# MUSE-ALMA Haloes IX: Morphologies and Stellar Properties of Gas-rich
Galaxies

Arjun Karki1, Varsha P. Kulkarni1, Simon Weng2,3,4,5, Céline Péroux2,6, Ramona
Augustin7, Matthew Hayes8, Mohammadreza Ayromlou9, Glenn G. Kacprzak10,5, J.
Christopher Howk11, Roland Szakacs2, Anne Klitsch12, Aleksandra Hamanowicz7,
Alejandra Fresco13, Martin A. Zwaan2, Andrew D. Biggs2, Andrew J. Fox14, Susan
Kassin7, Harald Kuntschner2
1 Department of Physics and Astronomy, University of South Carolina, Columbia,
SC 29208, USA
2 European Southern Observatory, Karl-Schwarzschildstrasse 2, D-85748 Garching
bei München, Germany
3 Sydney Institute for Astronomy, School of Physics, University of Sydney, NSW
2006, Australia
4 ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
5 ATNF, CSIRO Astronomy and Space Science, PO Box 76, Epping, NSW 1710,
Australia
6 Aix Marseille Université, CNRS, LAM (Laboratoire d’Astrophysique de
Marseille) UMR 7326, 13388, Marseille, France
7 Space Telescope Science Institute, 3700 San Martin Drive, Baltimore,
MD21218, USA
8 Stockholm University, Department of Astronomy and Oskar Klein Centre for
Cosmoparticle Physics, AlbaNova University Centre, SE-10691, Stockholm, Sweden
9Universität Heidelberg, Zentrum für Astronomie, Institut für theoretische
Astrophysik, Albert-Ueberle-Str. 2, 69120 Heidelberg, Germany
10 Centre for Astrophysics and Supercomputing, Swinburne University of
Technology, Hawthorn, Victoria 3122, Australia
11 Department of Physics, University of Notre Dame, Notre Dame, IN46556, USA
12 DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 128, 2200
Copenhagen, Denmark
13 Max-Planck-Institut für Extraterrestrische Physik (MPE), Giessenbachstrasse
1, D–85748 Garching, Germany
14 AURA for ESA, Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD 21218
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

Understanding how galaxies interact with the circumgalactic medium (CGM)
requires determining how galaxies’ morphological and stellar properties
correlate with their CGM properties. We report an analysis of 66 well-imaged
galaxies detected in _HST_ and VLT MUSE observations and determined to be
within $\pm$500 km s-1 of the redshifts of strong intervening quasar absorbers
at $0.2\lesssim z\lesssim 1.4$ with H i column densities $N_{\rm HI}$ $>$
$10^{18}$ $\rm cm^{-2}$. We present the geometrical properties (Sérsic
indices, effective radii, axis ratios, and position angles) of these galaxies
determined using GALFIT. Using these properties along with star formation
rates (SFRs, estimated using the H$\alpha$ or [O II] luminosity) and stellar
masses ($M_{*}$ estimated from spectral energy distribution fits), we examine
correlations among various stellar and CGM properties. Our main findings are
as follows: (1) SFR correlates well with $M_{*}$, and most absorption-selected
galaxies are consistent with the star formation main sequence (SFMS) of the
global population. (2) More massive absorber counterparts are more centrally
concentrated and are larger in size. (3) Galaxy sizes and normalized impact
parameters correlate negatively with $N_{\rm HI}$, consistent with higher
$N_{\rm HI}$ absorption arising in smaller galaxies, and closer to galaxy
centers. (4) Absorption and emission metallicities correlate with $M_{*}$ and
sSFR, implying metal-poor absorbers arise in galaxies with low past star
formation and faster current gas consumption rates. (5) SFR surface densities
of absorption-selected galaxies are higher than predicted by the Kennicutt-
Schmidt relation for local galaxies, suggesting a higher star formation
efficiency in the absorption-selected galaxies.

###### keywords:

Galaxies: structure – Galaxies: evolution – Galaxies: formation

††pubyear: 2022††pagerange: MUSE-ALMA Haloes IX: Morphologies and Stellar
Properties of Gas-rich Galaxies–A

##  1 Introduction

The circumgalactic medium (CGM) has become increasingly recognized as an
important component of the baryonic Universe. It serves as a transition region
between the galaxy disk and the intergalactic medium (IGM) (Tumlinson et al.,
2017). Metal-poor IGM gas is believed to flow into the galaxy, passing through
the CGM. This gas is converted into stars and progressively enriched
chemically. The outflows driven by the supernovae [or active galactic nuclei
(AGN)] transfer the enriched gas back into the IGM, also passing through the
CGM. This cosmic baryon cycle regulates star formation in the galaxy (Péroux &
Howk, 2020). Given the central role of the CGM in this cycle, it is expected
to play a major role in the evolution of the galaxy. Understanding how the CGM
interacts with galaxies requires analyzing how the stellar properties of the
galaxies are dictated by and, in return, influence the CGM properties.

The stellar properties of the galaxies are described by measurements of
various properties that depend directly on their stellar populations – for
example, photometric magnitudes, colors, star formation rates (SFRs), and
stellar masses. The morphologies of the galaxies are closely coupled to these
properties. They can be expressed in terms of various quantitative measures of
the surface brightness distribution such as the effective radius ($R_{e}$),
axis ratio (_b/a_), and Sérsic index ($n$). Broadly speaking, galaxies fall
into two main types in the color-magnitude diagrams – the “blue cloud”
consisting of the late-type, more actively star-forming galaxies, and the “red
sequence” of early-type, more passive galaxies that have their star formation
quenched (e.g. Kauffmann et al., 2003; Buta, 2011).

The “size” of a galaxy detected in optical light depends on its stellar mass
and the rate of star formation, which are governed by the dark matter halo and
the galaxy’s formation history. Massive galaxies are larger and have higher
SFRs. (Mowla et al., 2019). The slope of the size versus stellar mass relation
is shallower for late-type galaxies than for early-type galaxies (e.g. Shen et
al., 2003; van der Wel et al., 2014). This difference may be due to dry minor
mergers, which can lead to a size growth caused by adding an outer envelope
without adding as much mass. Galaxies that undergo repeated dry minor mergers
tend to have a larger size (e.g. Hilz et al., 2013; Carollo et al., 2013). The
star formation caused by gas-rich mergers can also lead to the formation of
larger disks. The different evolutionary paths taken by early-type and late-
type galaxies thus result in different size-mass relationships.

The direct observation of emissions from the gas inflows and outflows passing
through the CGM is difficult due to the very low gas density. Absorption
spectroscopy of background sources such as quasars or gamma-ray bursts (GRBs)
provides an alternative and powerful technique to study these gas flows.
Damped Ly$\alpha$ (DLA) and sub-Damped Ly$\alpha$ (sub-DLA) systems provide a
huge reservoir of neutral hydrogen required for star formation (e.g. Péroux et
al., 2003; Wolfe et al., 2005; Prochaska & Wolfe, 2009; Noterdaeme et al.,
2012; Kulkarni et al., 2022). DLAs ($N_{\rm HI}$ $\geq$ 2 $\times$ $10^{20}$
$\rm cm^{-2}$) and sub-DLAs ($10^{19}$ $\leq$ $N_{\rm HI}$ < 2 $\times$
$10^{20}$ $\rm cm^{-2}$) permit measurements of a variety of metal ions, and
are therefore among the best-known tracers of element abundances in distant
galaxies (e.g. Kulkarni et al., 2005; Rafelski et al., 2012; Som et al., 2015;
Fumagalli et al., 2016).

Although the absorption technique provides an effective tool to probe gas
along the sight line to the background object, it cannot provide information
about the galaxy in which the absorption arises (e.g. Bergeron, 1986; Bergeron
& Boissé, 1991). Also, detecting galaxies associated with absorbers in the
vicinity of the quasar using imaging and spectroscopy was not always effective
in past studies, since the galaxies selected for spectroscopic study were
sometimes found to be offset in redshift from the absorber. The technique of
integral field spectroscopy (IFS) provides an efficient method for detecting
galaxies associated with the absorbers, and thus connecting stellar properties
with gas properties (Péroux et al., 2019, 2022). Several surveys (e.g., MusE
GAs FLOw and Wind (MEGAFLOW; Schroetter et al., 2016), MUSE Ultra Deep Field
(MUDF; Fossati et al., 2019) and MUSE Analysis of Gas around Galaxies (MAGG;
Dutta et al., 2020; Lofthouse et al., 2020, 2023)) have used the power of IFS
to search for sources traced by Mg ii and H i absorption and studied the gas
properties of CGM. While the Bimodal Absorption System Imaging Campaign (BASIC
survey; Berg et al., 2022), has studied H i selected partial Lyman limit
systems (pLLSs) and Lyman limit systems (LLSs) to search for absorber-
associated galaxies, the Cosmic Ultraviolet Baryon Survey (CUBS; Chen et al.,
2020) has studied the galactic environments of Lyman limit systems (LLSs) at
$z_{\rm abs}<1$ using IFS observations. Another survey, MUSE Quasar-field
Blind Emitters Survey (MUSEQuBES; Muzahid et al., 2020) searched for
Ly$\alpha$ emitters (LAEs) at the redshift of the absorbers using guaranteed
time observations with the Multi-Unit Spectroscopic Explorer (MUSE; Bacon et
al., 2010) on the Very Large Telescope (VLT).

We have surveyed a large number of absorption-selected galaxies with VLT MUSE
and the Atacama Large Millimetre/submillimetre Array (ALMA; Wootten &
Thompson, 2009) as part of our MUSE-ALMA Haloes Survey, and have recently
imaged these galaxies with the Hubble Space Telescope (HST). The _HST_ images
provide high-resolution broadband continuum imaging of the galaxies, while the
MUSE data provide IFS of the galaxies, thus providing information about the
spatial distribution of gas kinematics, SFRs and emission-line metallicity.
The kinematics measured from the IFS also allows estimates of the dynamical
masses of the galaxies (e.g., Péroux et al., 2012; Bouché et al., 2013). Thus,
combining _HST_ images and MUSE IFS provides a powerful approach to studying
the morphologies and stellar content of absorption-selected galaxies and
relating them to the CGM gas properties. Together, the stellar and gas
properties can be used to put improved constraints on the evolution of
galaxies and their CGM.

The MUSE-ALMA Haloes (MAH) survey targets the fields of 32 H i rich absorbers
at redshift 0.2 $\leq$ zabs $\leq$ 1.4 detected in sight lines to 19 quasars.
These 32 absorbers were detected in HST FOS, COS, or STIS UV spectra. Most of
our quasars also have optical high-resolution spectra from VLT/UVES,
X-Shooter, or Keck/HIRES with spectral resolutions ranging from 4000-18 000
(X-shooter), 45 000-48 000 (HIRES) and up to 80 000 (UVES). The H i column
densities determined from these UV spectra (with resolution R $=$ 20 000$-$30
000) are found to be $N_{\rm HI}$ > $10^{18}$ $\rm cm^{-2}$. Information about
quasar spectra and an overview of the survey are provided in Péroux et al.
(2022). In this paper, we focus on 66 galaxies observed in the HST images that
lie within a radial velocity range of $\pm$ 500 km $\rm s^{-1}$ of the
redshifts of 25 H i rich absorbers (the remaining 7 absorbers having no
associated galaxies within $\pm$ 500 km $\rm s^{-1}$). The paper is organized
as follows: section 2 presents the sample selection and observations. Section
3 details the results derived from the observation. Section 4 summarizes our
findings. We adopt the following cosmology parameters: $\rm H_{\rm o}=70$ $\rm
km$ $\rm s^{-1}$ $\rm Mpc^{-1}$, $\Omega_{M}=0.3$ and $\Omega_{\Lambda}=0.7$
throughout the paper.

Table 1: Summary of HST observations. Listed are the quasar name, quasar and absorber redshifts, the full-width half maximum of the PSF of _HST_ image in each filter, the field of view, the _HST_ camera and filter used, the number of exposures $\&$ exposure time of each exposure and the 3-$\sigma$ limiting magnitude in each filter. A complete table of quasar fields and their properties is available as machine-readable online material.  Quasar | $z_{\rm qso}$ | $z_{\rm abs}$ | FWHM | FOV | Instrument |  $\rm n_{\rm exp}$ $\times$ $\rm t_{\rm exp}$ | Magnitude
---|---|---|---|---|---|---|---
|  |  | (") | (" $\times$ ") |  | [s] | limit
Q0058$+$0019 | 1.959 | 0.6127 | 0.188 | 80 $\times$ 80 | WFPC2/WF3 F702W | 4 $\times$ 1100 | 27.02
Q0138$-$0005 | 1.340 | 0.7821 | 0.073 | 160 $\times$80 | WFC3/UVIS F475W | 4 $\times$ 567 | 28.70
… | … | … | 0.083 | 160 $\times$ 80 | WFC3/UVIS F625W | 4 $\times$ 591 | 28.90
… | … | … | 0.130 | 123 $\times$ 123 | WFC3/IR F105W | 4 $\times$ 603 | 27.93
J0152$-$2001 | 2.060 | 0.3897 | 0.083 | 160 $\times$ 80 | WFC3/UVIS F336W | 2 $\times$ 587 + 2 $\times$ 595 | 29.39
… | … | 0.7802 | 0.074 | 160 $\times$ 80 | WFC3/UVIS F475W | 2 $\times$ 587 + 2 $\times$ 595 | 29.29
… | … | … | 0.182 | 80 $\times$ 80 | WFPC2/WF3 F702W | 2 $\times$ 1100 + 3 $\times$ 1300 + 1 $\times$ 1400 | 27.68
Q0152$+$0023 | 0.589 | 0.4818 | 0.083 | 160 $\times$ 80 | WFC3/UVIS F336W | 2 $\times$ 535 + 2 $\times$ 518 | 28.54
… | … | … | 0.074 | 160 $\times$ 80 | WFC3/UVIS F475W | 1 $\times$ 635 + 3 $\times$ 618 | 28.39
… | … | … | 0.082 | 160 $\times$ 80 | WFC3/UVIS F814W | 1 $\times$ 635 + 3 $\times$ 618 | 27.92
… | … | … | … | … | … | … | …
Figure 1: Median stacked image of Q0152+0023 in the F814W UVIS filter-band.
The image is created by combining all the individual exposure images, which
helps to remove the cosmic ray effects and bad pixels and improve the signal-
to-noise ratio. This enables us to study the morphological properties of the
galaxy populations robustly. The solid red circles represent the position of
the associated galaxies in the field of view, while a dotted black circle
denotes the QSO’s position. The astropy PHOTUTILS package was used to detect
the associated galaxies in the given quasar field. The associated galaxies are
located within $\pm$ 500 km $\rm s^{-1}$ of the absorber’s redshift. The
redshift of those galaxies came from MUSE data. The scale corresponds to 40
kpc at $z_{\rm abs}$ = 0.4818. The object identification number (ID) of these
galaxies came from the MUSE-ALMA Haloes master table listed in Péroux et al.
(2022).

##  2 HST images and Observations

Our primary _HST_ imaging dataset comes from the broad-band imaging
observations performed in GO Program ID 15939 (PI: Péroux) with the Wide Field
Camera-3 (WFC3). These data were complemented by archival Wide Field and
Planetary Camera-2 (WFPC2) or WFC3 images obtained in programs 5098, 5143,
5351, 6557, 7329, 7451, 9173, and 14594 (PIs Burbidge, Macchetto, Bergeron,
Steidel, Malkan, Smette, Bechtold, Bielby, respectively). The observations
consisted of multiple dithered exposures in a variety of filters. Further
details about these observations and the observation strategy used for our own
program (PID 15939) can be found in Péroux et al. (2022).

The data were reduced using the calwf3 or calwf2 pipelines. For each filter,
the sky-subtracted, aligned images from the individual exposures were median-
combined to produce the final images. Figure 1 and Figure 2 show examples of
final full-frame images and zoomed-in sections near the quasar. The quasar
point spread function (PSF) has been subtracted in the zoomed-in frame to
search for galaxies at small angular separations from the quasar. The PSF in
each filter and instrument for each given quasar field was constructed using
observations of all remaining quasar fields from our sample in the same band
and instrument. For each such image used in making the PSF, we masked the
objects other than the central quasar and performed sky subtraction. All such
processed images were aligned spatially and coadded after the flux levels in
the outer wings of the PSF were scaled to match with each other. The resulting
PSF thus constructed was subtracted from the quasar field of interest after
matching the flux levels of the two images. The PSF-subtracted images thus
produced were used to search for galaxies near the quasars. This approach is
similar to that used in previous works (e.g. Kulkarni et al., 2000, 2001; Chun
et al., 2010; Straka et al., 2011; Augustin et al., 2018). Object detections
and astrometric and photometric measurements were performed using the astropy
package photutils. The data reduction, PSF construction, PSF subtraction, and
photometric measurements are further detailed in Péroux et al. (2022).

Figure 2: Left panel: Median stacked zoomed-in image of Q1515+0410 in the
F814W UVIS filter-band. The image shows the bright background quasar
exhibiting strong diffraction spikes where a galaxy is in front of it. The
dotted black and solid red circles denote the location of the quasar and the
galaxy in the image. The quasar’s light contaminates the galaxy’s image.
Middle panel: A Point Spread Function (PSF) constructed to remove quasar’s
contamination. The PSF is designed using observations of all other quasar
fields from our sample in the same filter. Right panel: PSF subtracted image
of the same zoomed-in image. The contamination of the quasar on the galaxy is
removed after performing a careful PSF-subtraction. Detailed information about
PSF construction and PSF subtraction is provided in Péroux et al. (2022).

Using the MUSE observations along with the _HST_ imaging, a total of 3658
sources were detected in all of our fields. The MUSE Line Emission Tracker
(MUSELET) tool of the MPDAF package was used to detect sources with emission
lines, and the profound R Package was used to identify continuum sources in
the MUSE fields. A final master table was produced by matching the sources
detected in the HST images with the MUSE results using the topcat tool.
Spectroscopic redshifts were determined for 703 objects out of the 3658
sources detected in all fields using the marz tool on the VLT/MUSE spectra.
The remaining objects do not have spectroscopic redshifts, because they were
either detected outside of the MUSE field of view or too faint to estimate a
redshift. We refer the reader to Péroux et al. (2022) for a detailed
methodology regarding the redshift measurements and for the master table of
all targets.

LABEL:table1 provides a summary of _HST_ imaging observations for 18 quasar
fields. The high spatial resolution of the broad-band _HST_ images allowed us
to detect several sources nearby or far away from the quasar sightlines, which
were undetected in the MUSE cubes. The _HST_ images also enabled us to detect
and resolve several sources near the quasars whose redshifts are not well
known. While the MUSE data allowed us to study the emission properties of
galaxies, the study of geometrical properties of the galaxies and structural
features such as tidal tails are difficult to discern in MUSE images due to
insufficient spatial resolution. The high-resolution _HST_ images also allowed
us to study the morphologies of the galaxies and structural details.

The MUSE data show 79 associated galaxies within $\pm$ 500 km s-1 of the
absorber redshifts. Out of the total of 32 absorbers, 19 (59$\%$) have two or
more associated galaxies, 7 (22$\%$) have one associated galaxy and the
remaining 6 (19$\%$) have no associated galaxy detected within $\pm$ 500 km
s-1 of the absorption redshift. A detailed explanation of how these associated
galaxies were selected is provided in Weng et al. (2023). Out of these 79
galaxies, 9 galaxies were detected in emission only in MUSE fields (but not in
_HST_ images), one galaxy was detected at the edge of the _HST_ image, and
three galaxies were detected in the archival _HST_ images but were too faint
to perform reliable morphological measurements. Therefore, we analyzed the
remaining 66 associated galaxies in the 18 _HST_ fields.

Table 2: Results of our GALFIT morphological modeling, impact parameters (b), and surface brightness of the gas-rich galaxies. The listed parameters are the quasar name, object IDs from Péroux et al. (2022), impact parameters of the quasar sightlines from the galaxy centers, k-corrected absolute magnitude in the UVIS F814W filter, Sérsic index, effective radius, axis ratio, position angle (PA) of the major axis, absolute surface brightness averaged within the effective radii of the galaxies and goodness of fit. A complete table of associated galaxies and their properties is available as machine-readable online material.  Object | ID | b | Absolute mag | _n_ | _$R_{e}$_ | _b/a_ | PA | $<\mu_{\rm eff}>$ | $\chi^{2}_{\nu}$ |
---|---|---|---|---|---|---|---|---|---|---
|  | [kpc] | [F814W] |  | [kpc] |  | [deg.] | [mag $\rm arcsec^{-2}$] |  |
Q0138$-$0005 | 14 | 79.7 | $-21.39\pm 0.02$ | $0.84\pm 0.01$ | $1.92\pm 0.02$ | $0.70\pm 0.01$ | $106.38\pm 0.74$ | $18.59\pm 0.03$ | 1.093 |
Q0152$-$2001 | 13 | 83.8 | $-20.60\pm 0.07$ | $1.88\pm 0.08$ | $6.12\pm 0.34$ | $0.57\pm 0.01$ | $136.06\pm 1.66$ | $21.90\pm 0.14$ | 1.127 |
Q0152$-$2001 | 4 | 170 | $-22.29\pm 0.01$ | $1.53\pm 0.02$ | $5.01\pm 0.06$ | $0.30\pm 0.00$ | $140.92\pm 0.22$ | $19.77\pm 0.03$ | 1.365 |
Q0152$-$2001 | 5 | 60.7 | $-21.46\pm 0.04$ | $1.24\pm 0.03$ | $6.55\pm 0.16$ | $0.32\pm 0.00$ | $154.40\pm 0.37$ | $21.19\pm 0.07$ | 1.136 |
… | … | … | … | … | … | … | … | … | … |
Figure 3: Results of the Sérsic profile fitting using galfit for the
associated galaxies presented in the Figure 1. The left panels show galaxy
images in UVIS/F814W band, the best-fitted Sérsic model (middle panels), and
residual images (right panels). The orientation of the images is the same as
Figure 1.  Figure 4: The frequency distribution of the Sérsic index (upper-
left), effective radius (upper-right), galaxy’s redshift (lower-left), and the
k-corrected absolute magnitude (lower-right) in UVIS/F814W filter of the 66
associated galaxies. In each panel, the vertical dashed black line represents
the median value. We used IDL-based software kcorrect to calculate $\rm
k$-corrections to the absolute magnitudes.

##  3 Analysis and Results

###  3.1 Morphological properties of associated galaxies

The galapagos software (Häußler et al., 2011) was used to study the
morphologies of the 66 galaxies associated with the absorbers in our MUSE-ALMA
halo sample. Galapagos uses sextractor (Bertin & Arnouts, 1996) for object
detection and galfit (Peng et al., 2002) for two-dimensional image
decomposition, and can be run in batch mode to analyze multiple objects. This
galapagos analysis was performed on the reddest images obtained for each
quasar field because these images in the red or near-infrared filters (WFPC2
F702W, F814W, WFC3 F105W, WFC3 F140W, or NICMOS F160W) provide far more
sensitive detection thresholds and enable better deblending of extended
sources compared to the bluer filters. The redder bands better sample the
cooler and older stars, which in turn more accurately follow the gravitational
potential.

Sérsic profiles were fitted to each of the sample galaxies. In each case, a
cutout region was created with the galaxy centered in the image. Depending on
the size of the galaxy, the cutout region ranged from 3" $\times$ 3" to 7"
$\times$ 7" in size, and included a sufficient number of pixels at the sky
level surrounding the source. Most of the cutout images show only the galaxy
without the presence of nearby sources. In cases where nearby sources were
present, they were masked using the segmentation map made using sextractor.
For each object, the best-fitting values of the morphological parameters were
determined so as to minimize the residual between the data and the fitted
Sérsic model. In cases where there were significant residuals or the parameter
values returned by galapagos had large errors, the morphological parameters
were determined by adding more Sérsic components and individually running
galfit iteratively until the parameter converged. As an example, Figure 3
shows the outcomes of the Sérsic profile fitting for the five associated
galaxies detected in the UVIS/F814W image of the quasar field presented in the
Figure 1. Each of these five galaxies were well-fitted using a single Sérsic
component.

Figure 5: The absolute surface brightness averaged within the effective radius
of the galaxies associated with H i absorbers plotted against the absolute
magnitude in the UVIS/F814W band. Sample and literature galaxies are divided
into two bins in terms of H i column density using the median value of column
density of H i ($N_{\rm HI,med}$ = 6.03 $\times$ $\rm 10^{19}$ $\rm cm^{-2}$).
Magenta and yellow symbols denote galaxies with $N_{\rm HI}$ < $N_{\rm
HI,med}$ and $N_{\rm HI}$ $\geq$ $N_{\rm HI,med}$, respectively. Diamonds
denote galaxies nearest to the quasar sight lines (in impact parameter) from
our _HST_ measurements, while open circles denote the most massive galaxies in
each quasar field at the redshift of the absorber. The literature values are
taken from Fynbo et al. (2011), Augustin et al. (2018), Rhodin et al. (2021).
For literature galaxies, we calculated the surface brightness within the
$R_{e}$ using the photometric magnitudes listed in the literature papers. The
stacked histograms show the distribution of the galaxies in both axes.

LABEL:Tab2 lists the morphological parameters ($R_{e}$, n, b/a and PA of the
major axis (in degrees east of north)) along with impact parameter,
k-corrected absolute magnitude, absolute effective surface brightness and
reduced chi-squared values determined from our analysis for each of the
galaxies using _HST_ images. The galaxy redshifts are based on the emission
line measurements from our MUSE observations, as described in Péroux et al.
(2022). The absolute magnitude for each galaxy was determined using the
apparent magnitude and luminosity distance for the assumed cosmological
parameters and $\rm k$-corrected.

Since our sample consists of galaxies at different redshifts observed in
various bandpasses, applying a $\rm k$ correction is essential to make a
meaningful comparison among them (Blanton & Roweis, 2007). The IDL-based
software kcorrect was used to calculate $\rm k$-corrections to the absolute
magnitudes. Figure 4 shows the distribution of the morphological properties
provided by galfit and the galaxies redshift of the associated galaxies. For
our sample galaxies, the Sérsic index ranges from 0.33 to 2.27 with a median
value of 0.86 $\pm$ 0.07. This suggests that most of the sample galaxies are
disks or dwarf spheroidals. Such disk galaxies exhibit an exponential light
profile (Kelvin et al., 2012). The effective radii of the sample galaxies
range from 0.68 kpc to 7.55 kpc with a median value of 2.85 $\pm$ 0.15 kpc,
and their absolute magnitudes (in F814W filter) range from -15.80 to -23.73
with a median value of -20.81 $\pm$ 0.07. The redshifts of the galaxies range
from $z$ = 0.19 to $z$ = 1.15, with a median value $z$ = 0.56.

Table 3: Stellar Properties of the gas-rich galaxies and other galaxies from
the literature. The listed parameters are the quasar name, galaxy ID, galaxy’s
redshift, specific star formation rate, SFR surface density, stellar mass
surface density and sSFR surface density. The entries marked “-999” correspond
to measurements that are unavailable. A complete table of associated galaxies
and their properties is available as machine-readable online material.

Object | ID | $\rm z_{gal}$ | Log sSFR | Log $\Sigma_{\rm SFR}$ | Log $\Sigma_{\rm M*}$ | Log $\Sigma_{\rm sSFR}$
---|---|---|---|---|---|---
|  |  | [$\rm yr^{-1}$] | [M$\odot$ $\rm yr^{-1}$ $\rm kpc^{\rm-2}$] | [M$\odot$ $\rm kpc^{-2}$] | [$\rm yr^{-1}$ $\rm kpc^{\rm-2}$]
Q0138-0005 | 14 | 0.7821 | $-8.96\pm 0.21$ | $-0.53\pm 0.15$ | $8.44\pm 0.15$ | $-10.33\pm 0.21$
Q0152-2001 | 13 | 0.3814 | $-11.46\pm 0.62$ | $-3.33\pm 0.58$ | $8.13\pm 0.22$ | $-13.83\pm 0.62$
Q0152-2001 | 4 | 0.3814 | $-999$ | $-999$ | $9.33\pm 0.08$ | $-999$
Q0152-2001 | 5 | 0.3826 | $-10.92\pm 0.17$ | $-2.10\pm 0.10$ | $8.82\pm 0.14$ | $-13.35\pm 0.17$
… | … | … | … | … | … | …

_Note:_ The SFRs and _M*_ for our sample galaxies are from Weng et al. (2023)
and Augustin et al. (in prep.), respectively. The SFR and _M*_ for the
literature sample are from a Augustin et al. (2018), b Rhodin et al. (2021), c
Christensen et al. (2014), d Zabl et al. (2019), e Lundgren et al. (2012) and
f Ma et al. (2018).

###  3.2 Stellar Properties of associated galaxies

The SFRs of the associated galaxies were measured using the H$\alpha$ emission
line for the sample galaxies with z $\leq$ 0.4, and with [O ii] emission lines
for the remaining galaxies (where the H$\alpha$ emission lines fall outside
the MUSE wavelength coverage). Dust-corrected SFRs were calculated for 13
galaxies at redshift z $<$ 0.4 with detections of H$\alpha$ and H$\beta$ using
the measured H$\beta$ and H$\alpha$ emission-line fluxes. For 15 galaxies,
only a 3-$\sigma$ upper limit could be placed on the SFR. A complete
description of the SFR estimates and dust correction on SFRs is provided by
Weng et al. (2023). The stellar masses ($M_{*}$), estimated by using the _HST_
broad-band magnitudes and performing spectral energy distribution (SED) fits
using the photometric redshift code le phare (Arnouts et al., 1999; Ilbert et
al., 2006), were found to span a wide range 7.8 $<$ log $M_{*}$ $<$ 12.4.
Further detail about the stellar mass determination is provided in Augustin et
al. (in prep).

The SFR surface density and average stellar mass density within the effective
radius were calculated as

$\qquad\qquad\qquad\qquad\Sigma_{\rm SFR}=\frac{\rm SFR}{\rm 2\pi R^{2}_{e}}$
(1)

$\qquad\qquad\qquad\qquad\Sigma_{\rm M_{*}}=\frac{M*}{2\pi\rm R^{2}_{e}}$ (2)

The absolute effective surface brightness, <$\mu_{\rm eff}$> (mag $\rm
arcsec^{-2}$), averaged within the effective radius for our galaxies were
calculated based on the $\rm k$-corrected absolute magnitude and the effective
radius using the following expression (Graham & Driver, 2005):

$\qquad\qquad\rm<\mu_{\rm eff}>=\rm M+5\log_{10}\rm(R_{\rm e})+38.57$ (3)

LABEL:table3 lists the derived stellar properties of the galaxy populations.

Table 4: Absorption properties of the gas-rich galaxies and other absorbers
from the literature. Listed are the name of the quasar field, absorber
redshift, impact parameter of the nearest galaxy, normalized impact parameter
(b/$\rm R_{e}$), H i column density, rest equivalent widths of Mg II
$\lambda$2796 and Fe II $\lambda$2600 and the absorption metallicities. The
absorption metallicities listed here are the observed values (based on
generally Zn) in the quasar sightlines. The last column lists the references
for the impact parameter, absorber rest-frame equivalent widths, absorption
metallicity, and the H i column density. See the text for more details. The
entries marked “-999” correspond to measurements that are unavailable. A
complete table of absorption properties is available as machine-readable
online material.

Object | $\rm z_{abs.}$ | b | b/$\rm R_{e}$ | log $N_{\rm HI}$ |  $\rm W_{\rm r}$ Mg II 2796 |  $\rm W_{\rm r}$ Fe II 2600 | $\rm[X/H]_{\rm abs}$ | X | References
---|---|---|---|---|---|---|---|---|---
|  | [kpc] |  | [$\rm cm^{-2}$] | [Å] | [Å] |  |  |
Q0138$-$0005 | 0.7821 | 79.70 | $41.50\pm 0.22$ | $19.81\pm 0.08$ | $1.21\pm 0.10$ | $1.10\pm 0.11$ | $0.28\pm 0.16$ | Zn | [1, 4, 21, 30]
Q0152$-$2001 | 0.7802 | 54.30 | $9.28\pm 0.27$ | $18.87\pm 0.12$ | $0.36\pm 0.04$ | <$0.30$ | $-999$ | $-999$ | [1, 30]
Q0152$-$2001 | 0.3830 | 60.70 | $9.26\pm 0.22$ | <$18.80$ | $0.58\pm 0.05$ | $-999$ | $-999$ | $-999$ | [1, 5, 30]
Q0152+0023 | 0.4818 | 120.90 | $62.64\pm 2.31$ | $19.78\pm 0.08$ | $1.34\pm 0.06$ | $0.88\pm 0.06$ | -999 | $-999$ | [1, 30]
… | … | … | … | … | … | … | … | … | …

References: $[1]$ This work $[2]$ Hamanowicz et al. (2020), $[3]$ Boisse et
al. (1998), $[4]$ Péroux et al. (2008), $[5]$ Rahmani et al. (2018), $[6]$
Prochaska et al. (2007), $[7]$ Fynbo et al. (2011), $[8]$ Bashir et al.
(2019), $[9]$ Krogager et al. (2017), $[10]$ Hartoog et al. (2015), $[11]$
Zafar et al. (2017), $[12]$ Bouché et al. (2012), $[13]$ Berg et al. (2016),
$[14]$ Wolfe et al. (2008), $[15]$ Kashikawa et al. (2014), $[16]$ Christensen
et al. (2014), $[17]$ Augustin et al. (2018), $[18]$ Rhodin et al. (2021),
$[19]$ Péroux et al. (2011), $[20]$ Péroux et al. (2019), $[21]$ Péroux et al.
(2008), $[22]$ Rhodin et al. (2018), $[23]$ Boisse et al. (1998), $[24]$
Rahmani et al. (2016), $[25]$ Péroux et al. (2016), $[26]$ Wolfe & Wills
(1977), $[27]$ Kacprzak et al. (2011), $[28]$ Berg et al. (2017), $[29]$
Churchill (2001), $[30]$ Rao et al. (2006), $[31]$ Meiring et al. (2007),
$[32]$ Ledoux et al. (2006), $[33]$ Ma et al. (2018), $[34]$ Lundgren et al.
(2012), $[35]$ Zabl et al. (2019)

###  3.3 Absorption Properties of associated galaxies

The MUSE-ALMA Haloes survey analyzed the absorption properties of 32 H i rich
absorbers with $N_{\rm HI}$ > $10^{18}$ $\rm cm^{-2}$ using 19 quasar fields.
Using the _HST_ images of the 18 quasar fields, we detected 66 galaxies within
$\pm$ 500 km $\rm s^{-1}$ of the absorber redshift for 25 absorbers.
LABEL:table4 lists the impact parameters of the quasar sightlines from the
galaxy centers and the absorption properties along these sightlines for the
sample galaxies and the galaxies from the literature. The impact parameters of
these 66 associated galaxies are measured from the astrometry of the _HST_
images. The measurements of the column density of H i, absorption
metallicities, and the equivalent widths of the Fe II $\lambda$ 2600 and Mg II
$\lambda$ 2796 absorption lines are from various references in the literature.

The absorption metallicities listed for the DLAs and sub-DLAs in the sample
(available for 4 out of the 25 absorbers) are based on the Zn abundance
without corrections for ionization and (in most cases) dust depletion. The
effect of dust depletion is expected to be modest, since Zn is a volatile
element that is far less depleted in the interstellar medium (ISM) of the
Milky Way compared to refractory elements such as Fe (e.g. Jenkins, 2009;
Vladilo et al., 2011). Indeed, Zn is often used as the metallicity indicator
in DLA/sub-DLAs for these reasons. Ionization corrections are known to be
small for DLAs (Muzahid et al., 2016; Péroux & Howk, 2020). For sub-DLAs
(which tend to be more ionized than DLAs), the ionization corrections for Zn
abundance are found to be $\lesssim$0.2 dex (e.g., Meiring et al., 2009). We,
therefore, select only the absorbers with Zn abundance measurements for
comparison of the absorption metallicities with the stellar properties of the
galaxies in the following sections. Finally, we note that emission-line
metallicities are also available for our galaxies, and were measured using the
$R_{3}$ calibration from Curti et al. (2017). A complete description of the
galaxy metallicity estimates is provided in Weng et al. (2023).

Figure 6: Upper panel: SFR vs. stellar mass for galaxies associated with gas-
rich absorbers. The gray stars denote galaxies from Zabl et al. (2019) whose H
i column density is more uncertain [not based on the actual Ly$\alpha$
absorption profile, but estimated from the Mg ii $\lambda$2796 equivalent
width using the relation from Ménard & Chelouche (2009)]. Yellow and magenta
stars denote galaxies from Fynbo et al. (2011), Krogager et al. (2012),
Christensen et al. (2014), Augustin et al. (2018) and Rhodin et al. (2021).
All other symbols are as in Figure 5. The solid black line shows the star
formation main sequence from Boogaard et al. (2018) at the median redshift of
the sample galaxies. The blue and red dashed lines show the 1-$\sigma$
deviations from the SFR-_M*_ relations at $z_{\rm min}$ and $z_{\rm max}$ of
the full sample of absorber-associated galaxies (including galaxies from both
our MAH sample and the literature). Lower panel: plot of the difference in the
observed SFR and the expected SFR from the SFMS at $z_{\rm med}$ taken from
Boogaard et al. (2018) at the observed stellar mass vs. the stellar mass. The
blue and red dashed lines show the difference relative to the SFMS at $z_{\rm
med}$ for the lower and upper 1-$\sigma$ SFMS at $z_{\rm min}$ and $z_{\rm
max}$.  Figure 7: Mass-size and mass-concentration relationships of the
associated galaxies. Left panel: plot of stellar mass against the effective
radius. The solid blue line is the scaling relationship between the mass and
size of the star-forming galaxies (SFG) from Ichikawa et al. (2012) for the
redshift of 0.50 < z < 0.75. Right panel: plot of stellar mass against the
Sérsic index. The plots suggest that massive galaxies are bigger in size and
more concentrated. The gray stars in the left panel are the literature sample
from Zabl et al. (2019) whose H i column density is estimated from the Mg ii
$\lambda$2796 equivalent widths using the relation from Ménard & Chelouche
(2009). All other symbols are as in Figure 5.

##  4 Discussion

Using the high-resolution _HST_ images and the integral field spectroscopy
provided by MUSE, we have studied and analyzed the morphological and stellar
properties of 66 associated galaxies. The two powerful software: galapagos and
le phare, provide ample information about the structural and stellar
properties of those gas-rich galaxies. The following sections discuss the
scientific results, compare the associated galaxies with the general galaxy
population, and explore the connection between their stellar and absorption
properties.

###  4.1 Literature Sample

To examine how the properties of the galaxies in our sample compare to other
absorption-selected galaxies, we use a comparison sample compiled from the
literature. Specifically, this literature sample consists of 61 galaxies
detected at the redshifts of known gas-rich absorbers from the IFS surveys of
the CGM (see references listed in LABEL:table4). These literature galaxies
range in redshift from 0.10 to 3.15, and in impact parameter from $\sim$3 kpc
to 88 kpc. The H i column density of some of the literature galaxies (Zabl et
al., 2019, denoted as grey stars in the figures) are estimated from the Mg ii
$\lambda$2796 equivalent widths using the relation from Ménard & Chelouche
(2009). Three absorbers from this literature sample have multiple galaxies at
the absorber redshifts (Augustin et al., 2018). In these cases, if combined
measurements of stellar properties were available, we adopted those values and
treated those multiple sources as a single source. The stellar masses for the
galaxies in the literature sample were derived from SED fitting in most cases,
and using the tight correlation between $M_{*}$ and a dynamical estimator,
i.e. a function of galaxy velocity dispersion and rotational velocity
(Schroetter et al., 2019) in a few cases. The SFRs were measured using
H$\alpha$, Ly$\alpha$, or [O ii] emission line fluxes. The emission
metallicities for the literature sample are from Christensen et al. (2014),
Augustin et al. (2018), and Rhodin et al. (2018).

###  4.2 Correlations between stellar and absorption properties

To assess the correlations between the various properties of the galaxies
associated with the absorbers, we use the Spearman rank-order correlation
method to evaluate the correlation coefficient ($r_{s}$) and the probability
($p$) that the observed value of $r_{s}$ could occur purely by chance. In
cases where there is a mixture of detections and limits (i.e., in the presence
of censored data), we use the survival analysis method to calculate the
Spearman correlation coefficient (as implemented in the Image Reduction and
Analysis Facility (IRAF; Tody, 1986) task spearman). The survival analysis
method uses the Kaplan-Meier estimate of the survival curve to assign ranks to
the observations that include censored points. Censored points are assigned
half (for upper limits) or twice (for lower limits) the rank that they would
have had were they uncensored.

Given that the literature sample is based on observations obtained with
different selection methods, it is useful to ask how much the correlations are
affected by the inclusion or exclusion of the literature sample. With this in
mind, we computed the $r_{s}$ and $p$ values between the various properties
for both our own sample, and a larger sample after including the literature
galaxies. LABEL:table5 lists the results of these correlation calculations. In
the following subsections, we discuss some of the key implications of our
analysis to address two major questions: How do absorber-selected galaxies
compare to the general galaxy population? How do stellar and absorption
properties relate?

Figure 8: The effective radii plotted against the impact parameter color-coded
by column density of neutral hydrogen of the galaxies sample. The diamond
symbols are the sample galaxies that lie closest to the quasar sightline,
while open circles stars denote the most massive galaxies of each quasar at
the redshift of the absorber. The stars are the literature sample galaxies.
The red and blue dashed lines correspond to $\rm b=R_{vir}$, and $\rm
b=R_{vir}/2$, respectively, taking the approximate relation between the
effective radius and the virial radius. From the plot, we see most of the
sample galaxies are found at or within the $\rm R_{vir}$ and more than half of
the sample galaxies are found at or within the half of the $\rm R_{vir}$. It
is also interesting to see that all the galaxies that are closest to the
quasar’s sightlines are within the virial radius. Most of the gas-rich
galaxies are located in the region near the galactic center and fewer gas-rich
absorbers are found to be tracing CGM at a larger distance.

###  4.3 Do gas-rich galaxies differ from the general population?

We now compare the absorber-associated galaxies from our sample and the
literature with the properties of the overall galaxy population. While making
these comparisons, we examine whether there is a difference between galaxies
associated with high and low H i column densities, and also between small vs.
large impact parameters. The galaxies with the lowest impact parameters may be
thought of as the host galaxies of the absorbers (e.g. Schroetter et al.,
2016; Weng et al., 2023). In most cases (18 out of 24), the galaxies with the
lowest impact parameters are also the most massive galaxies.

####  4.3.1 Dependence of $\mu_{\rm eff}$ on luminosity

Figure 5 shows the absolute effective rest-frame surface brightness against
absolute magnitude relation, where the galaxies are color-coded by the H i
column density of the absorber associated with the galaxy. A clear positive
correlation ($r_{s}$ $=$ 0.76 and _p_ $=$ 4.19 $\times$ $10^{-16}$) is
observed, consistent with results from past studies (e.g. McConnachie, 2012;
Karachentsev et al., 2013; Seo & Ann, 2022). However, we find no substantial
difference between the trends for the lowest and intermediate column density
bins. The trend appears to be flatter for the lowest luminosity galaxies,
especially for galaxies associated with the highest H i column density
absorbers. This finding is consistent with past suggestions that the highest H
i column density absorbers may be associated with dwarf galaxies (Kulkarni et
al., 2010). We also analyzed a plot similar to Figure 5 by sub-sampling our
sample galaxies into two redshift bins using the median redshift of the sample
galaxies. No significant differences are observed between z and $N_{\rm HI}$
sub-samples.

####  4.3.2 Dependence of SFR on stellar mass

Figure 6 shows a plot of the SFR vs. stellar mass, revealing a strong
correlation with $r_{s}$ = 0.41 and $p$ = 1.24 $\times$ $10^{-4}$. Also shown
for comparison is the SFR-$M_{*}$ relation, i.e. the star formation main
sequence (SFMS) for galaxies at $\rm z$ $=$ 0.56, the median redshift of our
full sample of absorber-associated galaxies (based on the SFMS from Boogaard
et al., 2018). Since the SFMS evolves with redshift and our full sample covers
a wide redshift range, we show the 1-$\sigma$ deviations from the SFMS
relations at $\rm z$ $=$ 0.10 and $\rm z$ $=$ 3.15 (the minimum and maximum
redshifts of our full sample).

Most galaxies associated with strong intervening quasar absorbers appear to be
consistent with the SFMS within the uncertainties. We note, however, that a
small fraction of high-mass galaxies lie below the SFMS. The lower panel of
Figure 6 shows the deviation from the SFMS vs. $M_{*}$. The deviation seems to
be highest for galaxies with the highest stellar mass. Similar conclusions
were also reached by Kulkarni et al. (2022). We note, however, that dust
corrections for SFRs were not possible for most of these galaxies (12 out of
the 14 galaxies with $M_{*}>10^{10}\rm M_{\odot}$ showing $>2\sigma$ deviation
from the SFMS), and the true SFRs for these galaxies could be higher.

Figure 9: The rest-frame equivalent width of Mg II $\lambda$ 2796 plotted
against the stellar mass. All symbols are as in Figure 5. The stellar mass of
the galaxies is anti-correlated with the column density of H i gas (Augustin
et al., 2018) while the $N_{\rm HI}$ positively correlates with the equivalent
width of the metal lines (Rao et al., 2006). The massive galaxies will have
lower metal line strengths, while the less massive galaxies are found to
possess strong metal line strengths.

####  4.3.3 Dependence of Stellar mass on Sérsic index and size

Figure 7 shows plots of the stellar mass vs. the effective radius and Sérsic
index. Also shown for comparison is the mass-size scaling relationship for
galaxies at 0.50 $<$ $z$ $<$ 0.75 adopted from Ichikawa et al. (e.g. 2012).
$M_{*}$ appears to be strongly correlated with the effective radius ($r_{s}$
$=$ 0.49, $p$ = 9.77 $\times$ $10^{-7}$). A similar result was found in
previous studies (e.g. Ichikawa et al., 2012). A positive correlation is
observed between the Sérsic index and stellar mass with $r_{s}$ $=$ 0.43 and
$p$ = 2.51 $\times$ $10^{-4}$. The more massive galaxies tend to be more
centrally concentrated and, therefore, earlier-type. Similar results were also
observed in previous studies (e.g. van der Wel et al., 2014; Mowla et al.,
2019; Lima-Dias et al., 2021). However, we caution that our sample is
relatively small, and the correlation between $M_{*}$ and $n$ is sensitive to
the presence of a few galaxies with the largest masses. It seems clear that
galaxies with Sérsic index below 1.2 are primarily below $\rm
10^{10}M_{\odot}$ in stellar mass, while those with higher Sérsic indices span
the full mass range, consistent with observations of a wide mass range among
local early-type galaxies (e.g., dwarf spheroidal and giant elliptical
galaxies)

To summarize, we have compared the various morphological and stellar
properties of our galaxies (which were selected for strong H i absorption)
with the properties of the global galaxy population. We find that the
absorption-selected galaxies exhibit similar properties as shown by the
general population.

Table 5: Results of correlation tests between various properties of our sample
galaxies and literature galaxies. Column 1 lists the parameter pairs for which
the correlation is computed. Columns 2, 3, and 4 list the number of paired
parameters, the Spearman rank order correlation coefficient ($r_{s}$), and the
probability (p) that the observed value of $r_{s}$ could arise by chance for
both sample and literature galaxies. Columns 5, 6, and 7 list similar values
for our sample galaxies only. The last column lists the figure and the panel
number showing the corresponding data, where the first index denotes the
figure number, and the second and third indices denote the column number (from
left to right) and row number (top to bottom) of the panel in the figure.

Parameters | $N_{\rm total}$ | $r_{\rm s,total}$ | $p_{\rm total}$ | $N_{\rm sample}$ | $r_{\rm s,sample}$ | $p_{\rm sample}$ | Figure panel
---|---|---|---|---|---|---|---
$\rm M_{\rm F814W}$, $<\mu_{\rm eff}>$ | 79 | 0.761 | 4.19 $\times$ $10^{-16}$ | 66 | 0.734 | 2.17 $\times$ $10^{-12}$ | 5, 1, 1
log $M_{\rm*}$, log SFR | 88 | 0.411 | 1.24 $\times$ $10^{-4}$ | 60 | 0.404 | 2.19 $\times$ $10^{-3}$ | 6, 1, 1
log $M_{\rm*}$, $R_{\rm e}$ | 97 | 0.492 | 9.77 $\times$ $10^{-7}$ | 60 | 0.578 | 1.33 $\times$ $10^{-6}$ | 7, 1, 1
log $M_{\rm*}$, $n$ | 75 | 0.430 | 2.51 $\times$ $10^{-4}$ | 60 | 0.474 | 1.31 $\times$ $10^{-4}$ | 7, 2, 1
$R_{e}$, _b_ | 97 | 0.259 | 1.05 $\times$ $10^{-2}$ | 66 | 0.096 | 4.44 $\times$ $10^{-1}$ | 8, 1, 1
log $M_{*}$, $W_{r}$ (Mg II 2796 Å) | 51 | -0.272 | 4.86 $\times$ $10^{-2}$ | 60 | -0.397 | 1.68 $\times$ $10^{-3}$ | 9, 1, 1
log $M_{\rm*}$, $\rm[X/H]_{emi}$ | 70 | 0.434 | 5.68 $\times$ $10^{-3}$ | 35 | 0.330 | 8.10 $\times$ $10^{-2}$ | 10, 2, 1
log $\rm sSFR$, $\rm[X/H]_{emi}$ | 70 | -0.401 | 2.07 $\times$ $10^{-2}$ | 35 | -0.246 | 2.37 $\times$ $10^{-1}$ | 10, 2, 3
log $\rm SFR$, $\rm[X/H]_{emi}$ | 70 | -0.012 | 9.42 $\times$ $10^{-1}$ | 35 | 0.170 | 3.88 $\times$ $10^{-1}$ | 10, 2, 2
log $N_{\rm HI}$, _$b/R_{e}$_ | 45 | -0.556 | 2.00 $\times$ $10^{-4}$ | 31 | -0.393 | 3.14 $\times$ $10^{-2}$ | 12, 1, 1
log $N_{\rm HI}$, _$R_{e}$_ | 45 | -0.517 | 6.00 $\times$ $10^{-4}$ | 31 | -0.326 | 7.45 $\times$ $10^{-2}$ | 12, 2, 1
log $N_{\rm HI}$, log $\Sigma_{\rm sSFR}$ | 41 | 0.418 | 8.30 $\times$ $10^{-3}$ | 22 | 0.121 | 5.23 $\times$ $10^{-1}$ | 13, 1, 2
log $N_{\rm HI}$, log $\Sigma_{\rm SFR}$ | 42 | 0.287 | 6.65 $\times$ $10^{-2}$ | 23 | -0.215 | 3.14 $\times$ $10^{-1}$ | 13, 1, 1
$b/R_{e}$, $\rm[X/H]_{abs}$ | 20 | 0.433 | 5.12 $\times$ $10^{-2}$ | 5 |  |  | 11, 2, 1
_b_ , $\rm[X/H]_{abs}$ | 28 | 0.423 | 2.80 $\times$ $10^{-2}$ | 5 |  |  | 11, 1, 1
log $M_{\rm*}$, $\rm[X/H]_{abs}$ | 25 | 0.436 | 2.58 $\times$ $10^{-2}$ | 5 |  |  | 10, 1, 1
log SFR, $\rm[X/H]_{abs}$ | 18 | -0.447 | 6.52 $\times$ $10^{-2}$ | 4 |  |  | 10, 1, 2
log sSFR, $\rm[X/H]_{abs}$ | 17 | -0.597 | 1.11 $\times$ $10^{-2}$ | 4 |  |  | 10, 1, 3
log sSFR, log $M_{\rm*}$ | 80 | -0.465 | 1.38 $\times$ $10^{-5}$ | 55 | -0.580 | 3.53 $\times$ $10^{-6}$ |

Notes. $\rm[X/H]_{abs}$ is the absorption metallicity and $\rm[X/H]_{emi}$ is
the emission metallicity. Some rows do not report $r_{\rm s,sample}$ and
$p_{\rm sample}$ values since the number of paired parameters is small, which
is insufficient to perform correlation tests.

###  4.4 How do stellar and absorption properties relate?

We now examine the stellar properties of the galaxies within the velocity
range of $\pm$ 500 km $\rm s^{-1}$ of the absorption redshift with the
absorption properties. We only include the absorbers with reliable
metallicities for comparisons of absorption metallicities and stellar
properties of the galaxies. To perform these comparisons, we selected galaxies
with the smallest impact parameters from the quasar sightlines and the most
massive galaxies in each quasar field detected within $\pm$ 500 km $\rm
s^{-1}$ of the absorption redshift. We note that it is not possible to
consider all the galaxies in such cases or even use the average values of the
stellar properties of all the galaxies since doing so would either
underestimate or overestimate the true values, given that the impact
parameters of the individual galaxies are different.

####  4.4.1 Impact parameter and galaxy’s effective radius

Figure 10: Absorption and emission metallicities plotted against stellar
properties of gas-rich galaxies. Left panel: Absorption metallicities plotted
against the stellar mass, star formation rate, and specific star formation
rate (from top to bottom). All symbols are as in Figure 5. The absorption
metallicities are based on Zn for most cases, while for one absorber, we adopt
dust-free absorption metallicity. Right Panel: Emission metallicities plotted
against the stellar mass, star formation rate, and specific star formation
rate (from top to bottom). The solid and dashed black lines show,
respectively, the mass-metallicity relation for 0.5 < $z$ < 1.0 from Ly et al.
(2016) and the $\pm$1-$\rm\sigma$ uncertainties in this relation. The subpanel
at the bottom of the upper right panel shows the difference in the observed
emission metallicities and the expected emission metallicities from the MZR
(Ly et al., 2016) plotted vs. the stellar mass.

Figure 8 shows the impact parameter versus the effective radius for our
galaxies and other absorption-selected galaxies from the literature. For
reference, the red and blue dashed lines correspond to $\rm b=R_{vir}$, and
$\rm b=R_{vir}/2$, respectively, assuming the approximate relation between the
effective radius and the Virial radius (Kravtsov, 2013). Most of the sample
galaxies ($\sim$85 $\%$) lie below $\rm b=R_{vir}$, and more than half of the
sample galaxies ($\sim$59 $\%$) lie below $\rm b=R_{vir}/2$. All of the
galaxies at the smallest impact parameters (i.e., the most probable host
galaxies) are located below $\rm b=R_{vir}$ while almost all massive galaxies
($\sim$96 $\%$) are present below the red dash line, as shown in the Figure 8.
Given the approximate relation between the effective radius and the Virial
radius (Kravtsov, 2013), $\rm b/R_{e}\sim$70 corresponds to $\rm b\sim
R_{vir}$. It is thus interesting to note that most of the galaxies have impact
parameters below $\rm R_{vir}$ and that the galaxies with impact parameters
larger than $\rm\sim 0.3$ $\rm R_{\rm Vir}$ are almost all below the sub-DLA
limit in H i column density (Noterdaeme et al., 2014). While most DLAs and
sub-DLAs are associated with galaxies at impact parameters less than 0.2 $\rm
R_{vir}$, a small fraction ($\sim$26 $\%$) of sample galaxies have impact
parameters in the range of 0.5 $\rm R_{vir}$ to $\rm R_{vir}$. All of the
galaxies from the literature lie below $\rm b=R_{vir}/2$. This suggests that
while these gas-rich absorbers usually trace regions close to galaxy centers,
they occasionally trace the CGM at large distances extending out to the Virial
radius.

####  4.4.2 Dependence of Mg II $\lambda$ 2796 rest-frame equivalent width on
stellar mass

Studies of the interdependence of the Mg II $\lambda$ 2796 absorption strength
and the galaxy’s stellar properties have reached different conclusions.
Bordoloi et al. (2011) reported that the Mg II equivalent widths [estimated
from low-resolution spectra of zCOSMOS galaxies, obtained with the Visible
Multi-Object Spectrograph (VIMOS) on the Very Large Telescope (VLT), by
fitting a single Gaussian profile across the Mg II $\lambda$ 2796 and
$\lambda$ 2803 lines] increase with stellar mass for blue galaxies at lower
impact parameter (b $<$ 50 kpc). However, such dependence is absent in the red
galaxies and even in blue galaxies with larger impact parameters (b $>$ 65
kpc). Nielsen et al. (2013) suggested that more massive galaxies have larger
Mg II equivalent width in the MAGiiCAT sample, based on a positive correlation
between the K-band luminosity (assumed to be a proxy of $M_{*}$) and the Mg II
equivalent width.

For impact parameters smaller than 50 kpc, Lan et al. (2014) showed that the
Mg II $\lambda$ 2796 equivalent width shows a positive correlation with _M*_
for star-forming galaxies but not for passive galaxies. Taking the larger
dispersion values in median Mg II $\lambda$ 2796 equivalent widths, Rubin et
al. (2018) found that the median Mg II equivalent widths increase with the
stellar mass for blue galaxies at a transverse distance 30 kpc $<$ $\rm
R_{\perp}$ $<$ 50 kpc, however the median Mg II $\lambda$ 2796 equivalent
widths values for red galaxies are found to be smaller compared to those for
high-mass blue galaxies. Including both detections and upper limits in Mg II
$\lambda$ 2796 equivalent widths measurements, Dutta et al. (2020) reported a
weak positive correlation between Mg II $\lambda$ 2796 equivalent widths and
_M*_ in the MAGG sample.

For our MAH sample and literature galaxies, we find a weak negative
correlation ($r_{s}$ $=$ -0.27, $p$ = 4.86 $\times$ $10^{-2}$) between the Mg
II $\lambda$ 2796 equivalent widths and stellar mass. Part of the reason for
the difference between this trend and the weak or positive relations found for
Mg II absorbers seems to be the difference in the selection techniques. Our
sample absorbers are selected by high $N_{\rm HI}$, and therefore have higher
Mg II $\lambda$ 2796 equivalent widths. For example, $\sim 70\%$ of the
absorbers in our sample have Mg II $\lambda$ 2796 rest equivalent widths $>$
0.5 Å, while only $<15\%$ of the absorbers in the sample of Dutta et al.
(2021) fall in this category. Moreover, $\sim 60\%$ of the galaxies in our
sample are at impact parameters less than 100 kpc, while only $<10\%$ of the
galaxies in the sample of Dutta et al. (2021) fall in this category. We also
note that our $M_{*}$ values have substantial uncertainties, making a robust
detection of the trend difficult. Figure 9 shows plots of Mg II $\lambda$ 2796
absorption strengths versus the stellar mass. The H i column density is known
to be positively correlated with the Mg II and Fe II absorption strengths
(e.g. Rao et al., 2006). Furthermore, the H i column density is negatively
correlated with the stellar mass and with metallicity, suggesting that the
lower $N_{\rm HI}$ absorbers are associated with more massive galaxies that
have had high past star formation and gas consumption (Kulkarni et al., 2010;
Augustin et al., 2018). The negative correlation seen in the Figure 9 is thus
expected.

Figure 11: Absorption metallicities plotted versus the impact parameter (left)
and the normalized impact parameter (right). All symbols are as in Figure 5.
The light blue region below the solid blue line in the left panel figure
denotes the simulated distribution of impact parameters plotted against the
absorption metallicities for using the model described in Fynbo et al. (2008)
for the DLA galaxies at $z$ $=$ 3 and is taken from Krogager et al. (2012).
Extrapolating the model’s prediction, the region is further extended up to the
impact parameters of 100 kpc to include the sample galaxies detected at the
larger impact parameters and is denoted by a light blue region below the
dashed blue line. The trends suggest that metal-poor strong H i absorbers are
found in smaller haloes and, therefore, at smaller impact parameters (Krogager
et al., 2012).

####  4.4.3 Dependence of metallicity on stellar properties

The left panels of Figure 10 show plots of absorption metallicities vs.
stellar properties ($\emph{M}_{*}$, SFR and sSFR) of the galaxies. For most
cases, we use absorption metallicities based on Zn, which is less depleted on
dust grains. For one absorber, we use the dust-free absorption metallicity
inferred from multiple elements using the method of Jenkins (2009) based on
depletion trends observed in the local interstellar medium of the Milky Way.
The right panels of Figure 10 show similar plots, but for the emission
metallicities [from Weng et al. (2023) for our sample and from Christensen et
al. (2014), Augustin et al. (2018), Rhodin et al. (2018) for the literature
sample]. Also shown, for reference, in the left and right upper panels of
Figure 10 are the mass-metallicity relation (MZR) for star-forming galaxies at
0.5 < $z$ < 1.0 and the 1-$\rm\sigma$ uncertainties in this relation (Ly et
al., 2016). The bottom sub-panel in the upper right panel shows the difference
in the observed emission metallicities and the expected emission metallicities
based on the MZR from Ly et al. (2016) at the observed stellar mass. It is
clear that both the absorption-based metallicity (away from the galaxy center,
at the impact parameter of the corresponding quasar sight line) and the
emission-based metallicity (typically at the galaxy center) are positively
correlated with the stellar mass, and are generally consistent with the MZR
for star-forming galaxies.

Figure 12: The normalized impact parameter (b/$\rm R_{e}$) and the effective
radius plotted against the column density of H i gas. Left Panel: Plot of
b/$\rm R_{e}$ against the log of $N_{\rm HI}$. The plot infers that the H i
column density is higher for the galaxies found at low-impact parameters to
the quasar’s sightline. At the same time, there is low H i column density in
the regions located at larger distances. Right Panel: Plot of $\rm R_{e}$
against the log of $N_{\rm HI}$. The gas-rich galaxies are smaller in size
than the gas-poor galaxies. All symbols are as in Figure 5. The stars are the
literature values taken from Fynbo et al. (2011), Krogager et al. (2012),
Christensen et al. (2014), Augustin et al. (2018) and Rhodin et al. (2021).
The gray stars are the literature galaxies from Zabl et al. (2019) whose H i
column density is estimated from the Mg ii $\lambda$2796 equivalent widths
using the relation from Ménard & Chelouche (2009).

The middle panels of Figure 10 show plots of the absorption and emission
metallicity vs. the SFR. No correlation is observed between metallicity (both
absorption and emission metallicity) and SFR. The bottom panels of Figure 10
show plots of the absorption and emission metallicity vs. the specific star
formation rate (sSFR). Both absorption and emission metallicity are negatively
correlated with the sSFR. This suggests that the low-metallicity absorbers are
associated with galaxies that are forming stars (and consuming gas) more
vigorously. However, they are less enriched due to low past star formation
activity. While the plot suggests that the negative correlation is mostly
driven by the presence of literature galaxies, it is essential to expand the
sample to verify this correlation.

Figure 13: The surface densities of SFR (left panels) and sSFR (right panels)
measured within the effective radius plotted versus the H i column density.
The gas-rich absorbers tend to have higher surface densities of SFR and sSFR.
In the top panels, the galaxies are subdivided into two bins using the median
value of the stellar mass. Galaxies with log _M*_ < log _M* med_ are colored
with blue squares and the galaxies with log _M*_ $\geq$ log _M* med_ are
represented with green squares. The bottom panels show similar plots where the
galaxies are subdivided into two bins in terms of galaxies’ redshift. Blue-
colored galaxies have $\rm z_{gal}$ < 1 while green-colored galaxies have $\rm
z_{gal}$ $\geq$ 1\. Diamonds denote galaxies nearest to the quasar sight lines
from our _HST_ measurements, while open circles stars denote the most massive
galaxies of each quasar at the redshift of the absorber. One of the sample
galaxies does not have _M*_ measurement and is denoted by an unfilled diamond.
The stars are the literature values taken from Fynbo et al. (2011), Krogager
et al. (2012), Christensen et al. (2014), Rafelski et al. (2016), Augustin et
al. (2018), Ma et al. (2018) and Rhodin et al. (2021). In the left panel, the
solid black line is the Kennicutt-Schmidt relationship for nearby galaxies
taken from Kennicutt (1998), while in both panels, the solid red line is the
median value of the surface densities obtained from the TNG100 simulation. The
solid red vertical lines denote 1-$\sigma$ uncertainties in the median value.
The cyan dots are the simulated galaxies at $z$ = 0.5. No correlation is
observed between SFR surface density and H i column density but a positive
correlation exists between sSFR surface density and H i column density.
Absorption-selected galaxies have a higher star formation efficiency than
predicted by the K-S law for local galaxies. See the text for more details.

####  4.4.4 Dependence of metallicity on impact parameter and galaxy’s size

Figure 11 shows plots of the metallicities of the absorption-selected galaxies
vs. the impact parameter and the normalized impact parameter for galaxies from
our sample and the literature. To place these in context, we use a model for
the metallicity-size relation for DLAs suggested by Fynbo et al. (2008). In
this simple model, galaxies are assigned a size, metallicity, and metallicity
gradient based on their luminosities. The metallicity distributions of the
quasar DLAs and GRB DLAs are predicted using the luminosity function of UV-
selected galaxies (Lyman Break Galaxies), a metallicity vs. luminosity
relation, and the radial distribution of H i gas along with luminosity. Using
such a model prediction, Krogager et al. (2012) generated 4000 simulated data
points to compare to the measured data points. The light blue region under the
solid blue line in the right panel of Figure 11 shows these 4000 simulated
data points. For further details, see (e.g. Krogager et al., 2012). We
extended the region to impact parameters of 100 kpc to include our sample
galaxies. To do so, we extrapolated the metallicity-impact parameter
relationship predicted by those simulation points. The light blue region under
the dashed blue line in the Figure 11 shows the extrapolated region.

Both panels of Figure 11 suggest that the metallicity is higher for galaxies
sampled at higher impact parameters. This result is in agreement with previous
studies (e.g. Krogager et al., 2012; Krogager et al., 2017), and would be
consistent with the model expectation (Fynbo et al., 2008). This suggests that
the metal-poor systems are found in smaller haloes and, therefore, detectable
only in galaxies at lower impact parameters (Krogager et al., 2012).

####  4.4.5 Dependence of H i column density on impact parameter and galaxy
size

Figure 12 shows the impact parameter normalized by the effective radius and
the effective radius plotted versus the H i column density. A negative
correlation ($r_{s}$ $=$ -0.56 and _p_ $=$ 2.00 $\times$ $10^{-4}$) is
observed between the normalized impact parameter and the H i column density.
The effective radius of the absorbing galaxies also shows a strong negative
correlation ($r_{s}$ $=$ -0.52 and _p_ $=$ 6.00 $\times$ $10^{-4}$) with H i
column density. This shows that galaxies associated with higher H i absorbers
are smaller in size, and therefore likely to show strong absorption at small
impact parameters. Indeed, all galaxies in the current sample associated with
DLAs have effective radii smaller than 3 kpc, while all galaxies with $\rm
R_{e}>$3 kpc are associated with lower H i column density absorbers. This
finding is consistent with past suggestions that DLAs are associated with
dwarf galaxies (e.g. York et al., 1986; Kulkarni et al., 2010).

####  4.4.6 Relation between H i column density and surface density of star
formation

Figure 13 shows plots of the surface densities of the SFR and sSFR averaged
within the effective radius versus the column density of H i. In the upper two
panels, the galaxies are binned into two groups by stellar mass (above and
below the median stellar mass log _M* med_ = 9.67). In the lower two panels,
the galaxies are binned into two groups by redshift ($z<1$ and $z\geq 1$). For
comparison with local galaxies, we also show the relationship observed between
the surface densities of SFR and H i (Kennicutt, 1998) for low-redshift
spirals (what we refer to as the “atomic Kennicutt-Schmidt (K-S) relation”).
This relation is based on the best fit (log $\Sigma_{\rm SFR}$ = 1.02 log
$\Sigma_{\rm HI}$ \- 2.89) between the tabulated values of $\rm\Sigma_{SFR}$
and $\Sigma_{\rm HI}$ listed in Kennicutt (1998). We use this relation (which
translates to log $\Sigma_{\rm SFR}$ = 1.02 log $N_{\rm HI}$ \- 23.36) rather
than the standard KS relation between $\rm\Sigma_{\rm SFR}$ and $\Sigma_{\rm
gas}$ since the latter also includes molecular gas, and molecular gas
measurements are not available for most of the absorber-selected galaxies
plotted in Figure 13 (besides the few objects observed so far in CO emission
with ALMA).

The upper right panel of Figure 13 shows that $\Sigma_{\rm sSFR}$ is
positively correlated with the H i column density. The Spearman rank order
correlation test gives $r_{s}$ $=$ 0.42 and _p_ $=$ 8.30 $\times$ $10^{-3}$
between $N_{\rm HI}$ and $\rm\Sigma_{\rm sSFR}$ (although we note that this
relation is not significant if only our sample galaxies are considered.) The
correlation between $\rm\Sigma_{SFR}$ and $N_{\rm HI}$ (shown in the upper
left panel of Figure 13) is not as significant even after including the
literature galaxies, with $r_{s}$ $=$ 0.29 and _p_ $=$ 6.65 $\times$
$10^{-2}$. This finding seems to be at odds with the previous suggestions
based on simulations (e.g. Nagamine et al., 2004) that DLAs follow the KS law.

Indeed, most of the galaxies associated with the absorbers from our sample and
the literature lie substantially above the “atomic K-S relation”. If taken at
face value, this suggests that the absorption-selected galaxies (which have
$z_{\rm med}\sim 0.8$) have more efficient star formation compared to the
nearby galaxies. However, this apparent discrepancy may also be caused in part
by the fact that the local “atomic K-S relation” is based on observations of
21-cm emission (which is usually far less sensitive to low H i column
densities than the Ly$\alpha$ absorption line technique used for the quasar
absorber sample).

We also note that the galaxies with stellar mass greater than the median mass
are located farther away from the “atomic K-S” relation in the upper left
panel of Figure 13, as compared to lower-mass galaxies. This suggests that the
more-massive absorption-selected galaxies have more efficient star formation,
allowing them to reach comparable SFRs in lower H i column density regions.

The high values of $\Sigma_{\rm SFR}$ compared to the K-S relation for the
galaxies in our sample and the literature seen in Figure 13 may appear
surprising, given the findings of earlier studies based on indirect estimates
of SFR surface density that the star formation efficiency in DLAs at $z\geq 1$
is 1-3% of that predicted by the K-S relation (e.g. Wolfe & Chen, 2006;
Rafelski et al., 2011, 2016). The latter measurements are also shown in the
left panels of Figure 13 for comparison. A substantial fraction of our
galaxies have 18 $<$ log $N_{\rm HI}<20$. But even focusing on just the
absorbers with log $N_{\rm HI}\geq 20.3$ (i.e. the DLAs) in our sample, the
star formation efficiency of the absorber-associated galaxies (with a median
redshift of $\sim 1.01$) still appears to be comparable to or (for some
galaxies) substantially higher than predicted by the KS relation.

The large difference between our values of $\Sigma_{\rm SFR}$ and those in the
past DLA studies may result from the fact that, unlike our the study, the past
studies were based not on direct SFR measurements for galaxies associated with
DLAs, but on measurements in the outskirts of isolated star-forming galaxies
and on the assumption that the latter are related to DLAs. It is also
noteworthy in this context that the surface brightness of the galaxies
associated with DLAs detected in our sample and those from the literature are
in fact several magnitudes brighter than the upper limit of 29 mag arcsec-2
estimated in prior studies of star formation efficiency in DLAs at $z\sim 3$
(Wolfe & Chen, 2006; Rafelski et al., 2011). We note, however, that we cannot
make a precise statement about the agreement between those DLAs and the
simulation data due to the limited number of simulated galaxies with $N_{\rm
HI}>10^{21}$ cm-2. The ability of IFS studies to reveal star-forming galaxies
associated with DLAs (and lower H i column density absorbers) demonstrated by
our MUSE-ALMA-Halos sample and other IFS studies in the literature indeed mark
a huge improvement in detecting star formation in galaxies associated with
gas-rich quasar absorbers compared to past searches. We also note, in passing,
that the previous studies of the SFR surface density in DLAs mentioned above
(e.g., Nagamine et al., 2004; Rafelski et al., 2016) adopted the original KS
relation for $\rm\Sigma_{SFR}$ vs $\rm\Sigma_{gas}$ instead of the “atomic”
version of this relation $\rm\Sigma_{SFR}$ vs $\rm\Sigma_{HI}$.

To examine whether the star formation efficiency of absorber-selected gas-rich
galaxies may have increased dramatically at $z<1$, we compare the $\Sigma_{\rm
SFR}$ vs. log $N_{\rm HI}$ trends for galaxies with $z<1$ and galaxies at
$z\geq 1$ in the lower panels of Figure 13. The lower redshift galaxies appear
to have comparable SFR surface densities for lower H i column densities. This
suggests a higher star formation efficiency of absorber-selected galaxies at
$z<1$ compared to those at $z\geq 1$. Also shown for comparison in Figure 13
are simulated galaxies at $z$ = 0.5, based on an analysis of the data obtained
from the Illustris TNG simulations (Nelson et al., 2018; Pillepich et al.,
2018; Springel et al., 2018; Naiman et al., 2018; Marinacci et al., 2018).
These state-of-the-art cosmological simulations incorporate essential physical
processes pertinent to the formation and evolution of galaxies, such as
gravity, hydrodynamics, gas cooling, star formation, stellar feedback, black
hole feedback, and more. In this study, we employ the highest-resolution
version of the TNG100 simulation, executed within a $\sim 100\,\rm Mpc$ box.
Haloes are initially identified by employing the Friends of Friends (FOF)
algorithm (Davis et al., 1985). Galaxies, regarded as substructures, are
recognized as gravitationally-bound assemblies of particles within these FOF
haloes performing the SUBFIND algorithm (Springel et al., 2001). Each FOF halo
encompasses a central galaxy, generally the most massive galaxy within that
halo, and all additional galaxies within the halo are labeled as satellites.

Properties of galaxies, including stellar masses and star formation rates
(SFRs), are taken from the principal TNG galaxy catalogs. These are measured
within the stellar half-mass radius by utilizing the particle data of the
simulation. Furthermore, the neutral hydrogen (H i) content of TNG galaxies
has been extracted from catalogs provided by Diemer et al. (2018), based on
the analytic model of Sternberg et al. (2014), where they use an optimized
post-processing framework for estimating the abundance of atomic and molecular
hydrogen. This method uses the surface density of neutral hydrogen and the
ultraviolet (UV) flux within the Lyman-Werner band, with all computations
being performed through face-on projections within a two-dimensional model.
The UV radiation emitted from young stars is modeled by assuming a constant
escape fraction and optically thin propagation across the galaxy. The
simulation demonstrates a relatively satisfactory agreement with the
measurements of the SFR surface density based on emission-line observations
for galaxies from both our sample and the literature shown in Figure 13 (and,
like these data, also lie substantially above the upper limits for the DLAs
from past studies).

The agreement between the simulated and observed data appears to be better for
the sSFR surface density than for the SFR surface density, as seen in the
right panels of Figure 13. This difference may result from the differences in
the stellar mass distributions for the simulated and observed galaxies. The
stellar mass distribution of the observed galaxies (from our sample and the
literature) peaks around log $M_{*}=9.67$ and shows fewer low-$M_{*}$ galaxies
compared to the distribution for the simulated galaxies. The higher $M_{*}$
galaxies have lower $\Sigma_{\rm sSFR}$ (as expected from the negative
correlation between sSFR and $M_{*}$, see LABEL:table5), giving better
consistency between the $\Sigma_{\rm sSFR}$ vs. $M{*}$ trends for the
simulated and observed galaxies, compared to the median $\Sigma_{\rm SFR}$ vs.
$M{*}$ trends.

To summarize, we find interdependence between the stellar properties and the
absorption properties. In particular, the H i column density and the
absorption metallicity show correlations with _M*_ , ssfr, $\Sigma_{\rm
sSFR}$, but not with the SFR and $\Sigma_{\rm SFR}$.

##  5 Summary and Conclusions

We have analyzed the morphological and stellar properties of 66 galaxies
detected within $\pm$ 500 km s-1 of the redshifts of strong intervening quasar
absorbers at $0.2\lesssim z\lesssim 1.4$ with $N_{\rm HI}$ > $10^{18}$ $\rm
cm^{-2}$ (that also have MUSE and/or ALMA data). The structural parameters of
these absorption-selected galaxies were determined using galfit. The galaxies
were found to have Sérsic indices ranging from 0.3 to 2.3 and effective radii
ranging from 0.7 to 7.6 kpc. The $\rm k$-corrected absolute magnitudes of
these galaxies range from -15.8 to -23.7 mag. Our main findings are as
follows:

  1. 1.

The absolute (rest-frame) surface brightness shows a strong positive
correlation with the galaxy luminosity. The trend appears flatter at lower
luminosities for those galaxies that have high H i column densities. This
suggests dwarf galaxies are associated with high H i column densities.

  2. 2.

The star formation rate correlates well with the stellar mass. Most galaxies
associated with intervening quasar absorbers are consistent with the star
formation main sequence.

  3. 3.

Larger galaxies are found to be more massive compared to smaller galaxies.
Furthermore, massive galaxies are more centrally concentrated, as observed for
nearby galaxies. Overall the absorption-selected galaxies follow similar
trends as those shown by the general galaxy population.

  4. 4.

For most ($\sim$85%) of the galaxies in our sample, the impact parameters are
smaller than the virial radius. Most of the sight lines with high $N_{\rm HI}$
in our sample probe the CGM of the associated galaxies at impact parameters
less than half the virial radius, and only a small fraction have impact
parameters larger than the virial radius.

  5. 5.

The rest-frame equivalent widths of Mg II $\lambda$ 2796 show a negative
correlation with stellar mass. Such trend suggests that lower $N_{\rm HI}$
absorbers are associated with more massive galaxies that have undergone high
past star formation and gas consumption activity.

  6. 6.

The absorption metallicity and emission metallicity show a positive
correlation with the stellar mass for many of the absorption-selected galaxies
and are consistent with the mass-metallicity relation for star-forming
galaxies. While the metallicity shows no correlation with SFR, the metallicity
is negatively correlated with the specific SFR, suggesting that the low-
metallicity absorbers are associated with galaxies with vigorous current star
formation but low past star formation activity.

  7. 7.

Metallicity appears to be positively correlated with the impact parameter and
normalized impact parameter. This suggests that metal-poor galaxies are found
in smaller haloes and are, therefore, detectable in galaxies at smaller impact
parameters.

  8. 8.

The H i column density is negatively correlated with the normalized impact
parameter and the effective radius of the galaxies. This shows that galaxies
associated with higher $N_{\rm HI}$ absorbers are smaller in size and,
therefore, likely to show strong absorption at small impact parameters.

  9. 9.

The sSFR surface density is positively correlated with the H i column density,
but no correlation is seen between SFR surface density and H i column density.
Furthermore, the $\rm\Sigma_{SFR}$ for the absorber-associated galaxies is
substantially higher than predicted from the atomic K-S relation for nearby
galaxies, suggesting higher star formation efficiency in the absorber-selected
galaxies. The SFR surface density is also substantially higher than the upper
limits on $\rm\Sigma_{SFR}$ for DLAs estimated in past studies. Moreover, the
star formation efficiency for absorber-associated galaxies at $z<1$ appears to
be higher than for those at $z\geq 1$.

The overall conclusions from our results are: the stellar and morphological
properties of absorption-selected galaxies are consistent with the star
formation main sequence of galaxies and show the mass-metallicity relation.
Furthermore, the higher H i column density absorbers are associated with
smaller galaxies in smaller halos that have generally not experienced much
star formation in the past and have thus remained metal-poor. However, these
galaxies associated with the higher $N_{\rm HI}$ absorbers have more active
current star formation and exhibit higher surface densities of star formation
and gas consumption. Our study also reveals that a substantial fraction of
gas-rich quasar absorbers arises in groups of galaxies.

Our study of structural and stellar properties of 66 associated galaxies
associated with gas-rich quasar absorbers has thus allowed us to search for
correlations between a variety of morphological, stellar, and gas properties.
However, our sample is still relatively small. Increasing the number of
absorption-selected galaxies with measurements of the various properties with
future MUSE, ALMA, and _HST_ observations is essential to more robustly
establish the trends suggested by our study and to fully interpret their
implications for the evolution of galaxies and their CGM.

## Acknowledgements

We thank an anonymous referee for constructive comments that have helped to
improve this manuscript. AK and VPK acknowledge support from a grant from the
Space Telescope Science Institute for GO program 15939 (PI: Péroux). AK and
VPK also acknowledge additional partial support from US National Science
Foundation grant AST/2007538 and NASA grants NNX17AJ26G and 80NSSC20K0887 (PI:
Kulkarni). GK and SW acknowledge the financial support of the Australian
Research Council through grant CE170100013 (ASTRO3D). MA acknowledges funding
from the Deutsche Forschungsgemeinschaft (DFG) through an Emmy Noether
Research Group (grant number NE 2441/1-1). We also thank the International
Space Science Institute (ISSI) (https://www.issibern.ch/) for financial
support. This research made use of following python packages: astropy, a
community-developed core Python package for Astronomy (e.g. Astropy
Collaboration et al., 2013; Collaboration, 2018), matplotlib (Hunter, 2007),
pandas (McKinney et al., 2010), photutils (Bradley et al., 2022) and numpy
(Harris et al., 2020).

## Data Availability

Data directly related to this publication and its figures can be requested
from the authors. The raw data can be downloaded from the public archives. The
TNG simulation (Nelson et al., 2019) is publicly available at https://www.tng-
project.org/.

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##  Appendix A Images of Individual Fields

We show below the broad-band _HST_ images in the reddest filter available for
each of the remaining quasar fields, similar to the image of the field of
Q0152+0023 shown in Figure 1.

Figure 14: Similar figures to Figure 1. Shown figures are the median stacked
images of the quasar fields in the full-frame. The solid circles represent the
position of the associated galaxies in the field of view, while a dotted black
circle denotes the QSO’s position. The associated galaxies are located within
$\pm$ 500 $\rm kms^{-1}$ of the absorber’s redshift. The object identification
number (ID) of these galaxies came from the MUSE-ALMA Haloes master table
discussed in Péroux et al. (2022). While the scale corresponds to 60 kpc at
$z_{\rm abs}$ = 0.7821 for the top figure, the scale corresponds to 43 kpc and
61 kpc at $z_{\rm abs}$ = 0.3830 and 0.7802 for the bottom figure,
respectively.

Figure 15: See Figure 14 caption. The scale corresponds to 27 kpc at $z_{\rm
abs}$ = 0.6331 for the top figure, while in the bottom figures, the scale
corresponds to 36 kpc and 49 kpc at $z_{\rm abs}$ = 0.4833 and 1.1532 for the
left and right figure, respectively.

Figure 16: See Figure 14 caption. The scale corresponds to 26 kpc at $z_{\rm
abs}$ = 0.5604 for the top figure, while the scale corresponds to 25 kpc, 38
kpc and 36 kpc at $z_{\rm abs}$ = 0.1906, 0.3283, and 0.3130 for the bottom
figure, respectively.

Figure 17: See Figure 14 caption. The scale corresponds to 32 kpc, 41 kpc, and
47 kpc at $z_{\rm abs}$ = 0.3929, 0.6296 and 0.8999 for the top figures, while
the scale corresponds to 32 kpc, 44 kpc, 45 kpc and 46 kpc at $z_{\rm abs}$ =
0.3950, 0.7572, 0.7691 and 0.8311 for the bottom figure, respectively.

Figure 18: See Figure 14 caption. The scale corresponds to 38 kpc at $z_{\rm
abs}$ = 0.5380 for the top figure, 40 kpc at $z_{\rm abs}$ = 0.6057 for the
middle figure while the scale corresponds to 40 kpc and 43 kpc at $z_{\rm
abs}$ = 0.6085 and 0.6868 for the bottom figure, respectively.

Figure 19: See Figure 14 caption. The scale corresponds to 39 kpc at $z_{\rm
abs}$ = 0.5592 for the top figure, while in the bottom figures, the scale
corresponds to 45 kpc and 34 kpc at $z_{\rm abs}$ = 0.7869 and 0.4298 for the
left and right figure, respectively.