# The Quenched Satellite Population Around Milky Way Analogs

Ananthan Karunakaran${}^{1\,\href https://orcid.org/0000-0001-8855-3635}$ ,
David J. Sand${}^{2\,\href https://orcid.org/0000-0003-4102-380X}$, Michael G.
Jones${}^{2\,\href https://orcid.org/0000-0002-5434-4904}$, Kristine
Spekkens${}^{3,4\,\href https://orcid.org/0000-0002-0956-7949}$, Paul
Bennet${}^{5\,\href https://orcid.org/0000-0001-8354-7279}$, Denija
Crnojević${}^{6\,\href https://orcid.org/0000-0002-1763-4128}$, Burç˙ın Mutlu-
Pakd˙ıl${}^{7\,\href https://orcid.org/0000-0001-9649-4815}$, Dennis
Zaritsky${}^{2\,\href https://orcid.org/0000-0002-5177-727X}$
1Instituto de Astrofísica de Andalucía (CSIC), Glorieta de la Astronomía,
18008 Granada, Spain
2Steward Observatory, University of Arizona, 933 North Cherry Avenue, Rm.
N204, Tucson, AZ 85721-0065, USA
3Department of Physics and Space Science, Royal Military College of Canada
P.O. Box 17000, Station Forces Kingston, ON K7K 7B4, Canada
4Department of Physics, Engineering Physics and Astronomy, Queen’s University,
Kingston, ON K7L 3N6, Canada
5Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
21218, USA
6University of Tampa, 401 West Kennedy Boulevard, Tampa, FL 33606, USA
7Department of Physics and Astronomy, Dartmouth College, Hanover, NH 03755,
USA
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We study the relative fractions of quenched and star-forming satellite
galaxies in the Satellites Around Galactic Analogs (SAGA) survey and
Exploration of Local VolumE Satellites (ELVES) program, two nearby and
complementary samples of Milky Way-like galaxies that take different
approaches to identify faint satellite galaxy populations. We cross-check and
validate sample cuts and selection criteria, as well as explore the effects of
different star-formation definitions when determining the quenched satellite
fraction of Milky Way analogs. We find the mean ELVES quenched fraction
($\langle QF\rangle$), derived using a specific star formation rate (sSFR)
threshold, decreases from $\sim$50% to $\sim$27% after applying a cut in
absolute magnitude to match that of the SAGA survey ($\langle
QF\rangle_{SAGA}\sim$9%). We show these results are consistent for alternative
star-formation definitions. Furthermore, these quenched fractions remain
virtually unchanged after applying an additional cut in surface brightness.
Using a consistently-derived sSFR and absolute magnitude limit for both
samples, we show that the quenched fraction and the cumulative number of
satellites in the ELVES and SAGA samples broadly agree. We briefly explore
radial trends in the ELVES and SAGA samples, finding general agreement in the
number of star-forming satellites per host as a function of radius. Despite
the broad agreement between the ELVES and SAGA samples, some tension remains
with these quenched fractions in comparison to the Local Group and simulations
of Milky Way analogs.

###### keywords:

galaxies: dwarf – galaxies: evolution – (galaxies:) Local Group – radio lines:
galaxies

††pubyear: 2022††pagerange: The Quenched Satellite Population Around Milky Way
Analogs–9

##  1 Introduction

Dwarf galaxies play a crucial role in verifying and refining our model of
galaxy formation and evolution in the $\Lambda$CDM framework (e.g. Bullock &
Boylan-Kolchin, 2017). The Local Group (LG) has long been the foremost
laboratory for studies of dwarf galaxies, including the satellites of the two
massive hosts, the Milky Way (MW) and M31, as well as those in the periphery
beyond the immediate influence of these massive systems. While the LG affords
the opportunity to study some of the faintest systems, it is only one system.
In order to have a statistical understanding of the interplay between MW-like
hosts and their satellites, we must expand studies beyond the LG. Work in this
respect is underway.

One focus is on how the environment of dwarfs impacts their neutral hydrogen
(HI) gas reservoirs and their star formation. The vast majority of LG
satellites within the virial radius of their host are gas-poor and those
beyond it are typically gas-rich (Spekkens et al., 2014; Putman et al., 2021).
Similarly, the quenched fraction of LG satellites rapidly increases as stellar
mass decreases (Wetzel et al., 2015). These works suggest an environmental and
mass dependence on the quenching mechanisms of dwarf satellite galaxies.
Higher-mass satellites are thought to be less susceptible to the effects of
their hosts and hold on to their HI reservoirs, allowing them to continue
forming stars throughout their evolution (e.g. Simpson et al., 2018; Garrison-
Kimmel et al., 2019). On the other hand, the weaker gravitational potentials
of lower-mass satellites make them more susceptible to both internal (i.e.
star-formation feedback) and external (i.e. ram-pressure and tidal stripping)
processes. At the lowest stellar masses, ultra-faint dwarfs may have been
quenched via reionization regardless of their environment (Bullock et al.,
2000; Brown et al., 2014; Jeon et al., 2017; Applebaum et al., 2021; Sand et
al., 2022). Combining these results from observations with modern
hydrodynamical simulations provides useful insight into the evolutionary
processes that occur at the smallest mass scales.

There has been general consistency between observations of the LG and recent
simulations of LG and MW-like systems (e.g. Fattahi et al., 2016; Sawala et
al., 2016; Wetzel et al., 2016; Simpson et al., 2018; Garrison-Kimmel et al.,
2019; Libeskind et al., 2020; Engler et al., 2021; Font et al., 2021;
Applebaum et al., 2021; Akins et al., 2021; Samuel et al., 2022), including
investigations into the mass and time scales for satellite quenching. However,
there still exist some tensions as we begin to explore larger samples of
satellite systems beyond the LG (Sales et al., 2022). One such tension is the
contrast between both the quenched fractions of the LG and simulations of LG-
and MW-like systems with those in the Satellites Around Galactic Analogs
survey (SAGA; Geha et al., 2017; Mao et al., 2021).

The SAGA survey aims to identify, spectroscopically confirm, and characterize
the satellite population of nearby MW-like hosts down to satellites as faint
as Leo I ($M_{r}=-12.3$ mag). The H$\alpha$ emission from the single-fibre
spectroscopic follow-up of the SAGA satellites was used to characterize them
as quenched or star-forming with the vast majority falling into the latter
category. Even so, these single-fibre spectroscopic observations may have
underestimated the number of star-forming satellites, which motivated
Karunakaran et al. (2021) to use archival GALEX UV imaging as an alternative
spatially resolved star-formation tracer. Their findings increased the
fraction of star-forming satellites in the second stage release of the SAGA
survey (hereafter, SAGA–II; Mao et al. 2021) from $\sim$85% to $\sim$95%. In
addition to this re-characterization of the star-forming nature of these
systems, they provided a comparison of the fraction and number of quenched
satellites in the APOSTLE (A Project Of Simulating The Local Environment;
Fattahi et al., 2016; Sawala et al., 2016) and Auriga (Simpson et al., 2018)
hydrodynamical simulation suites. This comparison used similar host sample
sizes and applied similar stellar mass cuts to demonstrate a potential tension
between the surplus of star-forming satellites in observations and the
relative dearth in simulations (see also Simpson et al. 2018; Akins et al.
2021), even when incompleteness corrections are accounted for.

Given that many simulations use the Local Group as a useful benchmark, it is
interesting to ask: Are the Local Group and its quenched fraction typical?
Also, extending the study of satellite systems and their quenched fraction to
lower luminosities and masses than SAGA–II is an essential next step for
understanding what drives the evolution of the smallest galaxies. These lower-
mass galaxies are even more susceptible to the environmental effects of their
hosts. Understanding whether the trends we see in the lower mass regime within
the Local Group are present beyond it can help constrain whether or not the
Local Group is typical.

This tension in the quenched fraction between SAGA–II and both the LG and
simulations may lend some credence to the latter two being less representative
of the broader MW-like population. However, Font et al. (2022) have presented
a potential solution to this tension. By applying the SAGA–II absolute
magnitude cut to the satellites around MW-like hosts in the ARTEMIS (Assembly
of high-ResoluTion Eagle-simulations of MIlky Way-type galaxieS) simulation
suite (Font et al., 2020), they showed that the quenched fraction can be
decreased from $\sim 95\%$ to $\sim 75\%$, in their lowest stellar mass bin,
$\mathrm{log}(M_{*}/M_{\odot})\sim 6.8$. However, in their earlier work they
had estimated a by-eye surface brightness limit for the SAGA–II survey of
$\mu_{\mathrm{eff},r}\sim 25\mathrm{mag\,arcsec^{-2}}$ (Font et al., 2021).
This estimate is consistent with the empirical completeness limit derived by
Kado-Fong et al. (2021) for the Dark Energy Survey low surface brightness
(LSB) catalog (Tanoglidis et al., 2021). Mao et al. (2021) had used the Dark
Energy Survey LSB catalog to cross-match with their photometric catalog to
demonstrate that they are not missing any LSB satellite candidates. Therefore,
the agreement between the limits from Font et al. (2021) and Kado-Fong et al.
(2021) suggests that the SAGA–II photometric catalogs may be missing LSB
satellite candidates. Combining this proposed surface brightness limit, in
addition to an absolute magnitude limit, Font et al. (2022) found a
significant, $\sim$50%, reduction in the quenched fraction in their lowest
stellar mass bin relative to the total ARTEMIS satellite sample. This by-eye
surface brightness limit is a potentially useful metric to investigate further
with other simulated and observational samples, particularly those that are
complete towards lower surface brightness (e.g. Zaritsky et al., 2022).

There have been a plethora of observational efforts to characterize the
satellite populations in the nearby Universe (e.g. Chiboucas et al., 2009,
2013; Merritt et al., 2014; Sand et al., 2014; Karachentsev et al., 2015; Sand
et al., 2015; Carlin et al., 2016; Crnojević et al., 2016; Javanmardi et al.,
2016; Bennet et al., 2017; Müller et al., 2017; Smercina et al., 2018; Bennet
et al., 2019; Carlsten et al., 2019a; Crnojević et al., 2019; Bennet et al.,
2020; Mutlu-Pakdil et al., 2021, 2022; Bell et al., 2022). A complementary
survey to SAGA–II in the Local Volume is the Exploration of the Local VolumE
Satellites (ELVES) survey (Carlsten et al., 2022). This survey of nearby
($<12$ Mpc) massive hosts builds upon earlier work within the Local Volume. An
advantage of the ELVES survey is its ability to reach fainter systems and
estimate robust surface brightness completeness limits as a result of
performing their own photometry. On the other hand, their confirmation efforts
via surface brightness fluctuation-based distance measurements are susceptible
to systematic effects and may be less robust relative to the SAGA–II
spectroscopic follow-up. For instance, some satellite candidates from ELVES
have been shown to be at different distances than that inferred from surface
brightness fluctuations (e.g. Karunakaran et al., 2020, 2022). Irrespective of
these differences, having another survey to compare to the LG is critical.
Carlsten et al. (2022) find broad agreement with the observed quenched
fractions in the LG and do not agree with the low quenched fractions from the
SAGA–II satellites even when incompleteness corrections are taken into
account. The ELVES sample provides an interesting opportunity to study the
quenched fraction and number of satellites down to $M_{V}\sim-9$. Its
relatively high completeness also allows us to test the effect of the SAGA
absolute magnitude cut (i.e. $M_{r}=-12.3$) as well as surface brightness
effects.

In this paper, we investigate the number of star-forming satellites and
quenched fractions in the ELVES and SAGA–II satellite samples and explore the
role different selection criteria (e.g. magnitude and surface brightness
limits) play in measuring these quantities. We hope to better understand the
Local Group in the broader context of satellite systems as well as whether or
not the larger statistical SAGA–II sample suffers from systematic biases that
prevent drawing definitive conclusions about satellite populations beyond the
Local Group. In Section 2, we provide an overview of the SAGA–II and ELVES
satellite samples. We describe two different criteria for selecting ‘star-
forming’ dwarfs in Section 3 and then move on to discuss the various selection
effects that we explore in Section 4. We briefly summarize the implication of
our results in Section 5.

##  2 Satellite Samples

###  2.1 The Satellites Around Galactic Analogs (SAGA) Survey

The SAGA–II sample (Mao et al., 2021, hereafter, M21) consists of 127
satellites around 36 nearby (25-40 Mpc) Milky Way-like systems. The primary
selection criteria of these hosts is their $K$-band luminosity
$(-23>M_{K}>-24.6)$. The halo masses of these systems
$(M_{halo}\sim(0.7-2)\times 10^{12}M_{\odot})$ were estimated to also cover
the halo mass range encapsulating the MW’s halo mass (M21, see also Nadler et
al., 2020). Most host systems are in relative isolation (i.e. field-like
environments), while a few are analogs of the LG (see M21 for details).

The satellites in SAGA–II were initially selected from imaging catalogs (i.e.
Legacy Survey, SDSS, and DES). Satellite candidates without extant redshift
measurements were observed through various optical spectroscopic campaigns.
Overall, 80% of satellite candidates with $M_{r}\leq-12.3$ (assuming the
host’s distance) were spectroscopically targeted. The entire SAGA–II sample
contains a total of 127 satellites that project within 300 kpc with a
recessional velocity within $275\,{\mathrm{km\,s^{-1}}}$ of their putative
host. To avoid high levels of background light, only satellites beyond 15 kpc
are selected for spectroscopic follow-up (Carlsten et al., 2022) and we adopt
this distance throughout this work. Furthermore, there are four satellites
that fall below the aforementioned SAGA–II absolute magnitude limit. While we
include these four satellites in our analysis, we note that the results
presented here remain unchanged if they were to be removed.

As previously mentioned, a large number of satellites in SAGA–II are actively
star-forming as determined by their H$\alpha$ measurements. In a subsequent
study, Karunakaran et al. (2021) presented UV measurements leveraging the
spatial coverage of archival GALEX imaging to show that an even larger number
of the SAGA–II satellites have undergone recent star formation. The apparent
dearth of quenched satellites in these systems, relative to the Local Group,
points toward potential survey incompleteness. Alternatively, the larger
SAGA–II sample may be more representative of Milky Way-mass systems, making
the Local Group an outlier.

In order to characterize their survey incompleteness and potential interloper
fraction, M21 perform extensive modeling of their confirmed and unconfirmed
targets in conjunction with mock sample selection from dark matter-only
simulations. In particular, they provide incompleteness/interloper-corrected
quenched fraction estimates based on the detection of H$\alpha$, which we
adopt here. These corrections assume that all of the potential satellites that
were missed in the SAGA–II spectroscopic follow-up are quenched.

We adopt the photometric and derived properties (e.g. magnitudes, surface
brightness, stellar masses, etc.) from SAGA–II. We adopt the UV-derived star-
forming quantities from Karunakaran et al. (2021) for the SAGA–II sample. The
spatial coverage of the GALEX UV imaging ensures that we capture any star
formation-related emission across these satellites which may be missed by the
smaller optical fibers.

###  2.2 The Exploration of Local VolumE Satellites (ELVES) Survey

The ELVES survey (Carlsten et al., 2022, hereafter, C22) builds upon earlier
surveys of Local Volume (D$<$12 Mpc) systems, primarily that of Carlsten et
al. (2020). The ELVES sample consists of 31 Local Volume hosts whose primary
selection criteria is their $K-$band luminosity, $M_{K}<-22.1$. The satellites
around all hosts have been cataloged within 150 kpc, however, most have been
surveyed within 300 kpc. It should be noted that the satellite systems for 5
ELVES hosts (MW, M31, Cen A, NGC5236, and M81) are taken from the literature
(McConnachie, 2012; Chiboucas et al., 2013; Müller et al., 2015, 2017, 2018;
Crnojević et al., 2019).

The ELVES survey uses a combination of archival CFHT/MegaCam (i.e. Carlsten et
al., 2020) and DECaLS imaging primarily for source detection. The confirmation
of the association of these satellites is through surface brightness
fluctuation (SBF) distance estimates. The SBF method, tuned for LSB dwarfs
(e.g. Carlsten et al., 2019b), is employed on deeper Hyper Suprime-Cam,
Gemini, and Magellan imaging. We note that there may always be cases where the
SBF method faces difficulty, particularly for faint blue, clumpy/irregular
(i.e. star-forming) systems (e.g. Carlsten et al., 2019b; Greco et al., 2021;
Karunakaran et al., 2020, 2022). These SBF distances are used to classify a
satellite as “confirmed”, “background”, or “unconfirmed/candidate”. The total
ELVES sample consists of 338 confirmed satellites across 30 hosts111The lone
host yet to be analyzed is NGC3621 and 106 additional satellite candidates
with forthcoming distance estimates. While these additional satellites will
eventually provide useful statistical confidence, we only include “confirmed”
satellites in this work.

Due to the excellent quality of the data, the ELVES sample is capable of
reaching faint satellite luminosities. Through robust artificial galaxy
injection and recovery simulations, C22 determined the ELVES sample is
complete down to $M_{V}\sim-9$ and $\mu_{0,V}\sim
26.5\,\mathrm{mag\,arcsec^{-2}}$. In addition to deriving these completeness
limits, C22 perform analogous modeling to M21 to determine how many of the 106
satellite candidates without distances are real satellites, finding that as
many as $\sim 50$ out of 106 may be real.

Another crucial difference between the ELVES and SAGA–II surveys is their
survey coverage. While all of the SAGA–II systems have photometric catalogs
within a projected 300 kpc radius of their hosts, 21 out of 30 ELVES hosts
have coverage out to this projected radius with the remaining having coverage
to at least 150 kpc. As mentioned above, we only consider ELVES satellites
that project beyond the minimum SAGA–II separation of 15 kpc, removing 6 out
of 338 confirmed satellites.

We adopt all of the photometric properties, physical quantities, and
classifications derived for the hosts and satellites in the ELVES sample. We
compute $r-$band ($i-$band) apparent magnitudes of any ELVES satellite with
only $g-$ and $i-$band ($r-$band) photometry using the relations of Carlsten
et al. (2021) in order to conduct seamless comparisons to SAGA–II satellites.
Additionally, C22 present UV photometry for 271 satellites with available
GALEX imaging. We also adopt these UV measurements and derive any distance-
dependent quantities (i.e. star-formation rates) assuming a satellite’s host
distance.

##  3 Identifying Quenched and Star-forming Satellites

Classifying a galaxy as quenched or star-forming can be done through a variety
of methods. Here, we outline two possible methods of separating quenched and
star-forming satellites in the ELVES and SAGA-II samples and use these as our
star-forming definitions.

The first method is a photometric selection established by Carlsten et al.
(2021) where they separated quenched, early-type galaxies (ETGs) and star-
forming, late-type galaxies (LTGs) with the relation $g-i=-0.067\times
M_{V}-0.23$ in the colour–absolute $V-$band magnitude plane. We use this
relation for both the ELVES and SAGA–II samples in Section 4 to separate
quenched and star-forming satellites. We convert any $g-r$ colours to $g-i$
using the conversion provided in Carlsten et al. (2021).

Figure 1: A comparison of SFR (top) and sSFR (bottom) as a function of stellar
mass for the ELVES (green) and SAGA-II (orange) satellite samples. The ELVES
sample shown in this figure includes only satellites with available GALEX UV
data and with MW-like or less massive hosts (see Section 4 for more detail).
Satellites that are detected in UV and have
log(sSFR$[\mathrm{yr^{-1}}]$)$\geq-11$ are star-forming and shown as stars.
Quenched (indicated as Q in the legend) satellites that are detected in UV but
do not meet the aforementioned sSFR threshold are shown as open circles, while
those that are not detected in UV are upper limits and shown as filled circles
with downward arrows. The dotted line in both panels show a constant
log(sSFR$[\mathrm{yr^{-1}}]$)$=-11$.

The second method is via UV emission, particularly the specific star formation
rate (sSFR), indicating relatively recent (i.e. $\sim 200$ Myr) star
formation. We use here the NUV photometry derived for the SAGA–II sample from
Karunakaran et al. (2021) and for the ELVES sample from C22. Karunakaran et
al. (2021) used a simple star-forming criterion, i.e. $(S/N)_{NUV}>2$, for the
SAGA–II satellites and they found a high correspondence of satellites with
both H$\alpha$ and NUV emission. While this simple definition may suffice for
more distant star-forming systems, NUV imaging of more nearby quenched systems
may be sensitive to NUV emission from relatively older stellar populations
(Lee et al., 2009).

To circumvent this potential bias, we derive NUV star-formation rates using
the SFR relation from Iglesias-Páramo et al. (2006). These SFRs have not been
corrected for internal infrared extinction which is likely significant for
more massive satellites and likely negligible for low-mass ones (McQuinn et
al., 2015). We then determine an sSFR by taking the ratio of the NUV-derived
SFRs and stellar masses from the ELVES and SAGA–II sample catalogs. In Figure
1, we show these derived quantities as a function of stellar mass for both the
ELVES (green) and SAGA–II (orange) samples222As noted in Karunakaran et al.
(2021), LS-330948-4542, the lowest mass SAGA–II satellite
($\mathrm{log}(M_{*}/M_{\odot})\sim 5.6$), appears to have a size that is
severely underestimated in the SAGA–II catalog which leads to a subsequent
erroneous calculation of its stellar mass. Nonetheless, we make no attempt to
correct the reported properties of this object in the current study..
Satellites that are detected in UV and with $\mathrm{log}(sSFR)\geq-11$ are
considered star-forming, while those that fall below this limit or are
undetected, i.e. $(S/N)_{NUV}<2$, in NUV are quenched. Quenched satellites are
shown as circles and those that are NUV non-detections have downward arrows,
while star-forming satellites are represented by stars. The ELVES sample
probes lower stellar masses and most of these lower mass satellites are
classified as quenched.

We note that there are minor differences in the ELVES satellite sample sizes
as only a subset (271/338) have available UV imaging. Furthermore, in cases
where ELVES photometry is missing in a particular band, we assume the average
$g-r$ or $g-i$ colour of the sample to determine the required quantity. Three
relatively bright ELVES satellites (NGC4656, NGC247, IC239) and the Milky Way
satellites included in ELVES have neither $g,\,r,\,i\,$ nor UV photometry. We
substitute their morphological classifications (i.e. ETG to quenched and LTG
to star-forming) in our comparisons given that the more luminous systems and
the Milky Way satellites are typically less ambiguous in terms of their state
of star formation.

##  4 Selection Effects on the Quenched Satellite Population

###  4.1 Host and Photometric Selection Criteria

There are clear differences in the host and satellite properties between the
ELVES and SAGA-II samples. We briefly describe selection criteria in order to
have a fair comparison of these two samples.

We first address the differences in hosts. As noted by C22, there are several
host galaxies in the ELVES sample that would not meet the SAGA–II host
criteria: luminosity (i.e. $M_{K}<-24.6$), isolation (i.e. nearby bright
companion), and/or halo mass (i.e.
$M_{\mathrm{halo,group}}<10^{13}M_{\odot}$). We remove eight hosts (M104, M31,
NGC 1808, NGC 5194, NGC 3379, M81, Cen A, and NGC 3627) listed in C22 that
fail any of these criteria, see their Section 7.1 for more details. In
addition to the aforementioned eight hosts, we find the inclusion or exclusion
of six ELVES hosts (NGC 628, NGC 3344, NGC 3556, NGC 4517, NGC 4631, and NGC
4736) that fall below the SAGA–II $M_{K}$ limit (i.e. $M_{K}>-23$) make
marginal changes to our results. Similar to the conclusions of C22, we opt to
keep these systems for the purpose of sample size.

We now turn to a couple of photometric selection criteria that can affect the
comparison between these two samples. The first is the absolute magnitude
limit of the SAGA–II sample, $M_{r}\leq-12.3$, which will apply to the ELVES
sample as well. We note that there are other photometric cuts applied within
the SAGA–II survey with respect to spectroscopic follow-up and discuss their
relevance below. The second photometric criterion we consider in addition to
the $M_{r}$ cut is a surface brightness cut of
$\mu_{\mathrm{eff},r}<25\,\mathrm{mag\,arcsec^{-2}}$. This selection cut was
recently suggested by Font et al. (2022) to reconcile differences between the
SAGA–II sample and hydrodynamical simulations. Here, we apply a similar cut in
surface brightness to see its resulting effects on the number and fraction of
quenched satellites in the ELVES sample.

We compute the mean surface brightness values for the ELVES sample in the same
manner as SAGA–II (see their Eq. 2) by using the previously computed $r-$band
magnitudes (see Section 2) and determining the apparent effective radii using
the physical radii and host distances tabulated in C22. For the Milky Way
satellites with only $V-$band photometry, we approximate their mean $r-$band
surface brightness values assuming $V-r\sim 0.4$ (Crnojević et al., 2019) and
an exponential light profile to move from central to effective values,
$\mu_{\mathrm{eff}}-\mu_{0}\sim 1.123$ (Font et al., 2022, see also Graham &
Driver 2005). Given the various selection criteria described and the different
star-forming definitions, we have provided a summary of the number of
satellites that remain after each cut in Table 1.

Table 1: Breakdown of the total number, N, of ELVES Satellites and mean quenched fractions, $\langle$QF$\rangle$, for each Selection Criteria and Star-forming Definition. In addition, we list these values when only considering satellites that project within 150 kpc ($\mathrm{N_{150}}$ and $\langle$QF$\rangle_{150}$). The SAGA–II values are listed at the bottom for reference. Selection | Colour-Magnitude | UV+sSFR
---|---|---
Criteria | N |  $\langle$QF$\rangle$ | $\mathrm{N}_{150}$ |  $\langle$QF$\rangle_{150}$ | N |  $\langle$QF$\rangle$ | $\mathrm{N}_{150}$ |  $\langle$QF$\rangle_{150}$
Total | 338 | 72% | 214 | 75% | 271 | 58% | 183 | 62%
ELVES-H | 181 | 66% | 121 | 70% | 168 | 50% | 113 | 55%
ELVES-M | 98 | 37% | 65 | 42% | 89 | 27% | 59 | 28%
ELVES-SB | 82 | 34% | 54 | 39% | 75 | 27% | 49 | 30%
SAGA–II | 127 | 11% | 72 | 16% | 127 | 9% | 72 | 15%

In Figure 2, we show a comparison of three essential photometric properties of
these satellites: $r-$band apparent magnitude, surface brightness
($\mu_{\mathrm{eff},r}$), and colour ($g-r$). The total ELVES confirmed
satellite sample with none of the above cuts is represented by the contours in
each of these planes. The compounding selection cuts on the ELVES sample are
shown in different colours: the host cut is shown in green (ELVES-H), the
host+SAGA–II absolute magnitude cut in blue (ELVES-M), and the host+SAGA–II
absolute magnitude+surface brightness cut in red (ELVES-SB). It should be
noted that since these cuts are compounding, the sub-samples are included in
their parent sample, i.e. all red symbols are included in the same sample as
the blue and green symbols.

We can see from this figure that there is a clear separation between the ELVES
sample with only the host cut (green+blue+red) and the two sub-samples (blue
and red). For reference, we also include the relations from M21 that are used
to define the primary targeting region for their spectroscopic follow-up (see
their Eqs. 3a and 3b) as dotted lines in the upper- and lower-left panels. In
the upper-left panel, a small number of satellites do not satisfy the colour-
magnitude relation (diagonal dotted line) that SAGA–II uses to target
candidates spectroscopically. Since these satellites do not satisfy the
SAGA–II absolute magnitude cut, they will not skew our comparisons to the
SAGA–II sample. In the surface brightness-magnitude plane, all ELVES
satellites would qualify for spectroscopic follow-up as they lie above the
SAGA–II relation. The minimum angular size imposed on ELVES sources (circular
radius $\sim 4^{\prime\prime}$) is also clear relative to the SAGA–II sample,
however, this should have minimal impact on the interpretation given the
difference in distances to systems in each survey. The star-forming
populations in both the ELVES-SB and SAGA–II samples reside in similar
photometric parameter space. While there exist some high surface brightness,
bright ELVES satellites that are analogs to those in the SAGA–II sample, they
are members of host systems that do not satisfy the host criteria.

Compared within the ELVES sample, the vast majority of satellites that are
removed by the SAGA–II absolute magnitude cut alone are quenched, faint,
relatively red, and fall towards fainter effective surface brightness. We can
also see that there is only a marginal difference between the ELVES-M and
ELVES-SB sub-samples. In this case, the absolute magnitude cut effectively
removes the LSB satellites and negates any effect from the surface brightness
cut. We explore the implications of this in the following subsection.

Figure 2: A comparison of the apparent photometric properties of the ELVES and
SAGA-II samples. g–r vs r–band apparent magnitude (top-left), mean r–band
surface brightness at the effective radius ($\mu_{\mathrm{eff},r}$) vs r–band
apparent magnitude (bottom-left), and $\mu_{\mathrm{eff},r}$ vs g–r (bottom-
right). The ELVES sample is subdivided by the various observational selection
criteria as detailed in Section 4 and summarized in Table 1. For reference,
the contours show the KDE distribution of all satellites classified as
“Confirmed” in the ELVES sample. The SAGA–II sample is shown in orange.
Additionally, we include the relations defining the “primary spectroscopic
targeting regions” from the SAGA–II survey in the top- and bottom-left panels
as the diagonal dotted lines. The quenched and star-forming definitions are
defined as in Fig. 1.

###  4.2 Quenched Fractions and Satellite Counts

With both the quenched/star-forming definitions and selection effects
established above, we explore their effects on the quenched fractions and the
number of satellites per host in the ELVES and SAGA–II satellites samples. We
first consider all ELVES hosts that meet the aforementioned host criteria and
then shift our focus to the inner 150 kpc, the maximum radius out to which all
ELVES hosts have been completely surveyed. In addition to this latter point,
we briefly explore the quenched fractions and satellite counts as a function
of radius.

In Figure 3, we show the ELVES and SAGA–II quenched fractions as a function of
satellite stellar mass. Each panel uses one of the quenched/star-forming
definitions established in Section 3. The binning of the SAGA–II, ELVES-M, and
ELVES-SB samples attempts to follow the original binning in Mao et al. (2021)
in the same manner as in Karunakaran et al. (2021). Since the ELVES-H sample
spans the widest range in stellar mass, we have binned this sample to roughly
equate the number of total satellites (i.e. the denominator of the quenched
fraction) in each stellar mass bin. In the left panel, we use the colour-
magnitude relation from Carlsten et al. (2021) to separate quenched and star-
forming satellites for both satellite samples. The right panel employs the NUV
detection and sSFR threshold to distinguish star-forming and quenched
satellites, again, for both samples. Within each of these panels, we compute
the quenched fractions after applying the three compounding selection criteria
described above and follow the same colour scheme as in Figure 2. The shaded
regions (ELVES) and error bars (SAGA–II) are the 68% confidence intervals
computed using the Wilson score interval (Brown et al., 2001). The extended
lighter-coloured bars from the SAGA–II quenched fractions show the
incompleteness/interloper corrections estimated by Mao et al. (2021). The
dash-dotted and dotted lines, respectively, show the SAGA–II stellar masses at
which 80% and 100% of satellites have been targetted
spectroscopically333Following Karunakaran et al. (2021), we convert the
$M_{r}=-12.3$ and $M_{r}=-15.5$ limits to $M_{*}$ using the stellar mass
conversion relation from Mao et al. (2021) and the average SAGA–II colour,
$g-r\sim 0.39$..

Figure 3: Satellite quenched fraction as a function of stellar mass. The ELVES
sample is separated into different subsets by colour in order to highlight the
effect of compounding selection criteria (see Section 4 and Table 1). The
definition of a quenched satellite is different in each panel: left–quenched
and star-forming satellites are divided by a relation in the (g-i)–MV plane,
right–quenched satellites in both samples are either NUV non-detections or
their $\mathrm{log(sSFR)}<-11$. The shaded regions and error bars show the 68%
confidence intervals and the extended bars from the symbols show the
confidence intervals plus the incompleteness/interloper corrections. The
vertical dash-dotted and dotted lines show the SAGA–II 80% and 100%
spectroscopic coverage limits.

In the left panel, we can see that the application of these additional
selection criteria (ELVES-M and ELVES-SB) does marginally decrease the
estimated quenched fractions and bring them into better agreement with the
SAGA–II sample. Shifting to the right panel, which shows the UV+sSFR-based
quenched/star-forming classification, we see a decrease in the ELVES quenched
fractions below $\mathrm{log}(M_{*}/M_{\odot})\sim 8$. This shift brings the
ELVES sample into stronger agreement with the SAGA–II than the colour-
magnitude (or morphology) definition(s). Although the partial UV coverage for
the ELVES sample does affect the number of satellites in each subset, there
are only marginal ($<10\%$) differences between the ELVES-M and ELVES-SB in
either of the quenched/star-forming panels. It is interesting to note the
general agreement between the ELVES-H and SAGA–II sample in the right panel,
particularly in the $\mathrm{log}(M_{*}/M_{\odot})\sim 6.8$ bin. While the
additional selection criteria (ELVES-M and ELVES-SB) have an effect on the
quenched fraction, this agreement between the ELVES-H and SAGA–II values may
also stem from several compounding factors such as the aforementioned UV
coverage, choice of binning, inclusion of lower mass hosts, etc. We note that
the spike in the quenched fraction in the $\mathrm{log}(M_{*}/M_{\odot})\sim
8$ bin is a result of adopting the SAGA–II stellar mass bins. Nevertheless, we
adopt this latter star-forming definition as our preferred definition as it is
physically motivated (i.e. sensitive to significant recent star-formation) and
it is widely adopted in both observations (e.g. Karachentsev & Kaisina, 2013;
Wetzel et al., 2013) and simulations (e.g. Pallero et al., 2019; Akins et al.,
2021; Joshi et al., 2021). We provide the mean quenched fractions,
$\langle$QF$\rangle$, for each of these selection criteria and star-forming
definitions in Table 1.

In both of the panels in Figure 3, we can see the minimal difference the
additional surface brightness criterion (ELVES-M vs ELVES-SB) makes to the
resulting quenched fractions. To better understand this, we investigate the
number counts of satellites in the ELVES and SAGA–II samples. Figure 4 shows
the cumulative number of the star-forming (open and filled histograms) and
total (i.e. star-forming+quenched; filled circles) satellites per host as a
function of stellar mass. Both panels show the same quenched/star-forming
classification methods as in Figure 3. The tight correspondence between the
star-forming and the total number of SAGA–II satellites hint at a potential
dearth of quenched satellites. It is evident that the bulk of the SAGA–II
satellites build up at intermediate to high stellar masses. On the other hand,
the ELVES star-forming satellites more slowly increase up until the final two
stellar mass bins where the bulk of their satellite counts factor in. These
trends are seen regardless of star-forming definition and are likely a sign of
the underlying difference in the observed luminosity/mass functions of these
two satellite samples as described by C22. The broad agreement between the
cumulative number of satellites between the ELVES-M, ELVES-SB, and SAGA–II
samples is further solidified when considering various
incompleteness/interloper corrections. Mao et al. (2021) suggest that between
$6.6<\mathrm{log}(M_{*})<7.8$, $\sim 0.7$ satellites are missing per host in
their characterization of the incompleteness/interloper corrections for the
SAGA–II survey. Applying these corrections can readily explain the differences
in the cumulative number of satellites between the two surveys.

It should also be noted that there is a strong correspondence in the ELVES
sample between the colour-magnitude relation and a morphology-based
classification since the former is derived using the latter. While we do not
focus our comparisons using this morphological classification or a simple NUV
detection classification as in Karunakaran et al. (2021), we show our main
results using these methods in Appendix A.

Figure 4: Cumulative number of total (filled circles) and star-forming (open
and filled histograms) satellites for the various ELVES sample subsets in
comparison to the SAGA–II sample. The subsets are coloured as in Figures 2 and
3.

A factor that may play a role in the underlying differences in these two
samples is the non-uniform spatial coverage of the ELVES sample. As mentioned
in Section 2, all ELVES hosts are surveyed out to 150 kpc, while most are
surveyed to at least 300 kpc. We follow a similar methodology to C22 to equate
these samples and only select satellites that projected within 150 kpc of
their hosts. In Figures 5 and 6, we show the quenched fractions and the
cumulative number of satellites per host as functions of stellar mass,
respectively. We note that the SAGA–II quenched fractions in Figure 5 do not
include incompleteness/interloper corrections since they were derived for the
full survey coverage. Nevertheless, across both star-forming definitions, we
see a marginal increase in the quenched fractions, on average (see Table 1),
as well as an increase in scatter due to fewer satellites within each bin.
This general increase may have been expected based on the underlying
environmental influence on the quenching process. We can see that the total
number of SAGA–II satellites within 150 kpc is lower than the ELVES sub-
samples relative to Figure 4. This difference in satellite spatial density has
been highlighted by C22. However, if we focus on just the star-forming
satellites (open and filled histograms), we see that at intermediate stellar
masses there is a near identical number of star-forming satellites per host.
The agreement in this region should be considered significant since both
samples are sufficiently complete in this mass region.

Applying a surface brightness criterion, in addition to the SAGA–II absolute
magnitude cut ($M_{r}$$<$$-$12.3 mag), to the ELVES sample leads to marginal
differences in the quenched fraction (Figure 3) and slightly larger
differences in the cumulative number of satellites per host (Figure 4)
compared to the absolute magnitude criterion alone. Based on the more
significant decreases seen in the ARTEMIS quenched fractions $(\sim
10\%-40\%)$, it is, at first glance, curious that similar decreases are not
seen in the ELVES sample. Observationally, Figure 2 shows that the vast
majority of the LSB satellites are dropped by applying the absolute magnitude
cut alone. One implication of the minimal effect from the application of the
surface brightness criterion is that the SAGA–II photometric catalogs may not
be missing as many satellites as initially suggested by Font et al. (2021).
Instead, their photometric catalogs are relatively complete and given their
faint and/or diffuse nature, these satellites may be missed during their
spectroscopic follow-up, as explored by M21.

###  4.3 A Brief Exploration of Radial Trends

In Figure 7, we show the quenched fraction (left) and the number of satellites
per host (right) as a function of radius for the ELVES and SAGA–II samples. In
this comparison, we have restricted the ELVES hosts to those with survey
coverage out to 300 kpc. We adopt the UV+sSFR star-forming definition given
its relatively better agreement between the ELVES and SAGA–II samples. From
the left panel, we can clearly see the environmental dependence on the
quenched fraction as it decreases going from low to high projected distances
in all three ELVES sub-samples and is also present for the SAGA–II satellites.
We can also see that, as before, there is a marginal difference in the
quenched fraction radial profiles between the ELVES-M and ELVES-SB samples.
Although we do not include the SAGA–II incompleteness/interloper corrections,
the ELVES samples have, on average, higher quenched fractions across each
radial bin. However, it is clear to see that SAGA–II, ELVES-M, and ELVES-SB
samples are within reasonable agreement at larger project radii ($>150$ kpc)
despite not including the aforementioned corrections to the SAGA–II sample.

It is promising that the average values for the quenched fractions in the
ELVES sub-samples $(\sim 45\%-60\%)$ are broadly consistent with the quenched
fractions within similar radii from the Auriga (Simpson et al., 2018) and
Latte/FIRE-2 (Samuel et al., 2022) simulation suites. Interestingly, these
quenched fractions appear to reach relatively low values near the virial
radius (i.e. in the final radial bin) compared to those from these
aforementioned simulations. However, we believe that this is a result of the
different sampling and binning methods and not necessarily a bona fide
difference in the radial profiles between the observations and simulations.

We explore these differences in radial trends from a different point of view
in the right panel of Figure 7 by looking at the satellite number per host as
a function of radius. We focus this comparison on the ELVES-SB sample,
separating the total satellite count (solid red line) into star-forming
(dashed red line histogram) and quenched (dotted red line) constituents. Also,
we only include the SAGA–II star-forming satellites (filled orange histogram).
The number of quenched satellites per host in the ELVES-SB sample decreases as
a function of projected distance, while the number of star-forming satellites
generally increases. The star-forming satellites in the ELVES-SB sample hover
around $\sim 0.4$ satellites per host out to 300 kpc, while the SAGA–II ones
continue to increase up to $\sim 0.8$. This could be a result of the various
selection criteria that have been applied to the ELVES sample. Indeed, when
conducting this comparison with the colour-magnitude relation (or morphology)
as the star-forming definition, we see a minor increase in the number of star-
forming satellites per host in the larger radial bins and a similar increase
for the quenched ones at lower radii. However, these minor bin-to-bin
differences are difficult to reconcile as physical differences due to the
limited sample size considered here, particularly in the more restricted ELVES
sub-sample.

This broad consistency in the number of star-forming satellites suggests that
the apparent dearth of quenched satellites in the SAGA–II survey may not
solely stem from bias in their photometric catalogs. That is to say, the
underlying photometric catalogs may contain satellite candidates that are
difficult to spectroscopically confirm due to their faint and/or diffuse
nature, as suggested by M21. It is likely that these types of biases may be
better constrained in the complete SAGA survey with increased host and
satellite sample sizes.

Figure 5: Same as Figure 3 but only including satellites within 150 kpc of
their hosts.  Figure 6: Same as Figure 4 but only including satellites within
150 kpc of their hosts. Figure 7: Radial trends for the ELVES and SAGA–II
samples. ELVES hosts in this comparison are selected to have coverage out to
300 kpc. Left: Quenched fractions, computed using the UV+sSFR definition, as a
function of projected distance. The colour scheme is the same as in the
preceding figures (see also Table 1). A clear environmental effect on the
quenched fraction is present in all three ELVES subsets and even marginally in
the SAGA–II sample. Right: Number of satellites per host as a function of
projected distance from their host for the SAGA–II star-forming satellites and
the ELVES-SB subset. The latter is separated into total (red solid-line),
star-forming (red dashed-line), and quenched (red dotted-line) histograms.

##  5 Summary

We have presented a comparison of the quenched and star-forming satellite
population in the ELVES and SAGA–II samples. We applied cuts in host
luminosity, satellite luminosity, and satellite surface brightness to the
ELVES sample to understand their effects in our comparisons with the SAGA–II
satellites. With these different sub-samples of ELVES satellites, we compared
the quenched fraction and number of star-forming satellites between these two
surveys while also testing how different star-forming definitions can affect
these comparisons. Our primary conclusions from this work are as follows:

  * •

We find that the quenched fractions, calculated in a consistent manner using a
UV-derived sSFR, in the ELVES and SAGA–II samples are in agreement after
applying either (i) the SAGA–II absolute magnitude cut or (ii) a surface
brightness cut in addition to the SAGA–II absolute magnitude cut to the ELVES
sample (see Figure 3). Additionally, there is an even stronger agreement
between ELVES and SAGA–II when only accounting for satellites within 150 kpc
(see Figure 3). This lends confidence to these quenched fraction estimates as
the underlying samples of satellites are found via different techniques.

  * •

The absence of any significant effect on the ELVES sample after applying an
additional surface brightness cut implies that the SAGA–II sample is not
missing additional satellites beyond what they have already accounted for in
their incompleteness corrections.

  * •

Similarly, we find broad agreement in the cumulative number of all satellites
between the ELVES and SAGA–II samples, regardless of star-forming definition,
particularly when the SAGA–II incompleteness corrections are accounted for.

  * •

Our brief investigation of radial trends in both the ELVES and SAGA–II sample
found that (i) as expected, the quenched fraction decreases as a function of
radius and (ii) there is broad agreement in the number of star-forming
satellites in the ELVES and SAGA–II samples as a function of radius.

  * •

At first glance, there may be tension between the quenched fraction seen in
simulations, which use the Local Group as a benchmark, and larger statistical
samples of Milky Way-like systems. Additionally, the Local Group itself may be
an outlier among Milky Way-like systems. Continuing to expand observational
samples with multiwavelength datasets are crucial to better elucidate these
tensions.

The work we have presented here expands upon several investigations of the
quenched fraction around Milky Way-like systems. However, more stringent
constraints on these properties should be made using spectroscopic follow-up
to better characterize the association of these satellites (i.e. are they
gravitationally bound to their hosts? Are they potential backsplash systems?).
Additionally, comprehensive studies of their star-forming nature via resolved
H$\alpha$ and UV imaging (e.g. 20% of ELVES satellites do not have UV imaging)
would be valuable extensions that could further elucidate the results
presented here. HI observations are another crucial element which could shed
light on both quenching mechanisms (i.e. ram pressure stripping) and the star-
forming potential of these faint satellite systems; some of this work is
already underway (Karunakaran et al., 2022).

## Acknowledgements

AK acknowledges financial support from the State Agency for Research of the
Spanish Ministry of Science, Innovation and Universities through the "Center
of Excellence Severo Ochoa" awarded to the Instituto de Astrofísica de
Andalucía (SEV-2017-0709) and through the grant POSTDOC$\\_$21$\\_$00845
financed from the budgetary program 54a Scientific Research and Innovation of
the Economic Transformation, Industry, Knowledge and Universities Council of
the Regional Government of Andalusia. KS acknowledges support from the Natural
Sciences and Engineering Research Council of Canada (NSERC). BMP is supported
by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award
AST2001663. Research by DC is supported by NSF grant AST-1814208. DJS
acknowledges support from NSF grants AST-1821967 and 1813708.

This work made use of astropy (Astropy Collaboration et al., 2013, 2018),
jupyter (Beg et al., 2021), matplotlib (Hunter, 2007), numpy (Harris et al.,
2020), pandas (Wes McKinney, 2010), seaborn (Waskom, 2021), scipy (Virtanen et
al., 2020), and statsmodels (Seabold & Perktold, 2010).

This research made use of data from the SAGA Survey (sagasurvey.org). The SAGA
Survey was supported by NSF collaborative grants AST-1517148 and AST-1517422
and by Heising–Simons Foundation grant 2019-1402.

## Data Availability

The data used in this work are publicly available from the original
publications describing these samples.

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##  Appendix A Classifying Satellites Using Morphology and UV-detection

Here we show the quenched fractions and number of satellites for the ELVES
sample derived using their morphological classifications. For the SAGA–II
satellites, we adopt the simple star-forming criterion, i.e. $(S/N)_{NUV}>2$,
from Karunakaran et al. (2021), where they found a high correspondence of
satellites with both H$\alpha$ and NUV emission. We use this simple NUV
detection definition only in comparison to the ELVES morphological
classification, analogous to the comparison between morphology- and
H$\alpha$-based quenched fractions in C22 (see their Figure 11).

Comparing the ELVES quenched fractions and the number of satellites from
Figures 8 and 9, we can see there is a negligible difference between the
classifications based on the morphology and the colour-magnitude relation
regardless of the selection criteria applied (ELVES-H, -M, or -SB). This
consistency between these two classification methods should be expected given
the premise of the colour-magnitude relation determination in Carlsten et al.
(2021). It is interesting to point out in there is an even tighter
correspondence between the morphology-based and colour-magnitude relation-
based classifications when considering satellites within 150 kpc.

Figure 8: Same as Figures 3 and 5 for all satellites (left) and just those
within 150 kpc (right) but using morphology as the star-forming classification
for the ELVES sample and significant NUV emission as the star-forming
classification for SAGA–II.

Figure 9: Same as Figure 4 and 6 for all satellites (left) and just those
within 150 kpc (right) but using morphology as the star-forming classification
for the ELVES sample and significant NUV emission as the star-forming
classification for SAGA–II.