# A serendipitous discovery of HI-rich galaxy groups with MeerKAT

M. Glowacki1, L. Albrow2, T. Reynolds3, E. Elson4, E. K. Mahony5, J. R.
Allison6
1International Centre for Radio Astronomy Research (ICRAR), Curtin University,
Bentley, WA 6102, Australia
2University of Canterbury, Department of Physics and Astronomy, Private Bag
4800, Christchurch 8020, New Zealand
3International Centre for Radio Astronomy Research (ICRAR), The University of
Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia
4Department of Physics & Astronomy, University of the Western Cape, Robert
Sobukwe Rd, Bellville, 7535, South Africa
5ATNF, CSIRO Space and Astronomy, PO Box 76, Epping, NSW 1710, Australia
6First Light Fusion Ltd., Unit 9/10 Oxford Pioneer Park, Mead Road, Yarnton,
Kidlington OX5 1QU, UK
E-mail<EMAIL_ADDRESS>
(Accepted 2024 March 1. Received 2024 March 1; in original form 2023 September
30.)

###### Abstract

We report on the serendipitous discovery of 49 Hi-rich galaxies in a 2.3 hour
Open Time observation with MeerKAT. We present their properties including
their Hi masses, intensity and velocity maps, and spectra. We determine that
at least three Hi-rich galaxy groups have been detected, potentially as part
of a supergroup. Some members of these galaxy groups show clear interaction
with each other in their Hi emission. We cross-match the detections with
PanSTARRS, WISE and GALEX, and obtain stellar masses and star formation rates.
One source is found to be a potential OH megamaser, but further follow-up is
required to confidently determine this. For 6 sources with sufficient spatial
resolution in Hi we produce rotation curves with BBarolo, generate mass
models, and derive a dark matter halo mass. While the number of galaxies
detected in this relatively short pointing appears to be at the high end of
expectations compared to other MeerKAT observations and group HIMF studies,
this finding highlights the capability of MeerKAT for other serendipitous
discoveries, and the potential for many more Hi-rich galaxies to be revealed
within both existing and upcoming Open Time datasets.

###### keywords:

galaxies: groups: general – galaxies: interactions – radio lines: galaxies –
galaxies: star formation

††pubyear: 2024††pagerange: A serendipitous discovery of HI-rich galaxy groups
with MeerKAT–A

##  1 Introduction

Galaxy groups occupy up to $\sim$50% of the local Universe ($z\sim 0$; Eke et
al., 2004; Robotham et al., 2011) and are important parts of the hierarchical
structure of the Universe (Springel et al., 2018) where they trace filamentary
large-scale structure, as they lie between the low-density environments of the
field and high-density clusters. Galaxy systems form through episodic mergers,
with groups thought to act as the building blocks for the more massive
clusters. Groups number between 3–100 members within a dark matter halo of
mass between 1012–1014 M⊙ (e.g. Catinella et al., 2013). However, the
distinction between galaxy groups and clusters is inconsistently defined in
literature (see review by Lovisari et al., 2021).

Galaxy groups provide a window into the baryon cycle and the circumgalactic
medium (Tumlinson et al., 2017; Nielsen et al., 2020). External and internal
feedback mechanisms such as active galactic nuclei (AGN) feedback and tidal
interactions dominate (e.g. Ponman et al., 2003; McCarthy et al., 2010),
meaning galaxy groups are not merely ‘scaled-down’ versions of galaxy
clusters. The distinction between galaxy groups and clusters has not been
clearly made in previous literature, but galaxy clusters (often numbering 100+
galaxy members) are larger than groups ($\sim$3–50 galaxy members). The
properties of both are dependent on the density of the environment, although
galaxy clusters are generally denser. Interactions between group members and
their surrounding environment can also shape the evolution of galaxies as they
transition from star-forming spirals to massive, quenched galaxies dominating
in clusters (e.g. Baldry et al., 2004; Driver et al., 2011; Davies et al.,
2019). For example, there is evidence that galaxies have undergone ‘pre-
processing’ in group environments before they fall into galaxy clusters
(Mahajan, 2013; Bianconi et al., 2018; Kleiner et al., 2021; Loubser et al.,
2024), which can potentially quench star formation in group galaxies.

Neutral hydrogen (Hi) emission is a useful tool for studying group
environments because it can trace the tidal interactions between group
members, and extends well beyond the stellar component of the galaxy (e.g.
Broeils & Rhee, 1997; Leroy et al., 2008). Hi is the fuel for star formation,
and its distribution provides key insights into the quenching or triggering of
star formation in galaxies. Hi is a sensitive dynamical tracer and can be used
to observe environmental processes such as tidal interactions or ram-pressure
stripping, the latter seen for larger groups (Oosterloo & van Gorkom, 2005;
Serra et al., 2013; Saponara et al., 2018). By observing Hi in group galaxies,
much work has been done to understand the evolution of Hi within this
environment (Hess & Wilcots, 2013; Jones et al., 2019; Kleiner et al., 2021).
For example, Brown et al. (2017) conducted a statistic study on the Hi content
as a function of environment density for gas-poor to gas-rich regimes, and
found gas starvation alone cannot account for an observed decrease of gas
content in group and cluster environments. Stevens et al. (2023) examined the
TNG50 simulation suite and reproduced the effects of gas truncation from a
Virgo-like cluster environment on the gas content of satellite galaxies.

New radio telescopes serving as pathfinders for the upcoming Square Kilometer
Array (SKA) have already demonstrated their ability in detecting new Hi-rich
galaxy groups, as well as enhancing previous studies of galaxy groups, thanks
to improved sensitivity and survey speeds. The APERture Tile In Focus
(Apertif; van Cappellen et al., 2022) system uses a phased array feed (PAF)
upgrade of the Westerbork Synthesis Radio Telescope. The first year of survey
observations with Apertif has covered approximately one thousand square
degrees of sky (Adams et al., 2022). The Australian Square Kilometre Array
Pathfinder telescope (ASKAP; Deboer et al., 2009; Hotan et al., 2021) also
employs PAFs which enables Widefield ASKAP L-band Legacy All-sky Blind surveY
(WALLABY; Koribalski et al., 2020). WALLABY has publicly released its phase 1
dataset (Westmeier et al., 2022) and already conducted studies of individual
galaxy groups (e.g. Lee-Waddell et al., 2019; Reynolds et al., 2019). For et
al. (2021) also used WALLABY data to study the Eridanus Supergroup, where a
supergroup is defined as a group of groups that may eventually merge to form a
cluster.

The third of the SKA pathfinder telescopes is MeerKAT (Jonas & MeerKAT Team,
2016). MeerKAT has a lower survey speed than Apertif or ASKAP, but has a
greater sensitivity, and hence is able to detect lower Hi-mass galaxies than
other SKA pathfinders. The Fornax Survey with MeerKAT (Serra et al., 2023) is
a targeted survey of the Fornax cluster, with Kleiner et al. (2021) presenting
results on the Fornax A group. The MeerKAT International GigaHertz Tiered
Extragalactic Exploration survey (MIGHTEE; Jarvis et al., 2016) survey
includes a Hi emission component (MIGHTEE-HI; Maddox et al., 2021). Ranchod et
al. (2021) reported on the discovery of a galaxy group with 20 members from
the MIGHTEE-HI data. In addition, the Looking At the Distant Universe with the
MeerKAT Array (LADUMA; Blyth et al., 2016) survey is to be the deepest Hi
emission study by targeting a single field for over 3,000 hours.

These results from major science surveys are not the only avenue for detecting
and studying Hi-rich galaxies. For example, Healy et al. (2021) presented over
200 galaxies detected in a 15 hour observation of a galaxy cluster with
MeerKAT Open Time. However, untargeted studies of known clusters and galaxy
groups through MeerKAT Open Time or ASKAP Guest Science Time can provide yet
another avenue for the detection and analysis of Hi-rich galaxies, provided
such observations are in spectral-line modes. For example, Hi absorption
searches towards radio-bright quasars with these telescopes can also contain
Hi emission associated with other unrelated galaxies within the field of view.

We present a serendipitous discovery of 49 detections of Hi emission in a
single pointing with MeerKAT. In Section 2 we describe the MeerKAT
observations and ancillary datasets. In Section 3 we present the MeerKAT
detections and properties of the galaxies, and determine the detections reside
in multiple Hi-rich groups. We briefly discuss the serendipity of the
detection in Section 4, and summarise our conclusions in Section 5.
Throughout, we adopt optical velocities (c$z$) in the heliocentric reference
frame, the AB magnitude convention, and we assume a flat $\Lambda$CDM
cosmology with $H_{\rm 0}$ = 67.7 km s-1 Mpc-1 (Planck Collaboration et al.,
2016).

##  2 Observation and data analysis

###  2.1 Observation with MeerKAT

Observation 1617470178 of the target J0944-1000 (NVSS J084452-100103), at
8:44:52.67, –10:00:59.5, was carried out on 2021 April 3rd with MeerKAT as
part of proposal ID SCI-20210212-MG-01 (see Table 1). The observation was
taken in L-band (856 MHz bandwidth centred at 1284 MHz) at 32K spectral
resolution (26.123 kHz wide channels). The intention of the observation was to
confirm a tentative Hi absorption feature seen with the Australia Telescope
Compact Array (ATCA) near the optical spectroscopic redshift of $z$ = 0.04287
(Glowacki et al., 2017b). The SARAO SDP continuum image quality report gave an
root mean square (RMS) noise of 41 $\mu$Jy.

The raw data were transferred to the ilifu supercomputing cloud system and
reduced there. Bandpass, flux, and phase calibration, along with self-
calibrated continuum imaging, was performed using the processMeerKAT
pipeline111https://idia-pipelines.github.io/docs/processMeerKAT, which is
written in Python, uses a purpose-built CASA (McMullin et al., 2007)
Singularity container, and employs MPICASA (a parallelized form of CASA). Data
was at this stage rebinned by a factor of 4 (i.e. to ‘8K’ mode, 104.49 kHz-
wide channels), and the 1304–1420 MHz segment of the L-band was extracted for
the results presented in this paper. Model continuum visibility data were
subtracted from the corrected visibility data using the CASA task uvsub. A
second-order polynomial fit to the continuum was then calculated and
subtracted using the CASA task uvcontsub for all channels to remove residual
continuum emission from the spectral line data. Finally, spectral line cubes
were created using tclean with robust = 0.5 and no cleaning. The RMS per
104.49 kHz channel was consistent between 1304–1420 MHz with the per-channel
noise of 0.16 mJy beam-1 at the centre (1362 MHz). All channels were convolved
to a common synthesized beam of $14.0^{\prime\prime}\times 9.8^{\prime\prime}$
at a position angle of $-$20.1∘.

Table 1: Details of the MeerKAT observation for proposal ID SCI-20210212-MG-01. SBID | 1617470178
---|---
Phase centre | 8:44:52.67, –10:00:59.5
Bandpass calibrator | J0408-6545
Gain calibrator | J0730-1141
Channel width | 26.123 kHz (rebinned by factor of 4)
Pixel size | 2 arcsec
On-source integration time | 8340 sec (2.32 hr)
RMS |  0.16 mJy per channel ($\sim$1362 MHz)
Beam |  $14.0^{\prime\prime}\times 9.8^{\prime\prime}$; PA of $-$20.1∘

###  2.2 Source finding

While the putative HI absorption feature was not confirmed, upon initial
visual inspection of the spectral line cube with CARTA (Comrie et al., 2021a),
Hi emission was noticed in multiple instances, both spatially and spectrally
away from the centre of the cube. A more careful investigation followed, with
each channel inspected for Hi emission visually in CARTA. In addition to
manual visual source finding, we employed two other methods. The first was a
matched-filter approach which was separately developed to find galaxy
candidates in Hi data cubes. The MeerKAT cube was box-smoothed spatially with
a kernel of 20 arcsec by 20 arcsec, and spectrally with a kernel of width
equal to two channels (approximately 45 km s-1). Thereafter, the average flux
within the full 3D smoothing kernel (20 arcsec x 20 arcsec x 45 km s-1) was
calculated at every (x, y, z) location (i.e., voxel) in the smoothed cube. The
distribution of the resulting means was well modelled by a Gaussian of mean
zero and standard deviation $\sigma$. Any voxels in the smoothed cube that had
a filter-averaged flux greater than 6$\sigma$ were taken to contain potential
galaxy emission.

Figure 1: SIP outputs for IDs 23 and 34. Left to right, top to bottom, is the
Hi moment 0 map overlaid on a DECaLS DR10 image, the moment 0 map isolated,
the pixel SNR map, the moment 1 (velocity) map, the SoFiA masked and unmasked
spectrum, and the p-v slice diagram. SIP outputs for the remaining galaxies
are given in the Appendix available online. Contour levels are noted on the
individual subplots.

In general, we found the matched-filter source-finding approach to reliably
extract all emission of real galaxies, often including extended features such
as Hi tails. Additionally, the Source Finding Application 2 (SoFiA 2; Serra et
al., 2015; Westmeier et al., 2021) was employed to verify detections and
create individual subcubes.

The results of the three methods were then combined and individually verified
by eye. As part of verification, we considered data outputs from the SoFiA
Image Pipeline (SIP; Hess et al., 2022), where optical imaging from either the
Dark Energy Camera Legacy Survey (DECaLS; Dey et al., 2019) DR10 release, or
the PanSTARRS (Chambers et al., 2016) survey was used for overlaying Hi
contours, using default settings (where the lowest contour is at minimum
2$\sigma$ significance). Two examples of SIP outputs are given in Figure 1.
Tentative detections were removed e.g. single-channel detections or ones
difficult to distinguish from noise, and additionally without an optical
counterpart. SoFiA identified a couple additional Hi sources not originally
identified by the other methods, although it had initially failed to also
detect a couple other sources identified through visual source finding and
matched filter approaches when run on the entire cube.

Hi masses are calculated from SoFiA data products using equation 48 from Meyer
et al. (2017).

###  2.3 Ancillary datasets

To complement our Hi datasets, we looked at available ancillary data for
stellar mass and star formation rate (SFR) estimates. We used a mixture of
optical, mid-infrared, and near ultraviolet (NUV) datasets. In each case we
follow the methodology described by Reynolds et al. (2022), where we adapted
scripts provided on https://github.com/tflowers15/wallaby-analysis-scripts. We
summarise the steps involved below.

####  2.3.1 Optical

For each Hi detection we derive stellar masses from the PanSTARRS $g-$ and
$r-$band images. In summary, we obtain image cutouts at the position of each
Hi detection through the PanSTARRS cutout server
222https://ps1images.stsci.edu/cgi-bin/ps1cutouts. Photometry was derived
through the Python package Photutils on the $r$-band image, segmentation maps
via Segmentation for masking other sources, and isophotes fitted via Isophote.
The empirical relation from Taylor et al. (2011) was then used for stellar
mass calculation:

$\begin{split}{\rm log(}M_{*}{\rm/M_{\odot)}}&=-0.840+1.654(g-r)+0.5(D_{\rm
mod}+M_{\rm sol}-m)\\\ &-{\rm log(1+}z)-2{\rm log(}h/0.7),\end{split}$ (1)

where 0.840 and 1.654 are empirically determined constants (Zibetti et al.,
2009), the $g-r$ colour is in the SDSS photometric system, $m$ is the $r$-band
apparent magnitude in the SDSS photometric system, $D_{\rm mod}$ is the
distance modulus (used to convert from apparent to absolute magnitude), $h$ is
the Hubble Constant, and $M_{\rm sol}$ = 4.64 is the absolute magnitude of the
Sun in the $r$-band (Willmer, 2018). Calculated stellar masses have
uncertainties of $\sim$0.16 dex as by Reynolds et al. (2022).

####  2.3.2 NUV and mid-infrared

We estimate the star formation rate from two surveys. The first is the Galaxy
Evolution Explorer (GALEX Martin et al., 2005), where the NUV luminosity
traces emission from young stars (Kennicutt, 1998; Kennicutt & Evans, 2012).
Next is the Wide-field Infrared Survey Explorer (WISE; Wright et al., 2010),
where the fractions of polycyclic aromatic hydrocarbons (PAH) traced by the W3
(12 $\mu$m) band are high in regions of active star formation, thought to be
produced in molecular clouds and growing on dust grains. Alternatively the
warm dust continuum at the W4 (22 $\mu$m) band, sensitive to reprocessed
radiation from star formation, is another avenue for SFR measurements.

As with PanSTARRS, the GALEX and WISE images are masked as described by
Reynolds et al. (2022). Image units for photometry are converted to
magnitudes, with both NUV and WISE magnitudes with SNR $<$ 5 considered to be
upper limits. After converting to luminosity $L_{\rm NUV}$, the SFR from the
GALEX measurements is defined from Schiminovich et al. (2007) as

${\rm SFR_{NUV}/M_{\odot}yr^{-1}=10^{-28.165}}L_{\rm NUV}/{\rm
ergs^{-1}Hz^{-1}},$ (2)

For the mid-infrared SFR, we consider W4, or W3 if the less sensitive W4 band
is not available. After converting to the corresponding luminosity ($L_{\rm
W4}$ or $L_{\rm W3}$), the SFR is calculated as by Jarrett et al. (2013) via:

${\rm SFR_{W3}/M_{\odot}yr^{-1}=4.91\times 10^{-10}}(L_{\rm W3}-0.201L_{\rm
W1}/{\rm L_{\odot}}),$ (3)

and

${\rm SFR_{W4}/M_{\odot}yr^{-1}=7.50\times 10^{-10}}(L_{\rm W4}-0.044L_{\rm
W1}/{\rm L_{\odot}}),$ (4)

where a subtraction happens due to contamination from old stellar populations
done via subtracting a fraction of the W1 (3.4 $\mu$m) luminosity $L_{\rm
W1}$.

The total SFR is then the sum of SFRNUV and SFRW4(3), as done by Reynolds et
al. (2022). The derived SFRs have uncertainties of $\leq$0.1 dex.

Figure 2: The 49 Hi-rich galaxies detected by MeerKAT in a single 2.3 hr
pointing. Their intensity (moment 0) maps are overlaid as contours coloured by
Hi redshift on a PanSTARRS $r$-band image. Numbers correspond to the galaxy’s
ID number, as defined in Table LABEL:tab:properties. Contour levels are of
column density multiples of (2, 4, 8, 16, 32) $\times$ 1020 cm-2.

##  3 Results

In total, we obtain 49 detections of 21-cm emission within the MeerKAT data.
Henceforth we refer to individual galaxies by their assigned ID number. We
present the combined outputs for SIP for two galaxies, IDs 23 and 34, in Fig.
1. In the Appendix (available online) we give the remaining SIP images (Figure
A1), where the optical image is either a three-colour image from DECaLS DR10
or PanSTARRS, and notes on individual sources. A combined intensity (moment 0)
map for the whole field of view overlaid on a PanSTARRS $r$-band image is
presented in Fig. 2, where contours are coloured by redshift assuming a Hi
emission line (rather than e.g. hydroxyl; see Section 3.1.1).

In Table LABEL:tab:properties we present the Hi redshift and masses, stellar
masses, SFRs from the WISE mid-infrared and GALEX photometries where
available, and Hi gas fractions and specific SFR (sSFR) for each host detected
in MeerKAT. Three galaxies (ID3, ID20, ID25) had optical spectroscopic
redshifts available. The Hi redshift, as determined using SoFiA, agrees within
3$\sigma$ with the optical redshift and associated uncertainty (given as
0.00015). For a further 7 galaxies photometric redshifts estimates were
available using WISE magnitudes from the literature. All 7 photometric
redshifts from the literature here agree with Hi emission rather than other
radio spectral transitions (e.g. the hydroxyl 1665-1667 doublet), with
slightly higher (by $<$0.025) photometric redshifts seen for ID8, ID19, ID23
and ID24, and a lower photometric redshift for ID30. However, for the majority
of sources, no redshift information is available in the literature. In Table
LABEL:tab:radiocont we give the measured total radio continuum flux density
for our sources from the MeerKAT observation, generated with the
processMeerKAT pipeline at 1362 MHz with a 9.1 x 6.8" radio beam. We detect
radio continuum for 15 of our emission-line detections (13 unresolved). The
remaining emission sources are not detected at a sensitivity of 0.02 mJy.

No Hi data for these detections had been found in the literature, with sources
typically at too high redshift to be within the HIPASS survey footprint
(Barnes et al., 2001), or otherwise had too low a Hi mass to be detected
(HIPASS’ 3$\sigma$ $M_{\rm HI}$ sensitivity is stated to be 106 $d_{\rm
Mpc}^{2}$ M⊙; table 1 of Barnes et al. (2001)). Therefore, all Hi detections
presented here are new.

Table 2: Properties of the 49 Hi galaxies detected in the 2.3 hr pointing
centered on J0844–1000. We give the ID of the galaxy, the right ascension and
declination based on the Hi emission as measured by SoFiA, the redshift
(assuming a Hi emission line), the optical spectroscopic or photometric
redshift where available in the literature, Hi mass, stellar mass, Hi gas
fraction, and where available the star formation rates (SFR) based on either
the WISE W4 or W3 mid-infrared magnitude, SFR from GALEX (near-UV data), the
total SFR (mid-infrared and NUV values added, using W4 if it and W3 are both
available), and the specific SFR (sSFR).

ID | RA | Dec | $z_{\rm HI}$ | $z_{\rm lit}$ | log10($M_{\rm HI}$) | log10($M_{*}$) | log10($f_{\rm HI}$) | SFRW3 | SFRW4 | SFRNUV | SFRtot | log10(sSFR)
---|---|---|---|---|---|---|---|---|---|---|---|---
|  |  |  |  | M⊙ | M⊙ |  | M⊙ yr-1 | M⊙ yr-1 | M⊙ yr-1 | M⊙ yr-1 | yr-1
1 | 08:44:53.72 | -09:49:10.16 | 0.0387 |  | 9.96 | 8.88 | 1.08 | 0.01 | 0.08 | 0.21 | 0.28 | -9.43
2 | 08:45:02.01 | -09:48:54.00 | 0.0383 |  | 10.12 | 9.49 | 0.63 | 0.11 | 0.30 | 0.16 | 0.46 | -9.83
3 | 08:45:00.28 | -09:49:56.91 | 0.0385 | 0.038557a | 10.64 | 10.46 | 0.18 | 3.24 | 4.79 | 2.32 | 7.11 | -9.61
4 | 08:45:07.14 | -09:48:58.61 | 0.0389 |  | 9.69 | 8.10 | 1.59 | 0.00 |  | 0.11 | 0.11 | -9.06
5 | 08:45:03.82 | -09:53:55.94 | 0.0392 |  | 9.25 | 8.10 | 1.14 |  |  |  |  |
6 | 08:44:35.89 | -09:55:30.16 | 0.0387 |  | 9.36 | 7.32 | 2.03 |  | 0.00 |  | 0.00 | -9.72
7 | 08:44:48.32 | -09:55:25.42 | 0.0424 |  | 9.76 | 9.52 | 0.25 | 0.10 | 0.39 | 0.19 | 0.58 | -9.76
8 | 08:45:41.55 | -09:56:12.56 | 0.0439 |  $\sim$0.054b | 10.40 | 10.44 | -0.04 | 0.38 | 0.72 | 0.72 | 1.44 | -10.28
9 | 08:45:16.10 | -09:54:08.20 | 0.0391 |  | 9.77 | 8.98 | 0.79 |  |  |  |  |
10 | 08:45:13.10 | -10:09:09.35 | 0.0423 |  | 10.37 | 9.92 | 0.45 | 0.01 | 0.09 | 0.31 | 0.40 | -10.32
11 | 08:45:26.42 | -10:08:38.50 | 0.0422 |  | 9.97 | 9.20 | 0.77 | 0.03 | 0.15 | 0.35 | 0.50 | -9.50
12 | 08:45:16.36 | -10:05:55.03 | 0.0416 |  | 9.67 | 9.81 | -0.14 | 0.14 | 0.28 | 0.46 | 0.74 | -9.95
13 | 08:45:08.56 | -10:07:32.75 | 0.0430 |  | 9.42 | 9.52 | -0.11 | 0.03 |  |  | 0.03 | -11.04
14 | 08:44:25.25 | -10:21:24.08 | 0.0557 |  | 9.97 | 8.99 | 0.98 |  |  |  |  |
15 | 08:44:37.08 | -10:14:38.52 | 0.0558 |  | 9.87 | 9.10 | 0.77 | 0.01 | 0.15 |  | 0.15 | -9.94
16 | 08:43:43.43 | -09:45:33.57 | 0.0548 |  | 9.92 | 9.34 | 0.58 | 0.03 | 0.05 | 0.49 | 0.54 | -9.61
17 | 08:43:45.98 | -09:44:29.32 | 0.0547 |  | 9.95 | 9.21 | 0.74 |  | 0.21 | 0.11 | 0.32 | -9.70
18 | 08:46:21.42 | -10:02:12.45 | 0.0331 |  | 10.22 | 9.97 | 0.26 | 0.29 | 0.36 | 0.23 | 0.60 | -10.19
19 | 08:46:32.23 | -10:04:18.73 | 0.0329 |  $\sim$0.055b | 10.36 | 10.02 | 0.33 | 0.03 | 0.42 | 0.17 | 0.59 | -10.25
20 | 08:43:38.83 | -10:08:23.96 | 0.0385 | 0.03886a | 9.48 | 10.63 | -1.15 | 0.08 |  |  | 0.08 | -11.73
21 | 08:43:39.64 | -10:05:39.58 | 0.0390 |  | 9.10 | 7.59 | 1.51 | 0.01 |  |  | 0.01 | -9.59
22 | 08:43:41.26 | -10:03:23.66 | 0.0378 |  | 9.26 | 8.83 | 0.43 |  | 0.04 |  | 0.04 | -10.19
23 | 08:42:56.57 | -09:24:17.91 | 0.0386 |  $\sim$0.048b | 10.27 | 10.33 | -0.06 | 0.07 | 0.06 |  | 0.06 | -11.57
24 | 08:46:05.74 | -10:09:35.30 | 0.0423 |  $\sim$0.058b | 10.02 | 10.17 | -0.15 | 0.40 | 1.12 | 0.18 | 1.30 | -10.06
25 | 08:43:26.70 | -09:51:22.16 | 0.0412 | 0.040802a | 10.21 | 10.19 | 0.02 | 0.59 | 1.35 |  | 1.35 | -10.06
26 | 08:42:58.09 | -09:56:37.80 | 0.0572 |  | 10.01 | 8.94 | 1.07 | 0.00 |  |  |  |
27 | 08:43:30.57 | -09:35:52.50 | 0.0562 |  | 9.45 | 8.64 | 0.81 | 0.01 |  |  | 0.01 | -10.64
28 | 08:44:08.10 | -09:57:56.62 | 0.0546 |  | 10.08 | 9.46 | 0.62 | 0.04 | 0.29 |  | 0.29 | -9.99
29 | 08:44:06.75 | -10:03:19.94 | 0.0528 |  | 9.70 | 8.26 | 1.43 | 0.00 |  |  |  |
30 | 08:46:51.85 | -09:59:56.26 | 0.0525 |  $\sim$0.041b | 10.17 | 10.62 | -0.44 | 0.80 | 0.60 | 1.35 | 1.95 | -10.33
31 | 08:45:46.14 | -10:05:40.65 | 0.0529 |  | 9.76 | 8.95 | 0.81 | 0.14 | 0.16 | 0.17 | 0.33 | -9.43
32 | 08:44:50.83 | -09:45:00.91 | 0.0519 |  | 9.79 | 9.62 | 0.17 | 0.06 | 0.27 | 0.16 | 0.43 | -9.99
33 | 08:43:33.29 | -09:43:02.85 | 0.0518 |  | 9.97 | 9.57 | 0.40 | 0.20 | 0.30 | 1.04 | 1.34 | -9.44
34 | 08:44:32.36 | -10:07:55.08 | 0.0421 |  $\sim$0.042b | 9.76 | 10.80 | -1.04 | 0.39 | 0.87 |  | 0.87 | -10.86
35 | 08:46:05.67 | -10:30:20.14 | 0.0412 |  | 9.99 | 9.43 | 0.56 | 0.04 | 0.10 | 0.45 | 0.55 | -9.70
36 | 08:42:47.31 | -09:51:26.29 | 0.0406 |  | 9.71 | 9.19 | 0.52 | 0.00 | 0.17 |  | 0.17 | -9.97
37 | 08:43:34.37 | -10:25:25.55 | 0.0337 |  $\sim$0.032b | 9.53 | 9.98 | -0.45 | 0.70 | 0.98 |  | 0.98 | -9.98
38 | 08:44:12.61 | -09:49:03.91 | 0.0520 |  | 9.66 | 8.53 | 1.13 | 0.00 |  | 0.11 | 0.11 | -9.49
39 | 08:44:31.77 | -10:01:44.75 | 0.0437 |  | 9.47 | 8.95 | 0.52 |  | 0.05 |  | 0.05 | -10.28
40 | 08:44:17.64 | -10:24:45.39 | 0.0338 |  | 9.33 | 8.71 | 0.62 |  | 0.05 |  | 0.05 | -10.05
41 | 08:43:13.45 | -10:07:15.54 | 0.0386 |  | 9.37 | 9.60 | -0.23 |  | 0.03 |  | 0.03 | -11.10
42 | 08:43:41.75 | -09:30:47.30 | 0.0384 |  | 9.46 | 8.41 | 1.05 |  |  | 0.05 | 0.05 | -9.71
43 | 08:45:28.11 | -09:48:20.58 | 0.0329 |  | 9.29 | 7.88 | 1.41 |  |  | 0.05 | 0.05 | -9.18
44 | 08:44:59.09 | -09:46:43.20 | 0.0383 |  | 8.99 | 9.77 | -0.77 | 0.56 | 1.93 |  | 1.93 | -9.48
45 | 08:42:45.50 | -09:23:59.07 | 0.0335 |  | 9.71 | 9.48 | 0.23 | 0.02 | 0.10 |  | 0.10 | -10.47
46 | 08:45:24.13 | -09:59:29.32 | 0.0874 |  | 10.21 | 9.89 | 0.32 | 0.32 | 0.15 |  | 0.15 | -10.71
47 | 08:44:38.71 | -09:45:40.14 | 0.0867 |  | 9.97 | 9.07 | 0.90 | 0.05 |  |  | 0.05 | -10.37
48 | 08:44:23.13 | -10:03:10.17 | 0.0194 |  | 9.18 | 8.73 | 0.45 | 0.00 |  |  |  |
49 | 08:45:29.87 | -09:47:54.63 | 0.0323 |  | 9.04 | 7.36 | 1.68 |  |  |  |  |

References: ${a}$: Jones et al. (2009), $b$: Bilicki et al. (2014)

Table 3: Radio continuum flux densities for our Hi detections. All other detections have $S_{\rm 1.362GHz}$ upper limits of 0.02 mJy. ID | $S_{\rm 1362~{}MHz}$ | Unresolved?
---|---|---
| mJy | (9.1 $\times$ 6.8" beam)
2 | 0.5 | Yes
3 | 7.3 | Yes
8 | 0.4 | Yes
10 | 0.1 | Yes
12 | 0.1 | Yes
18 | 0.9 | No
24 | 0.5 | Yes
25 | 0.3 | Yes
30 | 0.7 | No
33 | 0.5 | Yes
34 | 1.1 | Yes
37 | 1.5 | Yes
44 | 1.2 | Yes
45 | 0.4 | Yes
46 | 0.1 | Yes
Figure 3: The Hi mass versus the stellar mass for the 49 galaxies detected in
this study. Where available, the points have been coloured by the combined SFR
calculated from the mid-infrared and near-UV data, or as black circles
otherwise. We note that galaxy ID3 has an enhanced SFR of more than 7 M⊙ yr-1.
The $M_{\rm HI}$-$M_{*}$ relation from Maddox et al. (2015) for ALFALFA
galaxies is overlaid for comparison in grey. Figure 4: The $M_{\rm HI}$ masses
versus redshift for our sample. The dashed line gives a 5$\sigma$ sensitivity,
dot-dashed line at 6$\sigma$, and dotted line at 10$\sigma$, assuming an
unresolved galaxy with velocity width of 200 km s-1, using equation 157 of
Meyer et al. (2017). Figure 5: Histograms of the Hi mass (top left panel),
stellar mass (top right), combined SFR (bottom left), and Hi gas fraction
(lower right) for the 49 galaxies detected in Hi in the 2.3 hr MeerKAT
pointing. Figure 6: WISE colour-colour properties of the galaxies in our
sample which were detected in WISE bands W1, W2 and W3. Where available,
points are coloured by the combined SFR, or given as black circles otherwise.
Points are overlaid on the scheme given in fig. 10 of Wright et al. (2010).
Image generated via code by Chao-Wei Tsai.

###  3.1 Properties of the sample

In Figure 3 we give the $M_{\rm HI}$ vs $M_{*}$ relation for the sample, with
points coloured by their SFR (where available). Broadly speaking the expected
correlation between the two can be seen; we compare with the relation
presented by Maddox et al. (2015) in grey for the Arecibo Legacy Fast ALFA
Survey(ALFALFA; Haynes et al., 2018). There are only two significant outliers
($\sim$1 dex). One is ID43 which has the lowest Hi mass of our sample (just
below 109 M⊙) and a higher corresponding stellar mass, and is separated below
the rest of the sample in this relation by up to $\sim$1 dex (see discussion
in Section 3.1.1). The other outlier is ID3, with a higher $M_{\rm HI}$ than
other galaxies with similar stellar masses, which we discuss below and in
Section 3.2.1. Also as expected, the higher mass galaxies, particularly in
stellar mass, tend to have higher SFRs.

In Fig. 4 we give the Hi mass versus redshift. Included are the 5, 6, and
10$\sigma$ sensitivity limits for our survey, using equation 157 of Meyer et
al. (2017) and assuming unresolved Hi sources with a velocity width of 200 km
s-1 for 104.49 kHz-wide channels as presented here. The gap between detections
and the line indicates we did not have fully searched to 5$\sigma$ (e.g. the
SoFiA search had a threshold of 10 sigma to limit false detections, while the
matched-filter approached used a minimum of 6$\sigma$), and/or that we missed
detections, or that these sensitivity curves are too optimistic. Figure 5
gives the distribution for Hi mass, stellar mass, combined SFR, and Hi gas
fraction. In regards to the lower-left panel for the SFR distribution for the
42 available measurements, one clear outlier can be seen, corresponding to ID3
with a SFR greater than 7 M⊙ yr-1 (the next highest being ID30 with SFR = 1.95
M⊙ yr-1). We discuss this case further in Section 3.2.1.

####  3.1.1 Masquerading megamasers?

Figure 7: Histograms of redshifts for 46 of the 49 galaxies in our detected
sample, excluding the lowest-redshift and two highest-redshift galaxies (IDs
46–48). We note that the colouring of the bins used does not directly match
that used in Fig. 2. Figure 8: Cumulative histograms as a function of the
distance to neighbouring Hi galaxies, for all 49 galaxies detected by MeerKAT,
ordered in increasing redshift left to right, top to bottom. The colour scheme
matches that used in Fig. 7. Several galaxy groups can be identified - e.g.
all seven galaxies at $0.030<z<0.035$ (dark blue) are within 5 Mpc of each
other. Figure 9: MeerKAT Hi contours overlaid on a three-colour DECaLS DR10
image for galaxy IDs 1, 2, 3 and 4. There is clear interaction between the
southern-most galaxy (ID3) and its neighbouring counterparts (ID1 and 2).
Galaxies ID1 and 2 have been found to have relatively diminished SFRs (0.28
and 0.46 M⊙ yr-1) compared to the SFR of ID3 (7.11M⊙ yr-1). Image generated
through SIP.

We have limited redshift information available in the literature for this
sample. While three optical redshifts agree well with the measured Hi redshift
from SoFiA, and a further seven photometric redshifts from WISE data also
indicate that the emission seen by MeerKAT for those galaxies is Hi, that
leaves another 39 galaxies without redshift information prior to this study.
As such, it is possible that rather than Hi emission, a detection could
instead be of another radio spectral line, such as hydroxyl (OH), as
demonstrated in the detection of an OH megamaser with Apertif (Hess et al.,
2021), and in the LADUMA survey (Glowacki et al., 2022), both through the
1665–1667 MHz OH doublet. OH megamasers are relatively rarer with little over
100 detected to date, although the advent of SKA pathfinders such as MeerKAT
and their associated spectral-line surveys are poised to improve on this space
(Roberts et al., 2021).

Short of dedicated spectral-line follow-up to verify redshifts for each
source, it is possible to make a prediction of whether a detection is an OH
megamaser at a higher redshift, which are typically seen in starburst
galaxies, through the WISE magnitude and colour information. We give the WISE
colour-colour distribution in Figure 6, overlaid on the classifications given
in fig. 10 of Wright et al. (2010). Most of our detections fall within the
spiral galaxy region of the plot, with a couple falling in the starburst
region (including the aforementioned ID3, which was confirmed to be detected
in Hi from its optical spectroscopic information). One source appears to be
QSO-like in its WISE colour properties, ID45. ID45 is seen to have unresolved
radio continuum with flux density $S_{\rm 1362~{}MHz}$ = 0.4 mJy, but no other
radio continuum or optical spectrum has been reported for this galaxy which
could determine whether it hosts an AGN.

Using the machine-learning approach described by Roberts et al. (2021) which
uses WISE W1, W2 and W3 magnitudes and the peak frequency of the spectral-line
emission with a k-Nearest Neighbours algorithm (private communication),
predictions were made for all 49 galaxies on whether the emission seen
corresponds to Hi or OH, as performed for the detection by Glowacki et al.
(2022). Only one detection, ID44, was identified as a potential OH megamaser.
The algorithm based upon the W1 vs W1–W2 information favoured the OH megamaser
model ($>$99%), but was outside any OH confidence interval for the algorithm
using W1–W2 vs W2–W3 (6% probability to be a OH megamaser).

We note that ID44 had the lowest measured (assumed) Hi mass of our sample
given the corresponding $z_{\rm HI}$ assumed; if it is actually an OH
megamaser than its $M_{\rm OH}$ would be higher due to a higher true distance.
ID44 was also the most significant outlier in the $M_{\rm HI}$ vs $M_{*}$
relation (Fig. 3) - this galaxy being an OH megamaser would explain this
outlier result. ID44 also has the third-highest SFR of our sample (1.93 M⊙
yr-1), which also matches the picture of OH megamasers typically living in
starburst galaxies that have undergone a recent merger or interaction. ID44
has the reddest W2–W3 colour of our sample (4.09 mag), placing it in the
ULIRGs (ultra-luminous infrared galaxy) and starburst sector of Fig. 6.

Lastly, we note that ID44 is also seen in radio continuum in our MeerKAT
observation, with a flux density of $S_{\rm 1362~{}MHz}$ = 1.2 mJy, and has
near-infrared $K-$band magnitude measurements of 14.017 $\pm$ 0.123 and 14.254
$\pm$ 0.088 from the Two Micron All Sky Survey (2MASS; Skrutskie et al.,
2006). We use the photometric $K-$band-redshift relation for radio galaxies
presented by Willott et al. (2003) (equation 1). Assuming $z$ = 0.0383 given
by the assumption the spectral-line emission is Hi, the expected $K-$band
magnitude is 10.33 mag. OH emission, corresponding to a host galaxy at
redshift $z$ $\sim$ 0.219, gives the expected $K-$band magnitude of 14.24 mag,
within the errors of the measured $K-$band magnitude for ID44. We repeat this
analysis for all other galaxies in our sample with radio continuum (14) and
$K-$band measurements in the literature (9). Two of these (IDs 2 and 12) had
photometric redshift estimates that would favour OH rather than Hi, although
we note no other evidence available supports the hypothesis these are OH, and
ID2 is seen to be interacting with ID3 which has an optical spectroscopic
redshift of 0.0385, in line with Hi (Section 3.2.1). Two other sources had
photometric redshifts from the $K-$band relation that loosely support the Hi
redshift, with the rest inconclusive, in part owing to the range of $K-$band
values found in the literature for these sources (e.g. 11.975–13.008 for
ID34).

We also consider the WISE information. The WISE colours for ID44 sits in the
high-energy radio galaxy (HERG) distribution for the Large Area Radio Galaxy
Evolution Spectroscopic Survey (LARGESS; Ching et al., 2017). We applied the
photometric redshift relations based upon the LARGESS sample for HERGs using
the W1 and W2 bands from table 2 of Glowacki et al. (2017a). This method
provides a photometric redshift of 0.12 and 0.16 from W1 and W2 respectively,
which suggests a higher-redshift host than 0.0383 expected from Hi. However,
these details can only be treated as circumstantial evidence towards it being
an OH megamaser at $z$ $\sim$ 0.219, in addition to the predictions from
methods by Roberts et al. (2021), rather than something definitive. Further
follow-up observations, namely spectroscopic optical measurements, will be
necessary to properly determine whether we do have a OH megamaser within the
dataset presented here.

###  3.2 Spatial distribution of the galaxies

In Figure 7 we give the redshift distribution for 46 of our 49 detections,
omitting IDs 46–48 at $z_{\rm HI}$ of $\sim$0.087 and 0.019, to zoom into the
bulk of our detections. We note that the colour scheme of the bins hence does
not match that of Fig. 2. Three main groups are seen: one at $z_{\rm HI}$
$\sim$ 0.033 (seven galaxies), another larger set at $\sim$0.041 (which
includes three sub-groupings of 14, 9 and 3 galaxies), and another at
$\sim$0.055 (also with several sub-groups, totalling 13 galaxies). This,
combined with the distribution seen in Fig. 2, indicates that multiple galaxy
groups have been detected, potentially as part of a supergroup. The distances
between members of separate galaxy groups e.g. IDs 19 and 25 at $z=0.0329$ and
$0.0412$ ranges from $\sim$15–100 Mpc.

We present Figure 8 to further examine galaxy groups in our sample. Assuming
all detections are in Hi for each galaxy (one galaxy focused on per panel,
labelled by ID and ordered from lowest to highest redshift), a cumulative
histogram is given, indicating the number of galaxies within 10 Mpc. For
example, for the galaxies between $0.032<z<0.034$ (navy-coloured histograms),
all 6 other companions are within 5 Mpc. It is evident that astronomers can
use MeerKAT for a $<3$ hour on-source observation to trace Hi-rich galaxy
groups and larger structures.

####  3.2.1 Interacting galaxies

Figure 10: Top: Rotation curves for galaxy ID18. Presented is the observed
(total) rotation curve from the BBarolo model (grey), the stellar rotation
curve derived from PanSTARRS imaging (blue), the gas rotation curve from a Hi
surface density profile derived by BBarolo (red), and the dark matter rotation
curve (purple) derived by subtracting the gas and stellar curves in quadrature
from the observed. We also include two additional points (grey stars) for the
BBarolo rotation curve fit to aid the observed rotation and dark matter model
curve fits. 2nd panel: The ISO (orange) and the NFW (green) dark matter halo
model fits to the dark matter rotation curve. Bottom two panels: as before,
but without the two additional points added to the BBarolo curve. The radius
values for both models decreases slightly as a result. For all panels, shaded
regions indicate the 25 and 75-percentile error ranges for each fit, which is
not displayed for the NFW profile due to visibility issues when displaying
these larger errors.

There are a few examples in our sample of interacting galaxies. Despite the
short observing time thus far obtained with MeerKAT on this field, we present
the clearest example of galaxy interaction traced by Hi in Figure 9. Hi
intensity-map contours for galaxy IDs 1, 2, 3 and 4 (top-right, middle-top,
bottom, and top-left respectively) are overlaid on a DECaLS DR10 three-colour
image. Note also that galaxies ID 5, 6, and 9 are located to the south (Fig.
2), all which have slightly irregular velocity fields that hint at a possible
interaction, and ID44 to the north (also reflected in the cumulative
distributions of neighbouring Hi galaxies in Fig. 8 \- assuming ID44 is not a
hydroxyl megamaser). We also see a few galaxies with irregular Hi morphologies
and/or disturbed velocity fields (e.g. IDs 13, 17, and 21).

Galaxy ID3, a face-on spiral galaxy (2MASS J08445897-0946457) at $z$ =
0.038557, is the most massive in both Hi and stellar content of this
particular subset (and the highest Hi mass of all 49 galaxies presented here),
and is directly interacting in Hi with both ID1 and ID2. It also has from its
WISE and GALEX photometries the highest SFR of the sample by far, of 7 M⊙
yr-1. ID3 is more $M_{\rm HI}$-massive compared to other galaxies with similar
stellar masses in both this sample and in ALFALFA (Fig. 3 and Maddox et al.,
2015). In contrast, both ID1 and 2 have SFRs of less than 0.5 M⊙ yr-1, in the
lower half of the measured SFRs of the sample (Fig. 5), while ID4 only has a
SFRNUV of 0.11 M⊙ yr-1. Our conclusion hence is that ID3 is currently
stripping the Hi gas from its neighbours to fuel its own star formation
activity.

We note that galaxy IDs 16 and 17, as well as 43 and 49 (as noted in Section
3.1.1), are quite near each other, with the latter showing evidence of
interaction in their spectral-line emission (see Figure A1 of the Appendix
available online). This is in addition to the aforementioned ID34 (Fig. 1
bottom set) with an unconfirmed Hi detection of a neighbouring dwarf galaxy.
More sensitive radio observations will be able to further highlight the
environment around these galaxies and potential pre-processing effects.

###  3.3 Mass modelling

A few galaxies amongst our detections were sufficiently spatially resolved
(spanning at least three radio beams) in Hi to attempt dynamical modelling to
determine the stellar, the gas and the dark matter mass components of the
galaxies.

####  3.3.1 Rotation curves

We used the Hi content to trace the total rotation curve of the galaxy.
3D-Barolo (3D-Based Analysis of Rotating Objects via Line Observations), also
known as BBarolo (Di Teodoro & Fraternali, 2015), was used for fitting 3D
tilted-ring models to the individual SoFiA subcubes for galaxy IDs 2, 3, 8,
10, 18, 19, 24, and 48. However, as ID2 was interacting with ID3, we were
unable to properly produce reasonable dark matter mass models for these
galaxies. We hence removed both IDs 2 and 3 from the current investigation.
Outputs for the model moment maps constructed by BBarolo was compared with the
SoFiA moment maps, as well as the channel-by-channel maps (see Figure A2 for
an example for ID18 in the Appendix as online material) to determine the
goodness of the 3D tilted-ring fits when generating the total observed
rotation curve, and the Hi surface density profile for each galaxy. The Hi
surface density profile was used to determine the mass of Hi within each
tilted ring, which was multiplied by an assumed factor of 1.4 to account for
the contribution of helium (as in e.g. Westmeier et al., 2011; Reynolds et
al., 2019). We next converted the Hi surface density profile to a gas rotation
curve. The ‘Polyex’ parametric model for the rotational velocity profile was
fitted to the gas and total rotation curves (equation 2 of Giovanelli &
Haynes, 2002). The Polyex model is an analytic representation of rotation
curves based on the amplitude of the outer rotation curve, the exponential
scale length of the inner rotation curve, and the outer rotation curve slope.
It has been demonstrated to work well in observation datasets (e.g. Elson,
2017) and galaxies from hydrodynamical simulations (e.g. Glowacki et al.,
2020).

Table 4: Derived dark matter halo quantities for the ISO and NFW models for the 8 galaxies attempted. We note the best fitting model in each case, and also give the measured total dynamical mass from BBarolo. | ISO |  | NFW |  |  |  |  |
---|---|---|---|---|---|---|---|---
ID | $\rho_{\rm 0}$ | $R_{c}$ | c | $R_{\rm 200}$ | $V_{\rm 200}$ | $M_{\rm 200}$ | $M_{\rm tot}$ | Preferred
|  $M_{\odot}$ pc-3 | kpc |  | kpc | km s-1 | $M_{\odot}$ | $M_{\odot}$ | model
8 | 0.15 | 0.7 | 5.9 | 72 | 56 | 5.4$\times$1010 | 6.6$\times$1010 | ISO
10 | 0.35 | 1.0 | 9.6 | 143 | 120 | 4.8$\times$1011 | 2.2$\times$1011 | ISO
18 | 1.5 | 0.5 | 17.8 | 129 | 111 | 3.7$\times$1011 | 1.6$\times$1011 | ISO
19 | 2.9 | 0.3 | 22.6 | 107 | 87 | 1.9$\times$1011 | 1.1$\times$1011 | ISO
24 | 2.0 | 0.4 | 25.0 | 108 | 89 | 2.0$\times$1011 | 1.1$\times$1011 | ISO
48 | 2.3 | 0.2 | 26.5 | 63 | 51 | 3.8$\times$1010 | 1.7$\times$1010 | ISO

The stellar rotation curve was calculated from the isophotes derived from
PanSTARRS $r$-band imaging (see Section 2.3.1). Equation 1 was applied to
obtain the stellar mass in each isophote radius. Similarly, the stellar
rotation curve was then calculated from the stellar mass profile. In the top
panel of Figure 10 we give the total observed, gas, and stellar rotation
curves for ID18. We subtracted the gas and stellar rotation curves in
quadrature from the observed rotation curve to obtain a dark matter rotation
curve. The rotation curves for other galaxies are given in Figure A4 within
the Appendix as online material.

Owing to a poor sampling of the inner rising parts of the rotation curves,
which resulted in high uncertainties for the Polyex fits, we tested fitting
for additional points. Relative to the datapoint in the rotation curve at
($r_{\rm 1}$, $v_{\rm 1}$) in the innermost part of the galaxy, we added two
more datapoints at ($r_{\rm 1}$/2, $v_{\rm 1}\times 0.9$) and ($r_{\rm 1}$/4,
$v_{\rm 1}\times 0.6$). These two points were found to agree well with the
original Polyex fit. We then repeated the Polyex fitting, as shown for ID18 in
the top panel of Figure 10. We find that this was not necessary for reasonable
rotation curves and corresponding mass model fits for IDs 10 and 18, but did
reduce the error in the Polyex and mass model curve fits, with more
significant improvements observed for the remaining four galaxies (see Figures
in Appendix). We note that including these two additional points also
decreases the $\rho_{\rm 0}$ values and slightly decreases the radii parameter
values found from the mass modelling fits, although parameter values prior to
this were consistent with values for other galaxies in the literature
(expanded on below).

####  3.3.2 Dark matter halo

We adopted two models for the dark matter halo. The first is the $\Lambda$CDM
Navarro-Frenk-White (NFW) cusp-dominated model (Navarro et al., 1996), with a
density profile of

$\rho_{\rm NFW}(r)=\frac{\rho_{\rm crit}}{(r/R_{s})(1+r/R_{s})^{2}},$ (5)

where $R_{s}$ is the scale radius, and $\rho_{\rm crit}$ is the critical
density of the universe ($\frac{3H^{2}}{8\pi G}$). This results in the
velocity profile

$V_{\rm NFW}(r)=V_{\rm
200}\sqrt{\frac{ln(1+cx)-cs/(1+cx)}{x[ln(1+c)-c/(1+c)]}},$ (6)

where $R_{\rm 200}$ is the point where the dark matter halo density is greater
than the critical density, $V_{\rm 200}$ is the velocity at this point, c =
$R_{\rm 200}$/$R_{s}$, and $x$ = $r/R_{\rm 200}$.

The second dark matter halo model considered was the spherical pseudo-
isothermal ISO core-dominated dark matter halo model, which assumes a constant
density within the galaxy core (de Blok et al., 2008). It is described by the
density profile

$\rho_{\rm iso}(r)=\frac{\rho_{0}}{1+r/R_{c})^{2}},$ (7)

where $\rho_{\rm 0}$ is the core density, and $R_{c}$ is the core radius, both
treated as free parameters within physical bounds from the literature. The
corresponding rotational velocity is then:

$V_{\rm iso}(r)=\sqrt{4\pi G\rho_{\rm 0}R_{c}^{2}(1-\frac{R_{c}}{r}{\rm
tan^{-1}}(\frac{r}{R_{c}}))}.$ (8)

In the bottom panel of Figure 10 we show the best fits to the dark matter halo
rotation curves from the NFW and ISO models for ID18, with other galaxies in
the bottom panels of Figure A4 in the Appendix as online material. In Table
LABEL:tab:modelling we give the corresponding ISO and NFW values, indicate
which model was preferred (determined via a $\chi^{2}$ test), and the dark
matter halo mass derived from BBarolo. ISO was the preferred model in all six
galaxies investigated here, with large errors found for the NFW curve fits (as
such, they are not plotted for visibility).

The majority of our galaxies are dark matter dominated, with dark matter halo
masses exceeding 1$\times$1011 M⊙, and M200 greater still. We note that the
inner, rising parts of the rotation curves are not well sampled, particularly
in our Hi data. As four of our six galaxies had noticeably improved dark
matter rotation curves and corresponding mass models from the inclusion of two
additional points at inner radii, we conclude that just using the existing
dataset results in a higher uncertainty on the values derived from the fitted
mass models. Deeper and higher resolution Hi data will be able to improve on
this aspect. The values we obtain for the ISO and NFW model parameters (Table
LABEL:tab:modelling) are however consistent with those found for other
galaxies. In table 3 of de Blok et al. (2008), values ranged for the following
parameters in the examined sample of THINGS galaxies: $\rho_{\rm 0}$:
0.9–298.7 $M_{\odot}$ pc-3; $R_{\rm c}$: 0.01—45.63 kpc; $c$: $<$0.1–30.9;
$V_{\rm 200}$: 35.2–$>$500 km s-1 (noting that de Blok et al. (2008) also
presents ISO and NFW parameter values from other implementations in further
tables). Swaters et al. (2011) found values of $\rho_{\rm 0}$: 0.5–570
$M_{\odot}$ pc-3 and $R_{\rm c}$: 0.5—2.7 kpc for dwarf galaxies, and Oh et
al. (2015) found values of $\rho_{\rm 0}$: 0.008–2.132 $M_{\odot}$ pc-3 and
$R_{\rm c}$: 0.15—8.4 kpc for LITTLE THINGS galaxies.

##  4 Serendipity

We examine whether our serendipitous discovery of 49 Hi-rich galaxies is
unexpected. While Ranchod et al. (2021) reported on the discovery of an Hi
group with 23 members in a MIGHTEE pointing, this is to date the first
reported discovery in an observation not intending to search for such galaxies
in the first place. But is this unusual? This is not straightforward to tell,
as larger spectral-line surveys are ongoing, so truly untargeted surveys with
the likes of MeerKAT or other SKA pathfinder telescopes are not yet available.
For example, while Pre-Pilot and Pilot survey results are now available for
WALLABY, these observations were all in pre-selected fields, with full survey
observations only recently started. MIGHTEE-HI also targets specific fields
with pre-existing ancillary datasets, including “10–15 lower-mass clusters and
galaxy groups per square degree" (Maddox et al., 2021).

In the work by Jones et al. (2020), four optical galaxy group catalogues were
cross-matched with ALFALFA to measure the Hi mass function (HIMF) for group
galaxies. They concluded there was no single group galaxy HIMF; while two were
found to be similar, the other two included either more lower-mass, Hi-rich
galaxies or no low-mass galaxies due to selection. They also concluded that
due to the far greater number of field galaxies in ALFALFA than group
galaxies, there was no region of their environment parameter space where group
galaxies were the dominant population. Cautun et al. (2014) applied a ‘NEXUS+’
model and found 77% of the total volume fraction of the two high resolution
Millennium simulations was occupied by voids, and 18% by walls, and only 6% by
filaments (fig. 8). Similarly, Falck & Neyrinck (2015) found agreement for the
Planck and WMAP simulations (fig. 3). These results suggest that to discover
several groups in a relatively short observation in a single MeerKAT pointing
(where the sensitivity of ALFALFA was not reached) is not likely.

In early examination of five-hour tracks undertaken with MeerKAT with the
MeerKAT HI Observations of Nearby Galactic Objects - Observing Southern
Emitters survey (MHONGOOSE; de Blok et al., 2016), which targets 30 nearby
disk and dwarf galaxies, additional Hi detections have been discovered with a
median of $\sim$20 detections per pointing within a 50 MHz chunk, with an
upper bound of 50 (private communication). Given this observation has less
than half the on-source time of MHONGOOSE pointings, 49 individual detections
is more than is typically expected to be detected. However, optical
spectroscopic redshift information of the field is required to better
ascertain whether this pointing was simply fortunate enough to target a dense
area of the sky in terms of large scale structure. Nonetheless, if one assumes
there are several Hi-rich galaxies to be found within any one MeerKAT pointing
based on this discovery, findings from MIGHTEE-HI, and preliminary MHONGOOSE
results, then there are undoubtedly a large number of galaxies awaiting
detections within existing and upcoming MeerKAT Open Time observations.

The sensitivity of MeerKAT in this frequency space is currently unparalleled,
which enables the detection of lower Hi-mass galaxies than those detected in
the HIPASS and ALFALFA all-sky surveys in less observing time. MeerKAT can
also achieve greater sensitivity than the ongoing WALLABY all-sky survey with
ASKAP, albeit with a far smaller field of view. Observations with MeerKAT
hence will be able to detect galaxy group members with lower Hi mass than any
other survey until the SKA. Below $z~{}<~{}0.1$ (above $\sim$1300 MHz) there
is no significant radio frequency interference (RFI), owing to the radio-quiet
site of the MeerKAT site. This redshift/frequency space is included in L-band
spectral-line observations with MeerKAT - typically zoom-mode observations
with MeerKAT will be focused on Hi rather than e.g. OH. We encourage Open Time
observers to investigate their datasets for Hi-rich galaxies (as well as
potentially OH megamasers). Such findings will collectively increase the
number of galaxy groups we can study in Hi and aid investigations into e.g.
the effect of pre-processing on galaxy group members, and more broadly galaxy
and galaxy group/cluster evolution, driven by the large science surveys of SKA
pathfinder telescopes.

##  5 Conclusions

We present the serendipitous discovery of 49 Hi-rich galaxies within a single
2.3 hour pointing with MeerKAT in Open Time data. With the use of ancillary
data from PanSTARRS, WISE, 2MASS, and GALEX, we obtained stellar masses and
star formation rates to complement the Hi information we present (Hi masses,
spectra, intensity and velocity maps).

Within our sample we find examples of galaxy interactions, including a case of
one galaxy stripping and fuelling star formation (to greater than 7 M⊙ yr-1)
from two neighbouring galaxies. Multiple Hi-rich galaxy groups are identified,
with three major groupings at $z~{}\sim$ 0.033, 0.041, and 0.055 - therefore
it is possible that we have also detected a supergroup or filament in this
MeerKAT pointing. We also find one potential OH megamaser within our sample,
although this is not confirmed due to a lack of optical spectroscopic
redshifts available. We generate rotation curves and dark matter mass models
for six galaxies in our sample that were sufficiently spatially resolved and
not found to be significantly interacting with another galaxy.

We considered the probability of detecting 49 Hi-rich galaxies in this
relatively short MeerKAT pointing. It appears that 49 detections are unlikely,
prompted by the study by Jones et al. (2020) which demonstrated that there is
no single group galaxy HIMF and a far greater number of field galaxies than
group galaxies within ALFALFA. Given the demonstrated ability of MeerKAT in
both major science surveys and another Open Time proposal (Healy et al., 2021)
to detect new galaxies in Hi and OH, which is attributed to an RFI-quiet
environment and high sensitivity in this space, we encourage other users of
spectral-line Open Time data to investigate their datasets. With sufficient
effort, significant datasets can be obtained to complement large science
surveys aiming to address outstanding questions in galaxy evolution, including
the formation of galaxy groups and their transition into supergroups and
clusters.

## Acknowledgements

We thank the anonymous referee for the helpful feedback provided that has
improved this paper. We thank Erwin de Blok, Barbara Catinella, Luca Cortese,
Nathan Deg, Rory Hackett, Scott Haydon, Julia Healy, Dane Kleiner, Ferry
Lanter, Filippo Maccagni, John Forbes, and Andrew Sullivan for useful
discussions and feedback on the paper. MG is supported by the Australian
Government through the Australian Research Council’s Discovery Projects
funding scheme (DP210102103).

The MeerKAT telescope is operated by the South African Radio Astronomy
Observatory (SARAO; www.sarao.ac.za), which is a facility of the National
Research Foundation (NRF), an agency of the Department of Science and
Innovation. The MeerKAT data presented in this paper were processed using the
ilifu cloud computing facility (www.ilifu.ac.za), which is operated by a
consortium that includes the University of Cape Town (UCT), the University of
the Western Cape, the University of Stellenbosch, Sol Plaatje University, the
Cape Peninsula University of Technology and the South African Radio Astronomy
Observatory. The ilifu facility is supported by contributions from the Inter-
University Institute for Data Intensive Astronomy (IDIA, which is a
partnership between the UCT, the University of Pretoria and the University of
the Western Cape), the Computational Biology division at UCT, and the Data
Intensive Research Initiative of South Africa (DIRISA). This work was carried
out using the data processing pipelines developed at the Inter-University
Institute for Data Intensive Astronomy (IDIA) and available at https://idia-
pipelines.github.io. IDIA is a partnership of the University of Cape Town, the
University of Pretoria and the University of the Western Cape. This work made
use of the CARTA (Cube Analysis and Rendering Tool for Astronomy) software
(https://cartavis.github.io), and iDaVIE-v (Immersive Data Visualisation
Interactive Explorer for Volumetric Rendering; Comrie et al., 2021b; Jarrett
et al., 2021). This research made use of
hips2fits,333https://alasky.cds.unistra.fr/hips-image-services/hips2fits a
service provided by CDS. This research has made use of the NASA/IPAC
Extragalactic Database (NED), which is operated by the Jet Propulsion
Laboratory, California Institute of Technology, under contract with the
National Aeronautics and Space Administration. Part of this research was
conducted through the International Centre for Radio Astronomy Research
(ICRAR) summer studentship program.

## Data Availability

Data will be made available upon reasonable request. The Open Time MeerKAT
data used in this survey is already publicly available via the SARAO archive
(SBID 1617470178).

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##  Appendix A Images and notes on individual sources

We present further SIP output images as in Fig. 1, and give notes for each
detection. We also present rotation curves and dark matter model fits as in
Fig. 10.

ID1: Host is a blue galaxy in a group environment. Interacting with ID3, where
it appears to be having its Hi gas stripped by ID3. This may explain its
relatively diminished SFR of 0.28 M⊙ yr-1 and disturbed velocity map.

ID2: Host is an edge-on disk galaxy. Like ID2, this galaxy is interacting with
ID3, with more redshifted gas on its south side being stripped. Small radio
continuum point source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.4 mJy.

ID3: Host is a large (log10($M_{*}$) = 10.46 M⊙) face-on spiral galaxy (2MASS
J08445897-0946457) with an optical spectroscopic redshift of $z$ = 0.038557.
It has a high SFR of 7.11M⊙ yr-1. This is attributed to the active stripping
of gas from both ID1 and 2. Large radio continuum point source seen with flux
density $S_{\rm 1362~{}MHz}$ = 7.3 mJy.

ID4: Host appears to be a faint blue galaxy. It is close to ID2, but does not
yet show clear evidence of interaction with the given sensitivity of the
MeerKAT observation, although its velocity map is not very regular.

ID5: Faint optical source identified as the host, with log10($M_{*}$) = 8.10
M⊙. To the south of IDs 1, 2, 3 and 4.

ID6: Faint optical source identified as the host, with log10($M_{*}$) = 7.32
M⊙. To the south of IDs 1, 2, 3 and 4.

ID7: Host is a larger galaxy relative to ID5/6. To the south of IDs 1, 2, 3
and 4.

ID8: Host is a large face-on spiral galaxy, with a potential nearby companion
visible to the right in the optical, with a minor peak in the Hi intensity map
aligning with the companion. No evidence of interaction in its velocity map or
spectrum - higher resolution imaging is required. Small radio continuum point
source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.4 mJy.

ID9: Host is a faint blue galaxy in the optical. Disturbed velocity map. To
the south of IDs 1, 2, 3 and 4.

ID10: Host is a large blue galaxy in the optical, with an apparent nearby red
companion. Hi spectrum is slightly asymmetric with more flux observed at the
redshifted (higher velocity) end. Part of a sub-group with IDs 11, 12 and 13,
to the south of lower-ID galaxies. Potential faint radio continuum emission
with flux density $S_{\rm 1362~{}MHz}$ $\sim$ 0.1 mJy.

ID11: Host actually appears as a blue galaxy in DeCALs. Asymmetric Hi spectrum
observed, and with a potential Hi feature extending to the upper left, as seen
in the intensity and velocity map. Part of a sub-group with IDs 10, 12 and 13,
to the south of lower-ID galaxies.

ID12: Host is a mostly face-on disk galaxy, with log10($M_{*}$) = 9.81 M⊙.
Part of a sub-group with IDs 10, 11 and 13, to the south of lower-ID galaxies.
Potential faint radio continuum emission with flux density $S_{\rm
1362~{}MHz}$ $\sim$ 0.1 mJy.

ID13: Host is a faint blue galaxy. Disturbed intensity and particularly
velocity map. Part of a sub-group with IDs 10, 11 and 12, to the south of
lower-ID galaxies.

ID14: Host identified in the optical albeit required to use PanSTARRS imaging
with noticeable streaks seen in the image. Not part of the aforementioned
group galaxies (higher redshift), instead tracing out a separate filament
primarily in the right hand side of the MeerKAT pointing (IDs 14–17, 26–32,
38).

ID15: Host is an edge-on disk galaxy.

ID16: Host is a blue spiral galaxy. Close to ID17.

ID17: Host is difficult to distinguish - either of two similarly-sized blue
galaxies in the optical. Close to ID16. Disturbed velocity map and a possible
extended feature to the south.

ID18: Host is an edge-on disk galaxy, with a bright counterpart near it
spatially (very likely a star). Close to ID19. Lopsided Hi spectrum with more
flux on its blueshifted (lower velocity) side. Elongated radio continuum
source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.9 mJy.

ID19: Two galaxies nearby, with the Hi centred on the leftmost galaxy. The
peak of the Hi however aligns with the rightmost galaxy, although this peak
contour is smaller than the radio beam. Fairly symmetric spectrum. Close to
ID18.

ID20: Host is a possible S0 galaxy, with the Hi extend somewhat perpendicular
to the optical alignment. Close to IDs 21 and 22. Spectroscopic redshift of
$z$ = 0.03886.

ID21: Very faint optical host identified (log10($M_{*}$) = 7.59 M⊙), which
drops out in the PanSTARRS $z$ and $y$ bands. Disturbed Hi maps. Between IDs
20 and 22 - a potential interaction at play?

ID22: A faint edge-on host identified, with no coverage in DECaLS DR10. To the
north and close to IDs 20 and 21.

ID23: Host is a large and spectacular edge-on spiral galaxy. Hi gas
distribution appears to have a deficiency in the centre by the host galaxy
bulge; prior to viewing optical imaging had been identified as two separate
galaxies, including by SoFiA. ID45 identified as a nearby galaxy.

ID24: Host is a large bright galaxy (log10($M_{*}$) = 10.17 M⊙). Small radio
continuum point source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.5 mJy.

ID25: Host is a large spiral face-on galaxy, with log10($M_{*}$) = 10.19 M⊙.
Optical spectroscopic redshift of $z$ = 0.04080. Small radio continuum point
source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.3 mJy.

ID26: Faint optical host identified, with log10($M_{*}$) = 8.94 M⊙.

ID27: Narrow Hi spectrum, with a faint optical galaxy also identified as the
host. Velocity map is curious in that the centre is redshifted - worth further
scrutiny in any follow-up observations.

ID28: Host is an edge-on spiral galaxy. Possible Hi feature emerging in the
north end. Close to ID 29.

ID29: Quite unusual Hi distribution evident. Optical host is hard to identify
in PanSTARRS but clearer in the north side as a faint blue galaxy in DECaLS
DR10, suggesting the southern Hi content is a tail or other interaction
feature. Close to ID 28.

ID30: Host is a bright, large galaxy in the optical, with log10($M_{*}$) =
10.62 M⊙. Extended, diffuse radio continuum source seen with flux density
$S_{\rm 1362~{}MHz}$ = 0.7 mJy.

ID31: Host is a faint blue galaxy. Hi is extended, with redshifted components
evident in the velocity map to the north and south.

ID32: Host is an edge-on spiral galaxy. Lopsided Hi spectrum and the velocity
field indicates a strong warp in the disk.

ID33: Host is a large spiral galaxy. Lopsided Hi spectrum. Small radio
continuum point source seen with flux density $S_{\rm 1362~{}MHz}$ = 0.5 mJy.

ID34: Host is a large optical galaxy with the largest stellar mass in our
sample (log10($M_{*}$) = 10.80 M⊙). Evidence of a nearby companion and faint
tail connecting it to the main galaxy, although deeper Hi observations are
required to confirm this. Small radio continuum point source seen with flux
density $S_{\rm 1362~{}MHz}$ = 1.1 mJy.

ID35: Host is a blue galaxy in the optical, at the edge of DECaLS DR10
coverage.

ID36: Host appears as a red galaxy in PanSTARRs. Most of the Hi emission is to
the south.

ID37: Host is a face-on spiral galaxy. Disturbed Hi velocity map. Small radio
continuum point source seen with flux density $S_{\rm 1362~{}MHz}$ = 1.5 mJy.

ID38: Host is a faint blue galaxy. Diffuse extended Hi emission seen.

ID39: Host is a faint blue galaxy. Diffuse extended Hi emission seen.

ID40: Host is a rather faint edge-on galaxy. Extended Hi emission to the south
with a hole seen.

ID41: Faint optical host identified with log10($M_{*}$) = 9.60 M⊙.

ID42: Host is an edge-on blue galaxy. Extended Hi emission to the south.

ID43: Host is a faint blue galaxy. Interacting with ID49.

ID44: Host is a small but bright galaxy. Hi poor, but also potentially
identified as an OH megamaser. Optical spectroscopic redshift data is required
to verify the emission type. Small radio continuum point source seen with flux
density $S_{\rm 1362~{}MHz}$ = 1.2 mJy.

ID45: Host is a compact galaxy. Small radio continuum point source seen with
flux density $S_{\rm 1362~{}MHz}$ = 0.4 mJy.

ID46: A higher redshift detection ($z_{\rm HI}$ = 0.08740). Host is a blue
galaxy. Small radio continuum point source seen with flux density $S_{\rm
1362~{}MHz}$ = 0.1 mJy.

ID47: A higher redshift detection ($z_{\rm HI}$ = 0.08674). Host is a blue
galaxy. Disturbed and diffuse Hi seen.

ID48: A lower redshift detection ($z_{\rm HI}$ = 0.01938). Host is a blue
galaxy.

ID49: A faint blue galaxy is identified as the host. Seen to be interacting
with ID44. Disturbed gas kinematics.

Figure 11: SIP outputs for galaxy IDs 1 and 2, as in Fig. 1. Contours are
overlaid on either DECaLS DR10 or PanSTARRS three-colour images. These two
galaxies are interacting with ID3. Images created via SIP.

Figure 12: Continued. SIP outputs for galaxy IDs 3 and 4. ID3 is interacting
with ID 1 and 2.

Figure 13: Continued. SIP outputs for galaxy IDs 5 and 6.

Figure 14: Continued. SIP outputs for galaxy IDs 7 and 8.

Figure 15: Continued. SIP outputs for galaxy IDs 9 and 10.

Figure 16: Continued. SIP outputs for galaxy IDs 11 and 12.

Figure 17: Continued. SIP outputs for galaxy IDs 13 and 14.

Figure 18: Continued. SIP outputs for galaxy IDs 15 and 16.

Figure 19: Continued. SIP outputs for galaxy IDs 17 and 18.

Figure 20: Continued. SIP outputs for galaxy IDs 19 and 20.

Figure 21: Continued. SIP outputs for galaxy IDs 21 and 22.

Figure 22: Continued. SIP outputs for galaxy IDs 24 and 25.

Figure 23: Continued. SIP outputs for galaxy IDs 26 and 27.

Figure 24: Continued. SIP outputs for galaxy IDs 28 and 29.

Figure 25: Continued. SIP outputs for galaxy IDs 30 and 31.

Figure 26: Continued. SIP outputs for galaxy IDs 32 and 33.

Figure 27: Continued. SIP outputs for galaxy IDs 35 and 36.

Figure 28: Continued. SIP outputs for galaxy IDs 37 and 38.

Figure 29: Continued. SIP outputs for galaxy IDs 39 and 40.

Figure 30: Continued. SIP outputs for galaxy IDs 41 and 42.

Figure 31: Continued. SIP outputs for galaxy IDs 43 and 44. Note ID43 is
interacting with ID49 (see final set of plots for this figure).

Figure 32: Continued. SIP outputs for galaxy IDs 45 and 46.

Figure 33: Continued. SIP outputs for galaxy IDs 47 and 48.

Figure 34: Continued. SIP outputs for galaxy IDs 49, and for both ID 43 and 49
in the bottom set. Figure 35: Continued. SIP outputs for both galaxy IDs 16
and 17, which are near each other. Figure 36: Output from BBarolo for the
channel-by-channel model fit to the Hi spectral line cube for ID18. Figure 37:
Output from BBarolo for the moment maps for the model fit to the Hi spectral
line cube for ID18. Figure 38: As in Fig. 10 for ID8 (top two panels). Figure
39: As in Fig. 10 for ID10. Figure 40: As in Fig. 10 for ID19. Figure 41: As
in Fig. 10 for ID24.

Figure 42: As in Fig. 10 for ID48, with the fitting results included without
the two additional points (bottom two panels). Here we see a more realistic
Polyex fit and corresponding ISO fit when including the two additional points.