# Deep Synoptic Array science: Two fast radio burst sources in massive galaxy
clusters

Liam Connor  Cahill Center for Astronomy and Astrophysics, MC 249-17
California Institute of Technology, Pasadena CA 91125, USA.  Vikram Ravi
Cahill Center for Astronomy and Astrophysics, MC 249-17 California Institute
of Technology, Pasadena CA 91125, USA.  Owens Valley Radio Observatory,
California Institute of Technology, Big Pine CA 93513, USA.  Morgan Catha
Owens Valley Radio Observatory, California Institute of Technology, Big Pine
CA 93513, USA.  Ge Chen  Cahill Center for Astronomy and Astrophysics, MC
249-17 California Institute of Technology, Pasadena CA 91125, USA.  Jakob T.
Faber  Cahill Center for Astronomy and Astrophysics, MC 249-17 California
Institute of Technology, Pasadena CA 91125, USA.  James W. Lamb  Owens Valley
Radio Observatory, California Institute of Technology, Big Pine CA 93513, USA.
Gregg Hallinan  Cahill Center for Astronomy and Astrophysics, MC 249-17
California Institute of Technology, Pasadena CA 91125, USA.  Owens Valley
Radio Observatory, California Institute of Technology, Big Pine CA 93513, USA.
Charlie Harnach  Owens Valley Radio Observatory, California Institute of
Technology, Big Pine CA 93513, USA.  Greg Hellbourg  Cahill Center for
Astronomy and Astrophysics, MC 249-17 California Institute of Technology,
Pasadena CA 91125, USA.  Owens Valley Radio Observatory, California Institute
of Technology, Big Pine CA 93513, USA.  Rick Hobbs  Owens Valley Radio
Observatory, California Institute of Technology, Big Pine CA 93513, USA.
David Hodge  Cahill Center for Astronomy and Astrophysics, MC 249-17
California Institute of Technology, Pasadena CA 91125, USA.  Mark Hodges
Owens Valley Radio Observatory, California Institute of Technology, Big Pine
CA 93513, USA.  Casey Law  Cahill Center for Astronomy and Astrophysics, MC
249-17 California Institute of Technology, Pasadena CA 91125, USA.  Owens
Valley Radio Observatory, California Institute of Technology, Big Pine CA
93513, USA.  Paul Rasmussen  Owens Valley Radio Observatory, California
Institute of Technology, Big Pine CA 93513, USA.  Jack Sayers  Cahill Center
for Astronomy and Astrophysics, MC 249-17 California Institute of Technology,
Pasadena CA 91125, USA.  Kritti Sharma  Cahill Center for Astronomy and
Astrophysics, MC 249-17 California Institute of Technology, Pasadena CA 91125,
USA.  Myles B. Sherman  Cahill Center for Astronomy and Astrophysics, MC
249-17 California Institute of Technology, Pasadena CA 91125, USA.  Jun Shi
Cahill Center for Astronomy and Astrophysics, MC 249-17 California Institute
of Technology, Pasadena CA 91125, USA.  Dana Simard  Cahill Center for
Astronomy and Astrophysics, MC 249-17 California Institute of Technology,
Pasadena CA 91125, USA.  Jean Somalwar  Cahill Center for Astronomy and
Astrophysics, MC 249-17 California Institute of Technology, Pasadena CA 91125,
USA.  Reynier Squillace  Cahill Center for Astronomy and Astrophysics, MC
249-17 California Institute of Technology, Pasadena CA 91125, USA.  Sander
Weinreb  Cahill Center for Astronomy and Astrophysics, MC 249-17 California
Institute of Technology, Pasadena CA 91125, USA.  David P. Woody  Owens Valley
Radio Observatory, California Institute of Technology, Big Pine CA 93513, USA.
Nitika Yadlapalli  Cahill Center for Astronomy and Astrophysics, MC 249-17
California Institute of Technology, Pasadena CA 91125, USA.

###### Abstract

The hot gas that constitutes the intracluster medium (ICM) has been studied at
X-ray and millimeter/sub-millimeter wavelengths (Sunyaev–Zeld’ovich effect)
for decades. Fast radio bursts (FRBs) offer an additional method of directly
measuring the ICM and gas surrounding clusters, via observables such as
dispersion measure (DM) and Faraday rotation measure (RM). We report the
discovery of two FRB sources detected with the Deep Synoptic Array (DSA-110)
whose host galaxies belong to massive galaxy clusters. In both cases, the FRBs
exhibit excess extragalactic DM, some of which likely originates in the ICM of
their respective clusters. FRB 20220914A resides in the galaxy cluster Abell
2310 at $z=0.1125$ with a projected offset from the cluster center of
520$\pm$50 kpc. The host of a second source, FRB 20220509G, is an elliptical
galaxy at $z=0.0894$ that belongs to the galaxy cluster Abell 2311 at
projected offset of 870$\pm$50 kpc. These sources represent the first time an
FRB has been localized to a galaxy cluster. We combine our FRB data with
archival X-ray, SZ, and optical observations of these clusters in order to
infer properties of the ICM, including a measurement of gas temperature from
DM and $y_{SZ}$ of 0.8–3.9 keV. We then compare our results to massive cluster
halos from the IllustrisTNG simulation. Finally, we describe how large samples
of localized FRBs from future surveys will constrain the ICM, particularly
beyond the virial radius of clusters.

galaxy clusters — radio transient sources, Abell 2310, Abell 2311

††journal: ApJ Letters††software: astropy, CASA, frb, heimdall, lpipe, pPXF,
Prospector, wsclean

##  1 Introduction

Galaxy clusters are massive ($10^{14}-10^{15}\,M_{\odot}$) gravitationally
bound objects comprised of hundreds to thousands of galaxies. Galaxies make up
just a few percent of the total cluster mass. The dominant component of
baryons by mass and volume is in the hot intracluster medium (ICM) made of
diffuse gas with $n_{e}\approx 10^{-3}$ cm-3 and $T_{e}\approx 10^{7}-10^{8}$
K. Within a sufficiently large volume (e.g., the virial radius), the ratio of
dark matter to baryons approximately matches the Universal value (Eckert et
al., 2019), which is not true for smaller halos where feedback is expected to
expel gas beyond the virialized dark matter halos (Tumlinson et al., 2017).

The ICM has been studied in great detail at X-ray wavelengths for the past
fifty years (Sarazin, 1986). Thermal bremsstrahlung emission from gas heated
to 2–15 keV is observed out to the virial radii of clusters (1–2 Mpc), tracing
the radial distribution of the ICM gas (Ghirardini et al., 2019). The ICM
reaches such high temperatures by adiabatic compression and shock heating as
the gas reaches hydrostatic equilibrium within the potential well (Voit,
2005). Free-free emission scales with emissivity, and the specific X-ray
luminosity can be written as an integral of plasma density squared,

$L_{X}\approx\int\,n^{2}_{e}\,\Lambda(T_{e})\,\textup{d}V,$ (1)

where $n_{e}$ is the number density of free electrons and $\Lambda(T_{e})$
characterizes the temperature dependence of X-ray emission. The total mass can
then be inferred from the cluster’s X-ray luminosity (Pratt et al., 2009a).
X-ray spectroscopy can also be used to measure the gas temperature (Böhringer
& Werner, 2010) and its velocity structure (Hitomi Collaboration et al.,
2016).

The hot plasma in the ICM is also observable at millimeter/sub-millimeter
wavelengths through the thermal Sunyaev-Zel’dovich (SZ) effect, whereby
photons in the cosmic microwave background (CMB) are inverse Compton scattered
by thermal electrons (Mroczkowski et al., 2019). This leads to spectral
distortions in the CMB at the level of $10^{-4}$–$10^{-5}$. SZ observations of
the ICM are parameterized by the Compton Y-parameter, which is given by the
integral of electron thermal pressure along the line of sight,

$y_{SZ}=\frac{k_{B}\,\sigma_{T}}{m_{e}\,c^{2}}\int n_{e}\,T_{e}\,\textup{d}l,$
(2)

where $k_{B}$ is Boltzmann’s constant, $\sigma_{T}$ is the Thomson cross-
section, $m_{e}$ is electron mass, $c$ is the speed of light.

Fast radio bursts (FRBs) offer an additional probe of the ICM of massive
galaxy clusters. FRBs are short-duration (10-2–102 ms) radio transients that
have been detected over cosmological distances ($z\lesssim 1.5$) (Petroff et
al., 2019; Cordes & Chatterjee, 2019). To date, $\mathcal{O}(10^{3})$ sources
have been discovered (CHIME/FRB Collaboration et al., 2021; Petroff et al.,
2016) but only two-dozen have been localized with sufficient angular precision
to identify a host galaxy (Chatterjee et al., 2017; Ravi et al., 2019; Heintz
et al., 2020; Bhandari et al., 2020). Propagation effects imparted on the
radio pulse encode information about the plasma through which the burst
travelled. Dispersion measure (DM) is an integral of line-of-sight electron
density and is given by,

$\textup{DM}=\int\,n_{e}\,\textup{d}l.$ (3)

Unlike with thermal X-ray emission or SZ observations of the ICM, the FRB DM
is detectably impacted by all plasma between us and the source, not just
$10^{6-8}$ K gas. This is both a blessing and a curse: FRB DMs will probe
plasma in the host galaxy, the circumgalactic medium (CGM), the ICM of
intervening or host clusters, the intergalactic medium (IGM), and the Milky
Way’s interstellar medium (ISM). For individual FRB sightlines, these terms
must be explicitly modelled. An FRB that is impacted by a galaxy cluster will
have the following “DM budget”,

$\rm{DM}_{obs}=\textup{DM}_{MW}+\textup{DM}_{IGM}+\frac{\textup{DM}_{ICM}}{1+z_{c}}+\frac{\textup{DM}_{host}}{1+z_{frb}},$
(4)

where $z_{c}$ and $z_{frb}$ are the cluster and FRB redshifts, respectively.
The observed DM is likely dominated by the IGM for most FRBs. Still, it is
important to be specific about what is meant by the IGM. In Macquart et al.
(2020), the relationship between DMcosmic and source redshift includes all
extragalactic gas between the Milky Way and the host galaxy. DMcosmic
therefore includes the CGM, intragroup medium (IGrM), ICM, and IGM. All of
those terms correlate with source distance because the optical depth of halos
increases with redshift. In this work we take the IGM to be ionized gas that
resides outside of virialized dark matter halos (McQuinn, 2016).

For sources that intersect or are embedded in galaxy clusters, the largest DM
contribution may be from the ICM (Prochaska & Zheng, 2019). For example, a
cluster with $\langle n_{e}\rangle=10^{-3}$ cm-3 and $R_{200}=1$ Mpc will lead
to DM${}_{\rm ICM}\sim 10^{3}$ pc cm-3 for low impact parameters. This value
is more than double the typical contribution from the IGM for a source at
$z=0.5$ and 70$\%$ larger than the mean DMobs of CHIME/FRB sources (Macquart
et al., 2020; CHIME/FRB Collaboration et al., 2021). The polarization
properties of FRBs can help measure the magnetic field of the ICM. Faraday
rotation measure (RM) is an integral of the free electrons, weighted by the
line-of-sight magnetic field strength,

$\textup{RM}=\frac{e^{3}}{2\pi\,m^{2}_{e}\,c^{4}}\int\,B_{\parallel}\,n_{e}(l)\,\textup{d}l,$
(5)

where $e$ is the charge of an electron. While other radio objects can provide
cluster RMs (van Weeren et al., 2019), FRBs are unique amongst extragalactic
sources in their ability to measure both RM and DM. Therefore, if one can
isolate the components of RM and DM that are due to the ICM, the mean line-of-
sight magnetic field strength in the cluster can be determined by their ratio,

$\langle B_{\parallel,\rm
ICM}\rangle=1.23\,\mu\textup{G}\,\,\frac{\textup{RM}_{\rm
ICM}}{\textup{DM}_{\rm ICM}},$ (6)

where RM and DM are given in the standard units of rad m-2 and pc cm-3,
respectively. The application of FRBs to the ICM has been considered in
previous works, including the detection of an FRB in the direction of the
Virgo cluster by ASKAP (Agarwal et al., 2019). In that case, the localization
precision was insufficient to determine a host galaxy, so it was unclear if
the source was embedded in, or behind, the cluster. Another unlocalized
source, FRB 20190116A (CHIME/FRB Collaboration et al., 2019) is likely within
a $\sim$ 5 Mpc of the Coma cluster in projection and may be dispersed by
filamentary structure extending from the cluster (Hallinan et al., 2019a).
Fujita et al. (2017) investigated the application of FRBs to the warm hot
intergalactic medium (WHIM) at the outskirts of galaxy clusters, where X-ray
observations are difficult due to the $n_{e}^{2}$ dependence of emissivity.
Nonetheless, most of the effort in studying halo gas with FRBs has been
devoted to the circumgalactic medium (Prochaska & Zheng, 2019; Ravi, 2019; Lee
et al., 2022). That is because the CGM is more difficult to detect than the
ICM using traditional means (X-ray and SZ observations are much less sensitive
to the gas in galaxy-scale halos), and because of the CGM’s significance in
galaxy formation and feedback processes. Connor & Ravi (2022) presented the
first statistical evidence for the impact of halo gas on FRBs and demonstrated
the importance of considering galaxy groups on FRB DM budgets. As we
demonstrate, current and future FRB surveys will find a significant number of
sources that are impacted by galaxy clusters, and understanding their effects
and prevalence are important for CGM studies, in addition to studying the ICM
itself.

In this work we make the first unambiguous detection of FRB sources that
belong to a galaxy cluster. Both sources were discovered by the real-time FRB
survey on the Deep Synoptic Array (DSA-110)111https://deepsynoptic.org. The
DSA-110 is a radio interferometer at the Owens Valley Radio Observatory (OVRO)
that was built to localize FRBs with $\sim$ arcsecond precision. A detailed
account of the instrument will be presented in Ravi et al. (in prep.). During
the observations presented in this work, the DSA-110 was operating in its
commissioning phase with 63 antennas collecting data, as described in Ravi et
al. (2022).

In Section 2 we describe the radio properties of two FRBs using the DSA-110.
We describe the two massive clusters of which the FRB host galaxies are
members. A companion paper details the interferometric localizations of FRB
20220509G and FRB 20220914A as well as their unusual host galaxies (Sharma et
al., in prep.). In Section 3.2 we model the DM contribution from the ICM for
both sources, combining our radio data with archival X-ray, SZ, and optical
data to infer properties about the clusters’ respective ICM. Finally, we
compare our results with clusters found in the IllustrisTNG simulation.

Source | RA (deg) | Dec (deg) | $\mathbf{z_{gal}}$ | DMobs | DMMW | RMobs |  $\mathbf{\tau}$ (ms) |  $\mathcal{F}$ (Jy ms) |  $b_{\perp}$ (kpc)
---|---|---|---|---|---|---|---|---|---
FRB 20220914A | 282.0568 | 73.3369 | 0.1139 | 631.29 | 47/55 | N/A | $<0.080$ | 2.2 | 520$\pm$50
FRB 20220509G | 282.6700 | 70.2438 | 0.0894 | 269.53 | 46/55 |  $-110$(1) | 0.08$\pm$0.02 | 5.5 | 870$\pm$50
Table 1: The radio properties of two galaxy cluster FRBs. DM and RM are reported in pc cm-3 and rad m-2, respectively. The scattering timescale, $\tau$, is referenced to 1.4 GHz. The two Galactic ISM DM estimates listed are YMW16 and NE2001. RA and Dec are in epoch J2000. Cluster | RA (deg) | Dec (deg) | Richness | $\mathbf{z_{clust}}$ |  M500 ($M_{\odot}$) | R500 (kpc) | LX (erg/s) | Y5R500 (arcmin2)
---|---|---|---|---|---|---|---|---
Abell 2310 | 281.81708 | 73.3472 | 124 | 0.1125 | 1.7$\times$1014 | 810 | $8.3\times 10^{43}$ | $0.85\pm 0.35\times 10^{-3}$
Abell 2311 | 282.497 | 70.376 | 190 | 0.0899(1) | 1.6$\times 10^{14}$ | 800 | 4.7$\times 10^{43}$ | $0.81\pm 0.36\times 10^{-3}$
Table 2: The properties of two galaxy clusters that host the FRBs presented in
this paper. $L_{X}$ is the X-ray luminosity at 0.1–2.4 keV within $R_{500}$.

##  2 Cluster FRBs

The radio properties of FRB 20220914A and FRB 20220509G are listed in Table 1.
The observed parameters of their respective host galaxy clusters are given in
Table 2. The two FRBs presented here are from distinct galaxy clusters, but
are relatively nearby on the sky—separated by just 3.1 degrees. DSA-110 is a
transit instrument that was parked at Declination $\sim$ $+$70 for most of the
2022 commissioning period. For this reason, most of our initial sample of
sources fall on a ring in RA and several pairs are within a few degrees of
each other. Below we described observations of the FRBs and their host
galaxies, as well as archival data obtained for the galaxy clusters.

Figure 1: Dedispersed total-intensity dynamic spectra for two FRBs detected by
DSA-110. Both FRBs reside in galaxies that belong to massive galaxy clusters.

###  2.1 FRB 20220914A

FRB 20220914A was detected at MJD 59836.1459660. Follow-up analysis found an
optimal DM of 631.3 pc cm-3 and a pulse full-width at half maximum (FWHM) of
140 $\mu$s. With a S/N of 13.4 and system-equivalent flux density (SEFD) of
140 Jy, the fluence of the burst was roughly 2.2 Jy ms. Offline
interferometric localization found the position of the FRB to be R.A. J2000,
decl. J2000 = 18h48m13.63s, $+$73d20m12.89s, the centroid of which is 1.6”
from a galaxy with spectroscopic redshift $z=0.1139$. The expected DM from the
Milky Way at these Galactic coordinates is roughly 50 pc cm-3 from NE2001
(Cordes & Lazio, 2002) and 47 pc cm-3 from YMW16 (Yao et al., 2017). The IGM
is expected to contribute 50–120 pc cm-3 at this redshift, suggesting that FRB
20220914A has significant extragalactic DM excess.

We find no evidence of scattering, placing an upper-limit of $\tau<80$ $\mu$s
at 1.4 GHz. Polarimetric analysis found no detectable polarization and no RM
was determined after searching a range of $-10^{6}$ to $+10^{6}$ rad m-2. The
upper-limits on polarization fraction were $L/I<15\%$ and $V/I<20\%$.

####  2.1.1 ABELL 2310 galaxy cluster

The position of FRB 20220914A was cross-matched with both the DESI Legacy
Imaging Surveys Data Release 9 (DR9) galaxy catalog (Dey et al., 2019) and DR9
cluster/group catalog (Yang et al., 2021). We find that the host galaxy of FRB
20220914A is a member of the massive galaxy cluster Abell 2310 (Abell, 1958).
According to the DESI DR9 group/cluster catalog, this cluster has richness 124
(i.e. number of member galaxies), $M_{180}=2.5\times 10^{14}$ $M_{\odot}$,
with a brightest cluster galaxy (BCG) at spectroscopic redshift $z=0.1125$.
The cluster is also in the Meta-Catalog of X-Ray Detected Clusters of Galaxies
(MCXC) with source name J1847.2+7320 (Piffaretti et al., 2011). The X-ray
surface brightness centroid is at 18h47m16.s 73d20m50s (Piffaretti et al.,
2011). The FRB offset from this position is 4.22’ suggesting a projected
physical impact parameter of 520 kpc. The X-ray luminosity within $R_{500}$ is
8.31$\times 10^{43}$ erg s-1, which gives $M_{500}=1.69\times 10^{14}$
$M_{\odot}$ using an empirical $L_{X}-M$ relation (Pratt et al., 2009b;
Piffaretti et al., 2011).

The cluster has also been detected via the thermal SZ effect and is listed in
the Planck SZ2 cluster catalog as PSZ2 G104.29+26.17 (Planck Collaboration et
al., 2016a). The SZ-derived mass based on a hydrostatic mass calibration is
$M_{500}=1.94\pm 0.28\times 10^{14}\,M_{\odot}$ (Planck Collaboration et al.,
2014), and its SZ centroid has a physical offset from FRB 20220914A of $\sim$
380 kpc. We have also analyzed the Planck MILCA $y$-map from Planck
Collaboration et al. (2016b) using the techniques described in Sayers et al.
(2016) to obtain both a two-dimensional projected model of the cluster
$y(\theta)$, along with the total integrated SZ signal $Y_{5R500}$. In brief,
we assume the cluster follows the profile shape given by Arnaud et al. (2010),
with the scale radius set by the X-ray value of $R_{500}$ and centered on the
X-ray centroid. We then determine the best-fit normalization of this model,
with the uncertainty on this normalization estimated from fits to 100 random
realizations of the Planck noise. The result is $Y_{5R500}=0.85\pm 0.35$
arcmin2.

The point-spread function (PSF) of Planck is large, so we take the offset
between FRB 20220914A and Abell 2310 to be the separation between the X-ray
centroid and the FRB’s host galaxy. This gives a projected physical offset of
520$\pm$50 kpc. In Figure 4 we show the filtered X-ray data with a contour for
the SZ emission region, as well as a zoom in on the optical host galaxy image.
The X-ray intensity data is taken from the public archive of X-ray
clusters222https://github.com/wwxu/rxgcc.github.io (Xu et al., 2022).

Figure 2: The polarization properties of FRB 20220509G. The top panel shows a
flat PA across the pulse and the middle panel shows the linearly polarized
pulse profile. The bottom panel is the Faraday spectrum with a peak at
RM=$-111.5$ rad m-2.

The redshift difference between the host galaxy of FRB 20220914A and the
brightest cluster galaxy (BCG) is $\Delta z=-0.00129$, indicating the host has
a recession velocity of roughly 390 km s-1. We do not know the radial position
of the FRB within the cluster, but we have good reason to believe it is not
near the front. We take the radial position to be $l_{LOS}$, which is zero at
the distance of the cluster center and negative behind the cluster. The radial
distribution of galaxies in clusters is well described by an NFW profile with
concentration parameter c=2.6 (Budzynski et al., 2012). With a virial radius
of 800 kpc, the probability distribution of galaxy radius peaks around 300 kpc
and declines towards larger radii. Therefore, for an impact parameter beyond
300 kpc, the most likely $l_{LOS}$ is zero. More convincingly, as we show in
Section 3.2, the FRB has significant excess dispersion that likely comes from
the ICM. The magnitude of this extra DM cannot easily be explained by the IGM
or the host galaxy, so $l_{LOS}$ is likely smaller than several hundred kpc.

####  2.1.2 The host galaxy of FRB 20220914A

The FRB 20220914 has been localized to a typical late-type spiral galaxy at
R.A. (J2000) = 18:48:13.9580 and declination (J2000) = +73:20:10.703 (Sharma
et al., in prep.). The spectroscopic redshift of the galaxy, as measured from
optical spectra acquired with Keck-I/LRIS, is $0.1139\pm 0.0001$. A detailed
spectral energy distribution analysis revealed a stellar mass of $\log
M_{*}(M_{\odot})=9.99^{+0.09}_{-0.09}$. The constrained star formation history
indicates significant recent star formation with several starbursts over the
last 3.5 Gyr, thus reflecting a wide probability distribution for the age of
its progenitor.

###  2.2 FRB 20220509G

The fast radio burst source FRB 20220509G had an arrival time of 59708.4944991
at reference frequency of 1500 MHz. Its optimal DM was 269.53 pc cm-3 and had
a fluence of 5.5 Jy ms. Offline interferometric localization found that the
source is at R.A. J2000, decl. J2000 = 18h50m40.8s, $+$70d14m37.8, with a
90$\%$ error ellipse with axes 4.7 and 3.2 in R.A. and decl. This is within 6”
of a massive galaxy with spectroscopic redshift $z=0.0894$. The Galactic ISM
DM estimates are 55 pc cm-3 from NE2001 and 46 pc cm-3 from YMW16. The
expected IGM contribution at this redshift is roughly 75 pc cm-3, but with
significant uncertainty. We analyze the source’s DM budget in Section 3.2.

Figure 3: Slice plots of the smoothed galaxy number density within 5
arcminutes of each FRB line-of-sight. The galaxy data are from the DESI Legacy
Imaging Survey DR9 and are mostly photometric redshifts.

The burst was fit with a scattering tail plus a Gaussian component. We find
evidence of scattering with a timescale of 80$\pm$20 $\mu$s at 1.4 GHz and a
Gaussian component that is $30\pm 10$ $\mu$s. Offline polarimetric analysis
found that FRB 20220509G was nearly 100$\%$ linearly polarized with an RM of
$-111.5\pm 1.5$ rad m-3 in the observer frame. This is significantly larger
than the Galactic RM foreground value of $-9\pm 16$ rad m-3. The burst’s
position angle (PA) is flat across the pulse. The polarization properties of
FRB 20220509G are shown in Figure 2.

####  2.2.1 Abell 2311 galaxy cluster

The host galaxy of FRB 20220509G is a member of the galaxy cluster Abell 2311
(Abell, 1958). According to the DESI DR9 cluster/group catalog, the cluster’s
richness is 190 with $M_{180}=2.5\times 10^{14}\,M_{\odot}$, determined by the
velocity dispersion of member galaxies. The radius at which the average
enclosed density is 500 times the critical density is $R_{500}=800$ kpc. The
X-ray luminosity within $R_{500}$ is $L_{X}=4.7\times 10^{43}$ erg s-1 with an
inferred mass of $M_{500}=1.6\times 10^{14}\,M_{\odot}$. The cluster does not
have a published SZ detection and is not in the Planck SZ2 cluster catalog.
However, we have analyzed the Planck MILCA $y$-map for this cluster in the
same way as for Abell 2311, finding $Y_{5R500}=0.81\pm 0.36\times 10^{-3}$
arcmin2.

The filtered ROSAT X-ray intensity is shown in Figure 4. The projected
physical offset between FRB 20220509G and the X-ray centroid is $870\pm 50$
kpc, placing the FRB at a minimum radius of just beyond $R_{500}$.

####  2.2.2 The host galaxy of FRB 20220509G

The likely host galaxy of FRB 20220509 is an early-type elliptical galaxy with
insignificant ongoing star formation, and hence stands out as a quiescent
galaxy in the known population of FRB hosts (Sharma et al., in prep.). The
measured spectroscopic redshift of the host is $0.0894\pm 0.0001$ and a
detailed spectral energy distribution analysis reveals a stellar mass of
$\log\mathrm{M}_{*}(\mathrm{M}_{\odot})=11.13^{+0.02}_{-0.02}$ with star
formation rate averaged over the last 100 Myr of $0.08^{+0.06}_{-0.04}$. An
old stellar population implies a long delay between the time of occurrence of
this FRB and the formation of its progenitor, thus opening another window of
progenitors with long delay times.

Figure 4: The two FRB sources reported in this work with their respective host
galaxies and galaxies clusters. The left column images show filtered ROSAT
X-ray intensity (Xu et al., 2022) for galaxy cluster Abell 2310 (top) and
Abell 2311 (bottom). The magenta circle in the top left panel has a radius of
1 Mpc and denotes the location of the SZ cluster from the PSZ2 catalog. The
bottom panel magenta cirlce corresponds to our SZ measurement for Abell 2311.
The right columns show insets on the position of FRB 20220914A (top) and FRB
20220509G (bottom) plotted over a PanSTARRS1 riz-band image (Chambers et al.,
2016, PS1).

##  3 Data analysis

We now seek to synthesize the FRB radio properties with observations of their
host galaxies and host clusters. This will allow us to infer the impact of the
ICM on FRB 20220509G and FRB 20220914A. Neither host galaxy has a high rate of
star formation. The early-type host of FRB 20220509G, in particular, is not
expected to have a significant ISM that would contribute to local dispersion
(Lees, 1992). In this section we estimate the origin of scattering, DM, and RM
and model the contribution of the ICM to each propagation effect.

###  3.1 Scattering & scintillation

Both FRB sources show evidence of scintillation that is consistent with a
nearby scattering screen in the Milky Way. FRB 20220509G and FRB 20220914A
have decorrelation bandwidths of $\Delta\nu=3.1\pm 0.7$ MHz and
$\Delta\nu=2.51\pm 0.16$ MHz, respectively. Since the two sources are only
separated by a few degrees, it is unsurprising that their decorrelation
bandwidth and modulation indexes are similar. However, the presence of fully-
modulated scintillation is physically interesting in the case of FRB
20220509G, which also shows evidence of temporal scattering. The presence of
both scattering and spectral scintillation allows one to place constraints on
the geometry of the two scattering screens. Scattering causes angular
broadening and if that broadening were too large the FRB would be resolved out
by the scattering screen in our Galaxy (Masui et al., 2015; Connor et al.,
2016; Simard & Ravi, 2021).

For a given scattering timescale, angular broadening is maximal when the
screen is halfway between us and the source. Therefore, if the screen were in
the CGM of an intervening galaxy at $z\sim 0.05$, we would not expect FRB
20220509G to scintillate. Following Eq 48 in Simard & Ravi (2021), we place an
upper-limit on the distance between the FRB source and the first scattering
screen to be $\leq 140$ kpc. This leads to three scenarios for the origin of
the temporal scattering in FRB 20220509G, each of which is plausible but
somewhat surprising given the early-type host galaxy and the hot, smooth ICM
in which it is embedded. The scattering could be in the ISM of the host galaxy
at $\sim$ kpc scales from the FRB emitting source. This would require an
unusual sightline given the lack of H$\alpha$ emission and limited turbulence
in the ISM of elliptical galaxies (Seta et al., 2021; Ocker et al., 2022).
Alternatively, it could arise in the immediate vicinity of the source, such as
in a stellar wind, analogous to the scattering in FRB 20190520 (Niu et al.,
2022a; Ocker et al., 2023; Beniamini et al., 2022; Anna-Thomas et al., 2022).
A third option is that it could be near the host galaxy in the ICM, perhaps in
the outflows or CGM of the host.

###  3.2 DM from the ICM

We model the DM along the line of sight to each FRB in order to generate a
probability distribution for the ICM contribution. The probability density
function (PDF, denoted here by $\mathcal{P}$) of a sum of independent
variables is the convolution of their individual PDFs. The DM terms are not
strictly independent, but we find that the convolution relation for a sum of
variables is a good approximation in this case. Using Eq. 4, we find,

$\mathcal{P}(\rm{DM}_{ICM})\\!=\\!\mathcal{P}(DM_{obs})\ast\mathcal{P}(-\rm{DM}_{MW})\ast\mathcal{P}(-\rm{DM}_{IGM})\ast\mathcal{P}(-\rm{DM}_{h})$
(7)

where $\mathcal{P}(\rm{DM}_{obs})$ is Gaussian with variance determined by the
measurement error on the observed DM. Here the DMs are all in the observer
frame, so we must multiply by $1+z_{c}$ when estimating the DM from the ICM.
We assert that the probability density must be zero for negative DM.

For FRB 20220914A, we place an upper-limit on $\rm{DM}_{h}$ to be 50 pc cm-3
based on the strong upper limit on temporal scattering. We take
$\mathcal{P}(\rm{DM}_{h})$ to be a uniform distribution between 0 and 50 pc
cm-3 because we do not have a strong motivation for a preferred DM peak in the
distribution. Previous detections of unscattered FRBs do not have a robust
measurement of local DM on which to base an empirical distribution. There is
reason to believe the local DM contribution is very small for other similar
FRB sources. For example, FRB 20180916B (Pastor-Marazuela et al., 2021) and
FRB 20220319D (Ravi et al., 2023) have comparable upper-limits on local
scattering and likely have DM${}_{h}\leq 20$ pc cm-3. The local ($<150$ kpc)
contribution to the DM of FRB 20220509G is less certain, due to the presence
of both scattering and scintillation. We assume a flat prior between 0 and 100
pc cm-3.

For $\mathcal{P}(\rm{DM}_{IGM})$, we use the IllustrisTNG simulation to
estimate the distribution of DM from the IGM for a source at a few hundred Mpc
along similar sightlines to our FRBs. We take the functional form of DMIGM
found by Zhang et al. (2021) for FRBs at $z\approx 0.1$, who also used
IllustrisTNG. However, we independently estimate the mean DMIGM for sightlines
that intersect massive halos with $M_{500}>10^{13.5}\,M_{\odot}$. We then
exclude DM contribution from the halo itself to estimate the mean of $\rm
DM_{\rm IGM}$ for that subset of sightlines. By doing this we account for
correlations in the Universe’s matter distribution: Sightlines that intersect
clusters are more likely to intersect filaments and less likely to pass
through voids, compared to typical positions. We find that for $z\lesssim
0.1$,

$\langle\rm DM_{IGM}\rangle\approx 22\,\rm
pc\,cm^{-3}\,\left(\frac{D_{A}}{100\,Mpc}\right),$ (8)

where $D_{A}$ is angular diameter distance. This gives a mean value of 93 pc
cm-3 with a 90$\%$ confidence interval on DM${}_{\rm IGM}=48-260$ pc cm-3 for
FRB 20220914A. For FRB 20220509G we find a mean value of 76 pc cm-3 with a
90$\%$ confidence interval on DM${}_{\rm IGM}=39-175$ pc cm-3. The estimated
IGM DM distributions are shown in Figure 5 as dashed red curves.

In these FRB directions, the Milky Way contribution is taken to be normally
distributed with mean 70 pc cm-3 and standard deviation 30 pc cm-3. This value
includes the Galactic halo. These values are based on NE2001 (Cordes & Lazio,
2002) and YMW (Yao et al., 2017) and recent evidence that the Milky Way halo
contribution to DM is smaller than previously thought (Bhardwaj et al., 2021;
Ravi et al., 2023; Cook et al., 2023). The two FRB sources are nearby on the
sky, allowing us to use similar estimates for $\mathcal{P}(\rm{DM}_{MW})$.

We have attempted to make conservative estimates on the uncertainty of each
component of the observed DM, which will result in a wider inferred DMICM
distribution. We warn that the various elements in the DM budget were
estimated by different means and are subject to modelling uncertainties. With
these caveats, the resulting probability distribution of the ICM contribution
to DM is shown in Figure 5. We find that Abell 2310’s ICM adds 265–511 pc cm-3
at 90$\%$ confidence to the observed DM of FRB 20220914A. In the frame of the
cluster, this range is 295–568 pc cm-3. These values make it unlikely that the
host galaxy is near the front of the cluster, as such a high $\rm DM_{\rm
ICM}$ requires a significant path through the intracluster medium. In the case
of Abell 2311, we find a 90$\%$ confidence interval of 16–172 pc cm-3 for $\rm
DM_{\rm ICM}$ in the cluster frame. This range is consistent with an FRB
embedded in a $1.6\times 10^{14}\,M_{\odot}$ cluster at a projected offset of
$\sim$ 870 kpc. Still, it is difficult to say with certainty that the FRB’s
majority DM component is the ICM due to the presence of scattering and larger
projected impact parameter of the host.

Figure 5: The relative probability distributions for each component of the
observed FRB DMs. The distributions of $\rm DM_{\rm ICM}$ are shown in the
purple shaded region under the black curves.

###  3.3 ICM magnetic field

FRBs are the only known cosmological sources for which both DM and RM can be
measured. If DMICM and RMICM can be determined, FRBs allow us to measure the
mean line-of-sight magnetic field strength of a galaxy cluster, as shown in
Eq. 6. The observed RM of FRB 20220509G is $-111.5\pm 1$ rad m-2, compared
with the expected Milky Way foreground RM of $-9\pm 16$ rad m-2 in that
direction (Hutschenreuter et al., 2022). If the extragalactic RM is dominated
by the ICM then the cluster-frame RM is $\approx$ 120 rad m-2, and we can use
$\mathcal{P}(\rm DM_{ICM})$ to infer $\langle B_{\parallel,\rm ICM}\rangle$ at
the impact parameter of FRB 20220509G. We find that the average magnetic field
strength is 0.7–7.5 $\mu$G. Again, this is subject to the assumption that the
observed RM is dominated by the ICM.

The values we obtain for both RM and $\langle B_{\parallel,\rm ICM}\rangle$
are in line with previous observations, as well as magnetohydrodynamical (MHD)
simulations of galaxy clusters (Carilli & Taylor, 2002; Marinacci et al.,
2018). Böhringer et al. (2016) analyzed the RMs from 1383 of extragalactic
polarized sources and found values between $-200$ and $+$200 rad m-2 were
common at $R_{500}$. The corresponding magnetic field strengths they deduced
were $\sim$ a few microGauss (Böhringer et al., 2016). In Section 5 we discuss
how cluster FRBs from future surveys could better constrain magnetic fields in
and around the ICM.

###  3.4 Mean temperature from DM

The ICM observables that we discuss in this work are DM, RM, X-ray brightness,
and the SZ-$y$ parameter. Each is a weighted integral of $n_{e}$ along the
line of sight. In Faraday rotation, the gas density is weighted by magnetic
field strength, $B_{//}$. For X-ray luminosity, emission is the sum of
$n^{2}_{e}$ weighted by $\Lambda(T_{e})$. In the case of the SZ-$y$ parameter,
$n_{e}$ is weighted by $T_{e}$ itself. X-ray derived density and SZ-derived
pressure are commonly used to estimate temperature (Eckert et al., 2013).
Alternatively, the ratio of X-ray luminosity to $y_{SZ}$ has been taken to
constrain the gas temperature. For example, Planck Collaboration et al.
(2016c) find the ratio of X-ray luminosity to $y_{SZ}$ for the Virgo cluster
at angular position $\theta$ to be $\langle
n_{e}\,\Lambda(T_{e})/(k_{B}\,T_{e})\rangle(\theta)$. This quantity offers
information on the cluster temperature profile under certain assumptions about
$n_{e}(r)$ and $\Lambda$.

We can attempt something similar using the ratio of $y_{SZ}$ to DMICM, which
will be independent of $n_{e}$. Evaluating Eq. 2 and Eq. 3 at impact parameter
$b_{\perp}$ we get,

$y_{SZ}(b_{\perp})\approx\frac{k_{B}\,T_{e}}{m_{e}\,c^{2}}\,\sigma_{T}\,\langle
n_{e}\rangle\,L_{ICM}$ (9)

$\textup{DM}_{ICM}(b_{\perp})\approx\langle n_{e}\rangle\,L_{ICM},$ (10)

where $L_{ICM}$ is the line-of-sight lengthscale of the cluster at that
$b_{\perp}$. By taking their ratio and re-arranging we can make a crude
approximation for the mean plasma temperature at that physical offset,

$\displaystyle\langle T_{e}(b_{\perp})\rangle$
$\displaystyle\approx\frac{m_{e}\,c^{2}}{\sigma_{T}\,k_{B}}\,\frac{y_{sz}}{\textup{DM}_{ICM}}$
(11) $\displaystyle=1.15\times
10^{7}\,\mathrm{K}\,\left(\frac{y_{SZ}}{10^{-6}}\right)\left(\frac{\rm
DM}{250\,\frac{\rm pc}{\rm cm^{3}}}\right)^{-1}$ (12)

We estimate the projected $y_{sz}$ at each cluster’s $b_{\perp}$ from our fits
to the Planck data described in Section 2. This gives $y_{SZ}=(3.31\pm
1.36)\times 10^{-6}$ for Abell 2310 at 520 kpc and $y_{SZ}=(6.80\pm
3.03)\times 10^{-7}$ for Abell 2311 at 870 kpc. Plugging these values into Eq.
12, we find $\langle k_{B}\,T_{e}\rangle\approx 0.8-3.9$ keV for Abell 2310,
in agreement with the expected electron temperature for a cluster of similar
mass at that impact parameter (Vikhlinin et al., 2005; Pratt et al., 2007).
This is the first time halo gas temperature has been measured using fast radio
bursts. For Abell 2311 at 870 kpc we find $\langle k_{B}\,T_{e}\rangle\approx
0.6-16$ keV along that line of sight. The large range in temperature is
primarily due to the uncertainty in ICM DM for FRB 20220509G.

While it is hard to match the statistical precision of an X-ray spectroscopic
temperature measurement, there are benefits to using FRB DMs to derive gas
temperature: With FRBs we do not need to account for “clumping” effects due to
the $n^{2}_{e}$ dependence (Eckert et al., 2015), the temperature will be
approximately mass-weighted rather than the more complicated weighting
intrinsic to spectroscopic measurements (Mazzotta et al., 2004), and current
X-ray facilities are generally not sensitive beyond $\sim$ $R_{500}$. The
obvious drawbacks of using FRBs are that we have only a single sightline and
the DM contribution of the IGM, Milky Way, and the host galaxy must be
modelled. The former will be alleviated by FRB surveys with high areal
density, providing multiple sightlines through individual halos. The latter
may be aided by cross-correlation (e.g. (Madhavacheril et al., 2019; chi,
2021)), which are less sensitive to host DM contamination. In Section 5 we
describe how future surveys will allow for statistical FRB/cluster studies.

##  4 IllustrisTNG Cluster Simulations

Figure 6: Four galaxy clusters from the TNG300-1 simulation whose masses are
similar to those of Abell 2310 and Abell 2311. The top row show gas surface
density within 2 Mpc of the cluster center. The green and blue circles
represent the impact parameter of FRB 20220509G and FRB 20220914A,
respectively. The bottom row shows DMICM as a function of impact parameter,
$b_{\perp}$, with error bars for the two observed cluster FRBs. The solid
purple line is the median DM over fifty azimuthal angles and the shaded region
shows the $90\%$ limits at that $b_{\perp}$. The curves assume the FRB is
embedded halfway in the ICM, i.e. $l_{LOS}=0$.

We use the IllustrisTNG simulation TNG300-1 (Nelson et al., 2019) to estimate
typical DM values of the ICM as a function of impact parameter. We seek also
to estimate the variance between galaxy clusters of similar mass, and variance
within a cluster for different position angle at fixed impact parameter.

We first extract cylinders of length 300 Mpc and radius 5 Mpc from the
simulation box that contain massive halos. These allow us to estimate not only
the ICM contribution to DM, but also the IGM along that sightline. We then
calculate gas properties for each cell in that cylinder and estimate free
electron density as,

$n_{e}=f_{e}\,\rho_{g}\,X_{H}\,/m_{p},$ (13)

where $f_{e}$ is the free electron abundance, $\rho_{g}$ is gas density,
$X_{H}$ is hydrogen abundance, and $m_{p}$ is the proton mass. We take $X_{H}$
to be 0.75. The $i^{th}$ cell’s contribution to the total DM is,

$\mathrm{DM}_{i}=n^{i}_{e}\,\Delta r_{i}\,(1+z_{i})^{-1},$ (14)

where $\Delta r_{i}$ is the distance through the cell at an impact parameter
$b_{i}$. The cell’s redshift is $z_{i}$. For cellsize, $\Delta x$, $\Delta
r_{i}=2\sqrt{\Delta x^{2}-b^{2}_{i}}$. The total DM is then $\Sigma DM_{i}$
for all cells that are intersected by the FRB.

We compute DM profiles for all halos in TNG300-1 that have
$M_{500}>10^{13.5}\,M_{\odot}$. In Figure 6 we show four galaxy clusters with
masses comparable to the masses of host clusters of FRB 20220509G and FRB
20220914A. The blue and green data points in the bottom row correspond to the
estimated ICM contribution to the two FRB DMs, which agree well with the
expected range at their respective impact parameters. There is significant
variance within a cluster even at a fixed impact parameter, particularly
beyond the virial radius (corresponding to $\approx 1500$ kpc given
$R_{500}\approx 800$ kpc for these clusters). There is also some scatter
between clusters, but the DM curves are roughly consistent. The mean values in
DM vs. $b_{\perp}$ (solid purple lines in Figure 6) are also in agreement with
analytic models for the cluster gas density (Vikhlinin et al., 2005; Prochaska
& Zheng, 2019).

Compared to simulations of the CGM or gas in galaxy groups, cluster
simulations are in relatively good agreement with one another as well as with
observations (Oppenheimer et al., 2021). As the sophistication of cosmological
MHD simulations progresses, they will be an invaluable tool for understanding
the properties of FRBs that are impacted by cluster gas. This is especially
true for magnetic field inference from FRB RMs and for gas temperatures
outside of $R_{500}$, as outlined in the following section.

##  5 Discussion

###  5.1 Beyond the virial radius

Outside of the virial radii of galaxy clusters, plasma is difficult to observe
via X-ray. FRB DMs, however, are more sensitive to this gas due to the $n_{e}$
(rather than $n_{e}^{2}$) dependence, and can constrain to ICM and WHIM on the
outskirts of clusters. Fujita et al. (2017) have shown that by combining FRB
DMs with the pressure profiles from SZ observations, the temperature profile
of the WHIM can be obtained beyond $1.5$ $R_{200}$.

In future FRB surveys, large numbers of localized FRBs will produce DM maps
with high areal density, intersecting individual clusters along multiple
sightlines. For example, the proposed DSA-2000 survey will spend roughly $5\%$
of its time on deep-drilling fields that overlap with Rubin, XMM-LSS, Extended
Chandra Deep Field-South, COSMOS deep fields (Hallinan et al., 2019b). This
will lead to roughly 500 FRBs in just $\sim$ 10 deg2. Nearly every massive
galaxy cluster out to $z=0.3$ will be intersected by at least one FRB
sightline. We will have a wealth of multiwavelength data in this field,
including SZ data and deep X-ray observations. Such a dataset will allow us to
constrain the magnetic field in the ICM and the density profile in the WHIM,
as well as gas temperatures outside of $R_{500}$. However, from Figure 6 we
see substantial azimuthal and inter-cluster variance in DM at large radii.
Analyses of the gas beyond $R_{500}$ ought to be done in tandem with
cosmological MHD simulations.

###  5.2 Prevalence of cluster FRBs

Roughly 5$\%$ of sightlines from FRBs at $z\approx 0.5$ are expected to
intersect galaxy clusters in the foreground (Prochaska & Zheng, 2019).
However, if an FRB sightline has a projected offset from a cluster that is
less than $R_{200}$, it is more likely that the FRB came from the cluster
itself than from behind it, assuming the rate of FRBs is related to stellar
mass and not just star formation. This is because the overdensity of galaxies
within massive halos is enough to counter the larger volume behind the galaxy
cluster. Using $R_{200}\approx 1$ Mpc, the comoving volume in region of a cone
behind a redshift 0.25 cluster out to $z=0.5$ is $\sim$ $7\times 10^{3}$ Mpc3.
Assuming a galaxy number density of roughly $10^{-2}$ Mpc-3 (White et al.,
2011), the volume behind the cluster should have only $\mathcal{O}(70)$
galaxies, compared with $10^{2-3}$ galaxies in the cluster. We note again that
this rough estimate assumes cluster galaxies are as likely as non-cluster
galaxies to produce FRBs. We have also ignored luminosity function
considerations, which make FRBs behind the cluster to be more difficult to
detect because they are less bright. It is therefore unsurprising that the
first two localized FRBs that are known to be impacted by the ICM have come
from member galaxies of clusters and not from behind clusters.

We have cross-matched twelve sources localized by the DSA-110 with cluster
catalogs and found two FRBs that reside in galaxy clusters. This suggests the
fraction of FRBs from galaxy clusters is $f_{cFRB}=0.17^{+0.36}_{-0.12}$,
using a 90% Poissonian confidence interval. We do not include other localized
FRBs because we are not aware of concerted efforts to cross-match those FRB
positions with clusters.

The large value of $f_{cFRB}$ has interesting implications for FRBs detected
at other surveys, and on our interpretation of observables such as the FRB DM
distribution. CHIME/FRB detects $\mathcal{O}(10^{3})$ FRBs per year, without
sufficient localization precision to identify a host galaxy. They may
therefore already have detected hundreds of sources that reside in galaxy
clusters. The host ICM could then dominate the high-DM tail of the total
observed DM distribution (James et al., 2022), which would otherwise be
interpreted as the most distant sources. Even with arcminute localizations, a
careful statistical cross-match of CHIME/FRB sources with galaxy cluster
catalogs could reveal this signal.

###  5.3 FRB progenitor implications

FRB 20220509G is the first source to belong to an early-type galaxy. This fits
an emerging picture that FRBs can be produced in a variety of environments,
including dense star forming regions, globular clusters, and pristine
environments with little HII (Tendulkar et al., 2017; Marcote et al., 2020;
Pastor-Marazuela et al., 2021; Kirsten et al., 2022; Niu et al., 2022b). The
full implications of FRB 20220509G’s quiescent host will be fleshed out by
Sharma et al. (in prep.). If more FRBs are localized to cluster galaxies with
low rates of star formation, then progenitor models must explain evolutionary
channels that can produce FRBs in the absence of recent core-collapse
supernovae. This would be promising for FRB applications research, as early-
type galaxies are not expected to have significant magnetoionic plasma in
their ISM or HII regions near the source, alleviating the problem of
disentangling host DM, RM, and scattering from cosmological contributions.

##  6 Conclusion

We have discovered two fast radio bursts sources that reside in massive galaxy
clusters. The host galaxy of FRB 20220914A is a member of cluster Abell 2310,
whose ICM dominates the DM budget of the FRB. We have combined the DM of FRB
20220914A with SZ observations of Abell 2310 to make the first estimate of the
mean line-of-sight temperature of gas using an FRB. FRB 20220509G belongs to
an early-type galaxy (Sharma et al., in prep.) at a projected offset of 870
kpc from the center of cluster Abell 2311. That cluster’s ICM is found to
contribute 16–172 pc cm-3 to the FRB DM, which is consistent with analytic
models and simulations of the ICM for a cluster with mass $M_{500}\approx
1.5-2\times 10^{14}M_{\odot}$. Polarization analysis of the burst found
significant Faraday rotation. Assuming this RM originates in the ICM, we
constrain the mean line-of-sight magnetic field strength to be 0.75-7 $\mu$G
in the intracluster gas. Roughly 17$\%$ of our first sample of localized FRBs
were found to reside in galaxy clusters. While we expect this fraction to come
down with time, galaxy clusters will likely play a significant role in
upcoming FRB surveys, particularly in attempts at mapping out the Universe’s
baryons.

The authors thank staff members of the Owens Valley Radio Observatory and the
Caltech radio group, including Kristen Bernasconi, Stephanie Cha-Ramos, Sarah
Harnach, Tom Klinefelter, Lori McGraw, Corey Posner, Andres Rizo, Michael
Virgin, Scott White, and Thomas Zentmyer. Their tireless efforts were
instrumental to the success of the DSA-110. The DSA-110 is supported by the
National Science Foundation Mid-Scale Innovations Program in Astronomical
Sciences (MSIP) under grant AST-1836018. We acknowledge use of the VLA
calibrator manual and the radio fundamental catalog. Some of the data
presented herein were obtained at the W. M. Keck Observatory, which is
operated as a scientific partnership among the California Institute of
Technology, the University of California and the National Aeronautics and
Space Administration. The Observatory was made possible by the generous
financial support of the W. M. Keck Foundation. We thank Ryuichi Takahashi and
Weiwei Xu for helpful discussions and materials related to their overlapping
work. We also thank Nicholas Battaglia for useful discussion. Keck:I (LRIS),
Keck:II (ESI)

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