17.8$\pm$1.1 | -23.40$\pm$0.20 | 10.2$\pm$0.2 | 10.59$\pm$0.08 | 0
Q2-16 | -21.3$\pm$0.4 | -19.1$\pm$0.9 | -24.17$\pm$0.27 | 10.2$\pm$0.2 | 10.40$\pm$0.11 | 1
Q2-A1 | -22.3$\pm$0.5 | -20.0$\pm$0.5 |  | 11.1$\pm$0.2 |  | 0
Q2-18 | -20.3$\pm$0.5 | -18.2$\pm$0.9 | -23.36$\pm$0.17 | 10.3$\pm$0.2 | 10.58$\pm$0.07 | 0
Q2-19 | -22.2$\pm$0.4 | -20.0$\pm$0.8 | -25.19$\pm$0.05 | 11.1$\pm$0.2 | 11.31$\pm$0.02 | 0
Q2-A2 | -20.5$\pm$0.5 | -20.0$\pm$0.5 |  | 10.4$\pm$0.2 |  | 0
Q2-21 | -21.3$\pm$0.5 | -19.3$\pm$0.8 | -24.34$\pm$0.11 | 10.7$\pm$0.2 | 10.97$\pm$0.04 | 0
Q2-22 | -20.1$\pm$0.5 | -20.0$\pm$0.5 |  | 9.7$\pm$0.2 |  | 1
Q2-23 | -22.3$\pm$0.5 | -19.7$\pm$0.9 | -25.49$\pm$0.04 | 11.1$\pm$0.2 | 11.42$\pm$0.01 | 0
Q2-24 | -19.4$\pm$0.6 | -18.4$\pm$1.0 |  | 9.5$\pm$0.2 |  | 1
Q2-A3 | -20.3$\pm$0.5 | -20.2$\pm$0.5 |  | 10.3$\pm$0.2 |  | 0
Q2-26 | -20.7$\pm$0.5 | -19.0$\pm$0.9 | -22.92$\pm$0.48 | 10.0$\pm$0.2 | 9.90$\pm$0.19 | 1
Q2-27 | -22.0$\pm$0.5 | -20.1$\pm$0.9 | -25.17$\pm$0.11 | 10.5$\pm$0.2 | 10.80$\pm$0.04 | 1
Q2-28 | -22.5$\pm$0.3 | -21.2$\pm$0.6 | -25.47$\pm$0.17 | 10.7$\pm$0.1 | 10.92$\pm$0.07 | 1
Q2-29 | -21.8$\pm$0.2 | -20.9$\pm$0.5 | -24.50$\pm$0.21 | 10.4$\pm$0.1 | 10.53$\pm$0.08 | 1
Q2-31 | -20.4$\pm$0.5 | -20.3$\pm$0.5 |  | 10.4$\pm$0.2 |  | 0
Q2-A4 | -22.6$\pm$0.5 | -21.7$\pm$0.5 |  | 10.7$\pm$0.2 |  | 1
Q2-32 | -20.7$\pm$0.5 | -20.5$\pm$0.5 | -22.93$\pm$0.23 | 10.0$\pm$0.2 | 9.90$\pm$0.09 | 1
Q2-33 | -22.6$\pm$0.5 | -22.1$\pm$0.5 | -25.15$\pm$0.11 | 10.7$\pm$0.2 | 10.79$\pm$0.05 | 1
Q2-A5 | -19.9$\pm$0.5 | -19.4$\pm$0.5 |  | 10.2$\pm$0.2 |  | 0
Q2-35 | -21.4$\pm$0.6 | -19.2$\pm$1.1 | -24.59$\pm$0.04 | 10.8$\pm$0.2 | 11.06$\pm$0.02 | 0
Q2-36 | -21.8$\pm$0.6 | -19.9$\pm$1.0 | -24.67$\pm$0.11 | 10.4$\pm$0.2 | 10.60$\pm$0.05 | 1
Q2-37 | -18.7$\pm$0.4 | -17.9$\pm$0.7 |  | 9.2$\pm$0.2 |  | 1
Q2-38 | -19.4$\pm$0.6 | -18.3$\pm$1.0 | -21.51$\pm$0.46 | 9.5$\pm$0.2 | 9.34$\pm$0.18 | 1
Q2-39 | -20.9$\pm$0.6 | -19.8$\pm$1.1 | -23.64$\pm$0.16 | 10.0$\pm$0.3 | 10.19$\pm$0.06 | 1
Q2-40 | -21.0$\pm$0.6 | -18.9$\pm$1.0 | -23.34$\pm$0.31 | 10.6$\pm$0.2 | 10.57$\pm$0.13 | 0
Q2-41 | -21.2$\pm$0.6 | -19.1$\pm$1.0 | -24.45$\pm$0.22 | 10.7$\pm$0.2 | 11.01$\pm$0.09 | 0
ID | $M_{i}$ | $M_{g}$ | $M_{Ks}$ | log(M${}^{*}_{i}$/M⊙) | log(M${}^{*}_{Ks}$/M⊙) | ELGs
---|---|---|---|---|---|---
Q3-1 | -19.8$\pm$0.6 | -18.8$\pm$1.1 | -22.18$\pm$0.40 | 9.6$\pm$0.2 | 9.60$\pm$0.16 | 1
Q3-2 | -22.4$\pm$0.5 | -21.1$\pm$0.8 | -25.45$\pm$0.04 | 10.7$\pm$0.2 | 10.91$\pm$0.01 | 1
Q3-3 | -22.1$\pm$0.6 | -19.9$\pm$1.0 | -25.28$\pm$0.03 | 11.1$\pm$0.2 | 11.34$\pm$0.01 | 0
Q3-4 | -19.2$\pm$0.7 | -18.1$\pm$1.1 | -21.66$\pm$0.26 | 9.4$\pm$0.3 | 9.39$\pm$0.11 | 1
Q3-5 | -20.3$\pm$0.5 | -19.1$\pm$1.0 | -22.75$\pm$0.36 | 9.8$\pm$0.2 | 9.83$\pm$0.14 | 1
Q3-6 | -19.7$\pm$0.5 | -19.8$\pm$0.5 |  | 10.1$\pm$0.2 |  | 0
Q3-A1 | -24.5$\pm$0.5 | -24.0$\pm$0.5 |  | 12.0$\pm$0.2 |  | 0
Q3-8 | -21.2$\pm$0.5 | -20.1$\pm$0.5 |  | 10.2$\pm$0.2 |  | 1
Q3-10 | -22.6$\pm$0.3 | -21.7$\pm$0.5 | -24.23$\pm$0.13 | 11.2$\pm$0.1 | 10.92$\pm$0.05 | 0
Q3-11 | -19.4$\pm$0.7 | -18.6$\pm$1.1 | -21.36$\pm$0.34 | 9.4$\pm$0.3 | 9.28$\pm$0.14 | 1
Q3-12 | -21.1$\pm$0.5 | -19.9$\pm$0.8 | -23.58$\pm$0.21 | 10.1$\pm$0.2 | 10.16$\pm$0.08 | 1
Q3-A2 | -19.6$\pm$0.5 | -19.8$\pm$0.5 |  | 10.0$\pm$0.2 |  | 0
Q3-15 | -19.0$\pm$0.5 | -19.2$\pm$0.5 |  | 9.8$\pm$0.2 |  | 0
Q3-16 | -17.8$\pm$0.5 | -17.0$\pm$1.1 |  | 8.8$\pm$0.2 |  | 1
Q3-17 | -19.7$\pm$0.6 | -17.5$\pm$1.1 | -22.85$\pm$0.44 | 9.6$\pm$0.2 | 9.87$\pm$0.18 | 1
Q3-18 | -20.7$\pm$0.4 | -19.8$\pm$0.8 | -22.99$\pm$0.14 | 10.0$\pm$0.2 | 9.93$\pm$0.06 | 1
Q3-19 | -20.9$\pm$0.4 | -19.8$\pm$0.6 | -23.56$\pm$0.06 | 10.6$\pm$0.1 | 10.66$\pm$0.02 | 0
Q3-20 | -18.2$\pm$0.5 | -17.1$\pm$1.0 |  | 9.0$\pm$0.2 |  | 1
Q3-21 | -22.1$\pm$0.4 | -20.6$\pm$0.7 | -24.91$\pm$0.08 | 10.5$\pm$0.2 | 10.70$\pm$0.03 | 1
Q3-23 | -21.4$\pm$0.6 | -19.8$\pm$1.0 | -24.50$\pm$0.07 | 10.8$\pm$0.3 | 11.03$\pm$0.03 | 0
Q3-24 | -18.4$\pm$0.7 | -16.6$\pm$1.1 | -22.17$\pm$0.27 | 9.6$\pm$0.3 | 10.10$\pm$0.11 | 0
Q3-25 | -22.2$\pm$0.5 | -19.5$\pm$0.8 | -25.68$\pm$0.07 | 11.1$\pm$0.2 | 11.50$\pm$0.03 | 0
Q3-26 | -20.9$\pm$0.7 | -19.0$\pm$1.1 | -23.76$\pm$0.09 | 10.6$\pm$0.3 | 10.73$\pm$0.04 | 0
Q3-27 | -20.7$\pm$0.7 | -19.3$\pm$1.1 | -22.99$\pm$0.48 | 10.0$\pm$0.3 | 9.93$\pm$0.19 | 1
Q3-28 | -22.5$\pm$0.5 | -20.5$\pm$0.8 | -25.57$\pm$0.02 | 11.2$\pm$0.2 | 11.46$\pm$0.01 | 0
Q3-29 | -21.9$\pm$0.6 | -21.1$\pm$0.9 | -23.81$\pm$0.22 | 10.4$\pm$0.2 | 10.25$\pm$0.09 | 1
Q3-30 | -19.7$\pm$0.5 | -19.5$\pm$0.5 |  | 9.6$\pm$0.2 |  | 1
Q3-31 | -20.5$\pm$0.5 | -19.2$\pm$0.9 | -23.35$\pm$0.20 | 9.9$\pm$0.2 | 10.07$\pm$0.08 | 1
Q3-A3 | -17.3$\pm$0.7 | -16.5$\pm$1.1 | -21.36$\pm$0.67 | 9.1$\pm$0.3 | 9.77$\pm$0.27 | 0
Q3-33 | -16.3$\pm$0.4 | -15.7$\pm$0.6 |  | 8.2$\pm$0.2 |  | 1
Q3-34 | -21.3$\pm$0.5 | -18.4$\pm$0.6 | -23.00$\pm$0.18 | 10.2$\pm$0.2 | 9.93$\pm$0.07 | 1
Q3-35 | -16.6$\pm$0.5 | -14.2$\pm$0.6 |  | 8.3$\pm$0.2 |  | 1
Q3-36 | -20.0$\pm$0.5 | -17.1$\pm$0.6 | -22.32$\pm$0.20 | 9.7$\pm$0.2 | 9.66$\pm$0.08 | 1
Q3-A4 | -19.9$\pm$0.5 | -19.2$\pm$0.5 |  | 10.2$\pm$0.2 |  | 0
Q3-38 | -20.9$\pm$0.5 | -19.7$\pm$0.5 | -23.28$\pm$0.28 | 10.0$\pm$0.2 | 10.04$\pm$0.11 | 1
Q3-39 | -21.2$\pm$0.5 | -19.5$\pm$0.5 | -23.51$\pm$0.22 | 10.2$\pm$0.2 | 10.14$\pm$0.09 | 1
Q3-40 | -21.7$\pm$0.5 | -19.4$\pm$0.8 | -24.87$\pm$0.04 | 10.9$\pm$0.2 | 11.18$\pm$0.02 | 0
Q3-A5 | -20.1$\pm$0.5 | -20.4$\pm$0.5 |  | 10.2$\pm$0.2 |  | 0
Q3-A6 | -19.5$\pm$0.5 | -19.3$\pm$0.5 |  | 9.5$\pm$0.2 |  | 1
Q3-43 | -21.2$\pm$0.5 | -20.0$\pm$0.9 |  | 10.2$\pm$0.2 |  | 1
Q3-44 | -20.6$\pm$0.5 | -19.0$\pm$0.8 | -23.87$\pm$0.07 | 9.9$\pm$0.2 | 10.28$\pm$0.03 | 1
Q3-45 | -19.9$\pm$0.5 | -18.3$\pm$0.9 | -22.56$\pm$0.34 | 10.2$\pm$0.2 | 10.26$\pm$0.14 | 0
Q3-46 | -20.0$\pm$0.5 | -18.4$\pm$0.9 | -22.36$\pm$0.32 | 10.2$\pm$0.2 | 10.17$\pm$0.13 | 0
Q3-A7 | -21.4$\pm$0.5 | -20.1$\pm$0.8 | -24.33$\pm$0.11 | 10.8$\pm$0.2 | 10.96$\pm$0.05 | 0
Q3-A8 | -20.9$\pm$0.5 | -20.1$\pm$0.5 |  | 10.6$\pm$0.2 |  | 0
Q3-49 | -23.0$\pm$0.3 | -21.9$\pm$0.5 | -25.44$\pm$0.05 | 11.4$\pm$0.1 | 11.41$\pm$0.02 | 0
ID | $M_{i}$ | $M_{g}$ | $M_{Ks}$ | log(M${}^{*}_{i}$/M⊙) | log(M${}^{*}_{Ks}$/M⊙) | ELGs
---|---|---|---|---|---|---
Q4-A1 | -17.3$\pm$0.5 | -16.9$\pm$0.5 |  | 8.6$\pm$0.2 |  | 1
Q4-2 | -21.1$\pm$0.6 | -19.1$\pm$1.0 | -24.22$\pm$0.08 | 10.6$\pm$0.3 | 10.92$\pm$0.03 | 0
Q4-3 | -21.1$\pm$0.6 | -19.6$\pm$1.1 | -23.74$\pm$0.18 | 10.1$\pm$0.3 | 10.23$\pm$0.07 | 1
Q4-4 | -19.8$\pm$0.7 | -18.0$\pm$1.0 | -22.50$\pm$0.25 | 10.1$\pm$0.3 | 10.23$\pm$0.10 | 0
Q4-5 | -20.6$\pm$0.6 | -19.2$\pm$1.0 | -23.31$\pm$0.32 | 9.9$\pm$0.2 | 10.06$\pm$0.13 | 1
Q4-A2 | -18.7$\pm$0.5 | -18.4$\pm$0.5 |  | 9.7$\pm$0.2 |  | 0
Q4-7 | -20.1$\pm$0.5 | -19.5$\pm$0.8 | -21.98$\pm$0.20 | 9.7$\pm$0.2 | 9.52$\pm$0.08 | 1
Q4-8 | -18.2$\pm$0.7 | -17.3$\pm$1.1 | -20.44$\pm$0.32 | 9.0$\pm$0.3 | 8.90$\pm$0.13 | 1
Q4-9 | -21.7$\pm$0.6 | -19.8$\pm$0.9 | -24.91$\pm$0.02 | 10.9$\pm$0.2 | 11.2$\pm$0.01 | 0
Q4-10 | -19.7$\pm$0.5 | -18.6$\pm$0.5 |  | 10.1$\pm$0.2 |  | 0
Q4-11 | -18.5$\pm$0.7 | -16.9$\pm$1.1 |  | 9.6$\pm$0.3 |  | 0
Q4-13 | -19.8$\pm$0.6 | -18.0$\pm$1.0 | -22.43$\pm$0.30 | 10.1$\pm$0.2 | 10.20$\pm$0.12 | 0
Q4-14 | -19.7$\pm$0.7 | -18.9$\pm$1.1 | -21.39$\pm$0.65 | 9.6$\pm$0.3 | 9.29$\pm$0.26 | 1
Q4-15 | -19.1$\pm$0.7 | -18.4$\pm$1.1 |  | 9.3$\pm$0.3 |  | 1
Q4-16 | -21.1$\pm$0.7 | -19.0$\pm$1.2 | -24.34$\pm$0.06 | 10.6$\pm$0.3 | 10.97$\pm$0.02 | 0
Q4-A3 | -19.3$\pm$0.5 | -18.8$\pm$0.5 |  | 9.4$\pm$0.2 |  | 1
Q4-18 | -19.5$\pm$0.8 | -16.7$\pm$1.2 | -22.82$\pm$0.16 | 10.0$\pm$0.3 | 10.36$\pm$0.07 | 0
Q4-19 | -20.1$\pm$0.6 | -19.3$\pm$1.0 | -23.09$\pm$0.18 | 9.7$\pm$0.3 | 9.97$\pm$0.07 | 1
Q4-20 | -21.1$\pm$0.6 | -19.0$\pm$1.1 | -24.37$\pm$0.05 | 10.7$\pm$0.3 | 10.98$\pm$0.02 | 0
Q4-21 | -21.2$\pm$0.5 | -19.7$\pm$0.5 |  | 10.7$\pm$0.2 |  | 0
Q4-22 | -19.7$\pm$0.7 | -18.8$\pm$1.2 | -21.56$\pm$0.58 | 9.6$\pm$0.3 | 9.35$\pm$0.23 | 1
Q4-23 | -20.2$\pm$0.7 | -18.1$\pm$1.1 | -23.10$\pm$0.24 | 10.3$\pm$0.3 | 10.47$\pm$0.09 | 0
Q4-24 | -20.3$\pm$0.7 | -18.4$\pm$1.2 | -23.08$\pm$0.16 | 10.3$\pm$0.3 | 10.46$\pm$0.06 | 0
Q4-25 | -18.4$\pm$0.8 | -16.7$\pm$1.2 |  | 9.6$\pm$0.3 |  | 0
Q4-26 | -21.5$\pm$0.5 | -20.8$\pm$0.9 | -23.51$\pm$0.17 | 10.3$\pm$0.2 | 10.14$\pm$0.07 | 1
Q4-27 | -19.3$\pm$0.6 | -16.5$\pm$1.0 | -22.16$\pm$0.34 | 9.9$\pm$0.3 | 10.10$\pm$0.14 | 0
Q4-28 | -20.3$\pm$0.7 | -18.4$\pm$1.2 | -23.27$\pm$0.17 | 10.3$\pm$0.3 | 10.54$\pm$0.07 | 0
Q4-A4 | -19.8$\pm$0.5 | -18.6$\pm$0.8 | -21.90$\pm$0.45 | 9.6$\pm$0.2 | 9.49$\pm$0.18 | 1
Q4-A5 | -19.6$\pm$0.5 | -19.5$\pm$0.5 |  | 10.0$\pm$0.2 |  | 0
Q4-31 | -21.6$\pm$0.6 | -19.4$\pm$1.0 | -24.74$\pm$0.04 | 10.9$\pm$0.3 | 11.13$\pm$0.02 | 0
Q4-32 | -24.4$\pm$0.1 | -22.2$\pm$0.3 | -27.04$\pm$0.02 | 12.0$\pm$0.1 | 12.05$\pm$0.01 | 0
Q4-33 | -18.6$\pm$0.4 | -17.8$\pm$0.7 | -20.06$\pm$0.19 | 9.1$\pm$0.1 | 8.76$\pm$0.08 | 1
Q4-A6 | -19.3$\pm$0.5 | -19.1$\pm$0.5 |  | 9.4$\pm$0.2 |  | 1
Q4-35 | -18.9$\pm$0.5 | -18.2$\pm$1.1 | -22.14$\pm$0.15 | 9.3$\pm$0.2 | 9.59$\pm$0.06 | 1
Q4-36 | -23.5$\pm$0.3 | -21.7$\pm$0.5 | -26.43$\pm$0.01 | 11.1$\pm$0.1 | 11.30$\pm$0.01 | 1
Q4-37 | -18.0$\pm$0.5 | -16.2$\pm$0.9 |  | 8.9$\pm$0.2 |  | 1
Q4-38 | -21.8$\pm$0.5 | -19.9$\pm$0.9 | -24.80$\pm$0.04 | 10.9$\pm$0.2 | 11.15$\pm$0.02 | 0
Q4-39 | -20.7$\pm$0.5 | -18.8$\pm$0.5 |  | 10.5$\pm$0.2 |  | 0
Q4-40 | -22.2$\pm$0.5 | -21.0$\pm$0.5 |  | 10.6$\pm$0.2 |  | 1
Q4-41 | -20.7$\pm$0.7 | -18.7$\pm$1.1 | -23.54$\pm$0.13 | 10.5$\pm$0.3 | 10.65$\pm$0.05 | 0
Q4-42 | -21.2$\pm$0.6 | -19.6$\pm$1.0 | -23.85$\pm$0.34 | 10.7$\pm$0.2 | 10.77$\pm$0.13 | 0
Q4-43 | -20.2$\pm$0.6 | -18.5$\pm$1.0 | -22.55$\pm$0.32 | 10.3$\pm$0.3 | 10.25$\pm$0.13 | 0
Q4-44 | -22.3$\pm$0.5 | -20.1$\pm$0.9 | -25.73$\pm$0.02 | 11.1$\pm$0.2 | 11.52$\pm$0.01 | 0
Q4-45 | -20.5$\pm$0.6 | -18.6$\pm$1.0 | -23.26$\pm$0.21 | 10.4$\pm$0.2 | 10.53$\pm$0.08 | 0
Q4-46 | -21.7$\pm$0.3 | -20.7$\pm$0.6 | -23.60$\pm$0.13 | 10.9$\pm$0.1 | 10.67$\pm$0.05 | 0
Q4-47 | -21.1$\pm$0.7 | -19.2$\pm$1.1 | -24.04$\pm$0.09 | 10.6$\pm$0.3 | 10.85$\pm$0.04 | 0
Q4-48 | -21.5$\pm$0.5 | -19.6$\pm$0.8 | -24.65$\pm$0.07 | 10.8$\pm$0.2 | 11.09$\pm$0.03 | 0
Q4-49 | -22.2$\pm$0.5 | -20.0$\pm$0.8 | -25.37$\pm$0.04 | 11.1$\pm$0.2 | 11.38$\pm$0.02 | 0
Q4-50 | -19.2$\pm$0.7 | -17.9$\pm$1.2 |  | 9.9$\pm$0.3 |  | 0
Q4-51 | -22.2$\pm$0.4 | -20.2$\pm$0.8 | -25.14$\pm$0.03 | 11.1$\pm$0.2 | 11.29$\pm$0.01 | 0
Q4-52 | -20.6$\pm$0.7 | -18.6$\pm$1.1 | -23.55$\pm$0.12 | 10.4$\pm$0.3 | 10.65$\pm$0.05 | 0
Q4-54 | -20.9$\pm$0.5 | -19.5$\pm$0.6 | -23.93$\pm$0.17 | 10.6$\pm$0.2 | 10.80$\pm$0.07 | 0
Q4-55 | -20.2$\pm$0.4 | -18.7$\pm$0.5 | -23.39$\pm$0.19 | 10.3$\pm$0.2 | 10.59$\pm$0.07 | 0
Q4-56 | -19.7$\pm$0.5 | -18.8$\pm$0.5 |  | 9.6$\pm$0.2 |  | 1
Q4-57 | -20.9$\pm$0.5 | -18.7$\pm$0.5 | -22.93$\pm$0.18 | 10.6$\pm$0.2 | 10.40$\pm$0.07 | 0
Q4-58 | -22.8$\pm$0.5 | -18.7$\pm$0.5 | -25.17$\pm$0.03 | 11.3$\pm$0.2 | 11.30$\pm$0.01 | 0
Q4-59 | -20.5$\pm$0.5 | -19.4$\pm$0.5 |  | 10.4$\pm$0.2 |  | 0
Q4-60 | -21.4$\pm$0.5 | -19.4$\pm$0.5 | -23.22$\pm$0.13 | 10.8$\pm$0.2 | 10.52$\pm$0.05 | 0
Q4-61 | -22.7$\pm$0.5 | -21.5$\pm$0.5 | -25.92$\pm$0.13 | 11.3$\pm$0.2 | 11.6$\pm$0.05 | 0
Q4-62 | -21.2$\pm$0.5 | -19.3$\pm$0.5 | -23.12$\pm$0.21 | 10.7$\pm$0.2 | 10.48$\pm$0.08 | 0
Q4-63 | -21.4$\pm$0.5 | -19.4$\pm$0.5 | -23.80$\pm$0.13 | 10.8$\pm$0.2 | 10.75$\pm$0.05 | 0
Q4-64 | -20.5$\pm$0.7 | -18.5$\pm$0.9 | -24.01$\pm$0.11 | 10.4$\pm$0.3 | 10.83$\pm$0.04 | 0
Table 4: Oxygen abundances of the SF galaxies with available emission line measurements. Column 2 show oxygen abundances estimated by using the O3N2 strong-line method. ID | 12+log(O/H)O3N2
---|---
Q1-3 | 8.37$\pm$0.03
Q1-A1 | 8.44$\pm$0.04
Q1-5 | 8.27$\pm$0.03
Q1-10 | 8.71$\pm$0.04
Q1-12 | 8.56$\pm$0.08
Q1-15 | 8.10$\pm$0.06
Q1-18 | 8.70$\pm$0.06
Q1-19 | 8.42$\pm$0.03
Q1-25 | 8.58$\pm$0.06
Q1-37 | 8.27$\pm$0.05
Q1-40 | 8.68$\pm$0.02
Q2-1 | 8.61$\pm$0.08
Q2-3 | 8.35$\pm$0.04
Q2-9 | 8.22$\pm$0.05
Q2-11 | 8.31$\pm$0.05
Q2-22 | 8.41$\pm$0.05
Q2-A4 | 8.51$\pm$0.02
Q2-32 | 8.49$\pm$0.03
Q2-37 | 8.43$\pm$0.05
Q2-38 | 8.34$\pm$0.05
Q2-39 | 8.50$\pm$0.02
Q3-1 | 8.26$\pm$0.03
Q3-2 | 8.63$\pm$0.03
Q3-4 | 8.49$\pm$0.04
Q3-5 | 8.34$\pm$0.04
Q3-8 | 8.73$\pm$0.04
Q3-11 | 8.25$\pm$0.05
Q3-12 | 8.64$\pm$0.10
Q3-16 | 8.62$\pm$0.11
Q3-18 | 8.71$\pm$0.06
Q3-21 | 8.72$\pm$0.09
Q3-30 | 8.15$\pm$0.03
Q3-31 | 8.63$\pm$0.10
Q3-34 | 8.32$\pm$0.02
Q3-35 | 8.21$\pm$0.10
Q3-36 | 8.52$\pm$0.05
Q3-39 | 8.60$\pm$0.04
Q3-A6 | 8.23$\pm$0.05
Q3-44 | 8.57$\pm$0.06
Q4-3 | 8.59$\pm$0.09
Q4-5 | 8.54$\pm$0.07
Q4-7 | 8.33$\pm$0.03
Q4-8 | 8.17$\pm$0.02
Q4-14 | 8.26$\pm$0.02
Q4-15 | 8.09$\pm$0.03
Q4-19 | 8.27$\pm$0.04
Q4-22 | 8.75$\pm$0.11
Q4-26 | 8.42$\pm$0.03
Q4-A4 | 8.46$\pm$0.06
Q4-33 | 8.37$\pm$0.05
Q4-A6 | 8.49$\pm$0.05
Q4-35 | 8.24$\pm$0.02
Q4-40 | 8.77$\pm$0.19
Q4-56 | 8.31$\pm$0.03