pith. sign in

arxiv: 2509.07097 · v2 · submitted 2025-09-08 · 🌌 astro-ph.GA

Constraining Gas Mass Fractions in Galaxy Groups and Clusters with the First CHIME/FRB Outrigger

Adam E. Lanman , Sunil Simha , Kiyoshi W. Masui , J. Xavier Prochaska , Rachel Darlinger , Fengqiu Adam Dong , B. M. Gaensler , Ronniy C. Joseph
show 11 more authors
Jane Kaczmarek Lordrick Kahinga Afrokk Khan Calvin Leung Lluis Mas-Ribas Swarali Shivraj Patil Aaron B. Pearlman Mawson Sammons Kaitlyn Shin Kendrick Smith Haochen Wang
This is my paper

Pith reviewed 2026-05-18 17:41 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords fast radio burstsdispersion measuregalaxy clustersgalaxy groupsgas mass fractionintracluster mediumbaryon distributionCHIME/FRB
0
0 comments X

The pith

Fast radio bursts passing through galaxy groups and clusters constrain their gas mass fractions by matching dispersion measures to halo models.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper demonstrates that localized fast radio bursts provide a new tool to measure the gas content in galaxy groups and clusters. Their dispersion measures, which depend on electron density, are compared to models of halo gas distributions after accounting for other contributions. This allows constraints on the gas mass fraction at different radii in these halos. Such measurements are valuable because feedback from galaxies strongly affects gas in group-scale halos, deviating from simple scaling relations, and traditional probes like X-rays are weak there. Future catalogs of such events will enable broader tests of how baryons are distributed in the universe.

Core claim

Three fast radio bursts from the first CHIME/FRB Outrigger sample have host galaxies within or behind galaxy clusters and groups. The contribution to their dispersion measures from the intragroup or intracluster medium is calculated by integrating various halo density profiles, with uncertainties from halo mass and host distance included. For the higher mass systems, these predicted DM values align with the remaining extragalactic DM. In the case of FRB 20230703A intersecting multiple groups with a low total DM, this comparison yields constraints on the gas mass fraction f_g as a function of radius, which agree with recent eROSITA findings at R_500 while showing mild tension at R_200 with X-

What carries the argument

Dispersion measure from fast radio bursts, integrated along the line of sight through halo density profiles, to constrain gas mass fraction f_g(R).

Load-bearing premise

Halo mass estimates and the line-of-sight distances to the host galaxies must be known with sufficient precision that their uncertainties do not dominate the dispersion measure budget.

What would settle it

A new FRB with accurately determined host redshift and associated halo mass whose measured dispersion measure falls well outside the predicted range from the gas fraction models would falsify the current constraints.

Figures

Figures reproduced from arXiv: 2509.07097 by Aaron B. Pearlman, Adam E. Lanman, Afrokk Khan, B. M. Gaensler, Calvin Leung, Fengqiu Adam Dong, Haochen Wang, Jane Kaczmarek, J. Xavier Prochaska, Kaitlyn Shin, Kendrick Smith, Kiyoshi W. Masui, Lluis Mas-Ribas, Lordrick Kahinga, Mawson Sammons, Rachel Darlinger, Ronniy C. Joseph, Sunil Simha, Swarali Shivraj Patil.

Figure 1
Figure 1. Figure 1: The fields of each FRB host in the Second Digitized Sky Survey (DSS2)(Lasker et al. 1996). Member galaxies are indicated by color-coded circles, and the R500 virial radii of each cluster is shown by the dashed circles. We omit TullyN08 from the field of FRB 20230703A, since its proximity makes it cover a much larger angle of the sky than the other two groups. For Abell 924, the virial radius is shown aroun… view at source ↗
Figure 2
Figure 2. Figure 2: Comoving positions of galaxies (points) and filaments (lines) within 10 Mpc/h of the center of NSCS-J1218, from Tempel et al. (2014). Galaxies are color-coded by the nearest filament. Galaxies that are members of group 15955 of Tempel et al. (2012), which is equivalent to NSCS-J1218, are marked in black. Cartesian positions are relative to the group center, with the Z direction along the line of sight to F… view at source ↗
Figure 3
Figure 3. Figure 3: Comparison of ICM electron density models for fg,500 = 1 and M500 = 1015 M⊙. Curves for the mNFW profile are shown for different concentration parameters. The two values (3.07 and 4.14) correspond with halo masses of 1014 and 1015 M⊙ using the Magneticum Mv – c, respectively, though the curve for each is still shown for 1014 M⊙. Vertical lines mark the impact parameters of each FRB (indicated by the last f… view at source ↗
Figure 4
Figure 4. Figure 4: Halocentric coordinates to for computing DMICM. The impact factor (b), radius (y), and line of sight position parameter (s) are all kept in units of R500. The integral is taken from the nearest point on the sightline that is within the halo (denoted by smin), to the each sampled host galaxy position. When the host galaxy is confidently behind the halo, the integral is taken to smax = −smin. As empirical fi… view at source ↗
Figure 5
Figure 5. Figure 5: Baryon fractions vs. radius for each model for different halo concentrations, normalized so that fg,500 = 1. The vertical black lines mark the locations of R200, which depends on the concentration parameter. We use the c500 and z values listed in [PITH_FULL_IMAGE:figures/full_fig_p015_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Distributions of DMICM for each model for each group along the sightline of FRB 20230703A. For WH24-J1218, samples are taken over line-of-sight distance smax within the group. DMs for distances smax > 0 (on the “far side” of the cluster center) are histogrammed with a solid line, while “near side” samples (smax < 0) are plotted with a dashed line. The y-axis on the plot is much larger because the number of… view at source ↗
Figure 7
Figure 7. Figure 7: Distributions of DMICM for each model for the sightline of FRB 20230203A. As in [PITH_FULL_IMAGE:figures/full_fig_p018_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Upper limits on fg(Rmax) for each model, assuming the same fg for all three halos along the FRB 20230703A sightline. For conservative upper limits, these use the lower 1 σ bound of total DMICM, and only including the near-side peak of DM values for WH24-J12188 and that all three. The value at each radius ignores any contribution to DMICM from outside of Rmax, as well as any DM contributions from the host g… view at source ↗
Figure 9
Figure 9. Figure 9: Numerically-integrated values of nˆ0 for the isothermal and cool-core UPP over a range of masses. APPENDIX A. UPP NORMALIZATION The UPP, being empirically-derived, implicitly assumes a value of fg,500. To make the baryon fraction a free parameter, we need to normalize the densities such that fg,500 = 1, using the value fB = 0.175 assumed in Arnaud et al. (2010). The baryon mass density is related to the pr… view at source ↗
read the original abstract

In recent years, localized fast radio bursts (FRBs) have emerged as a powerful tool to study the structure of the baryonic matter in the universe. Their dispersion measures (DMs) scale linearly with electron density independent of gas temperature, making them particularly well suited to studying the intragroup medium (IGrM), where traditional probes such as X-ray emission and the SZ effect are weak. Evidence suggests that the gas in group mass halos ($M_{500}$ ~ $10^{13}$ -- $10^{14}$ M$_\odot$) is strongly affected by galactic feedback, causing deviations from cluster scaling relations. Three FRBs from the first CHIME/FRB Outrigger sample come from host galaxies found within or behind galaxy clusters and groups. We estimate the DM contribution of each ICM/IGrM by integrating different halo density profiles, accounting for uncertainties in halo mass and the host galaxy line of sight distance. For the more massive halos, predicted cluster DMs agree with the extragalactic DM budget. One burst, FRB 20230703A, intersects three groups yet has a low extragalactic DM. By comparing model predictions with the measured DM, we constrain the gas mass fraction $f_g(R)$ in these halos. Comparing with published $M$--$f_g$ relations, we find consistency with recent eROSITA results at $R_{500}$ and mild tension at $R_{200}$ and with earlier X-ray--based relations. As CHIME/FRB Outriggers build a large catalog of localized FRBs, many additional sightlines through groups and clusters will be obtained. These will enable systematic tests of intragroup and intracluster gas properties and sharpen constraints on the distribution of baryons in massive halos.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. The manuscript uses localized FRBs from the CHIME/FRB Outrigger sample to probe the intragroup/intracluster medium. Focusing on FRB 20230703A, whose sightline intersects three groups, the authors integrate halo density profiles (normalized by gas mass fraction f_g) to predict the dispersion measure contribution, incorporating uncertainties in halo mass and line-of-sight host distance. They then compare the modeled DM to the observed extragalactic DM to derive constraints on f_g(R) at R_500 and R_200, finding consistency with recent eROSITA M–f_g relations at R_500 and mild tension at R_200 (as well as with earlier X-ray relations). The work positions FRBs as a complementary probe for lower-mass halos where feedback effects are prominent and anticipates larger samples for systematic tests.

Significance. If the modeling and uncertainty propagation are robust, the result provides an independent, temperature-insensitive constraint on baryonic content in group-scale halos, where X-ray and SZ signals are weak. This is a genuine strength: the approach is falsifiable with future localized FRBs and directly tests deviations from self-similar scaling due to feedback. The explicit use of multiple density profiles and external mass priors is noted as a transparent choice.

major comments (1)
  1. [Section describing FRB 20230703A modeling and f_g derivation] The central claim (constraining f_g(R) and reporting consistency/tension with eROSITA) rests on the DM comparison for FRB 20230703A. Because predicted DM scales linearly with f_g × M_halo and the path length through the halo depends on the precise impact parameter and host distance, the manuscript must demonstrate that the full 0.2–0.5 dex uncertainties on published M_500/M_200 and the line-of-sight geometry are propagated into the allowed f_g interval (e.g., via Monte Carlo sampling of the posterior). If these are treated only as fixed values or partial ranges, the reported mild tension at R_200 cannot be distinguished from the null case of an uninformative constraint.
minor comments (2)
  1. [Abstract and methods] The abstract states that uncertainties in halo mass and host distance are accounted for, but a short methods paragraph or appendix table listing the adopted priors, integration limits, and density-profile variants (e.g., NFW vs. beta-model) would improve reproducibility.
  2. [Results section on FRB 20230703A] Figure or table presenting the DM budget breakdown (host, IGM, halo contributions) for FRB 20230703A would help readers assess whether the group DM is the dominant term or whether other components could absorb the tension.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive feedback. We address the major comment in detail below, clarifying our approach to uncertainty propagation while agreeing to improve the presentation in revision.

read point-by-point responses

  1. Referee: [Section describing FRB 20230703A modeling and f_g derivation] The central claim (constraining f_g(R) and reporting consistency/tension with eROSITA) rests on the DM comparison for FRB 20230703A. Because predicted DM scales linearly with f_g × M_halo and the path length through the halo depends on the precise impact parameter and host distance, the manuscript must demonstrate that the full 0.2–0.5 dex uncertainties on published M_500/M_200 and the line-of-sight geometry are propagated into the allowed f_g interval (e.g., via Monte Carlo sampling of the posterior). If these are treated only as fixed values or partial ranges, the reported mild tension at R_200 cannot be distinguished from the null case of an uninformative constraint.

    Authors: We thank the referee for this important clarification request. The manuscript does propagate the full uncertainties on halo mass (0.2–0.5 dex) and line-of-sight geometry when deriving the f_g constraints. We sample M_500 and M_200 from the published posterior distributions (or uniform ranges spanning the quoted uncertainties when posteriors are unavailable), and we vary the impact parameter and host distance within the geometric bounds allowed by the observed host redshift and the group/cluster positions. These samples are used to compute a distribution of predicted DM contributions for each trial value of f_g; the resulting DM distribution is then compared to the measured extragalactic DM to obtain the posterior on f_g at R_500 and R_200. The reported mild tension at R_200 persists after this marginalization: even when halo masses are drawn from the upper end of their uncertainty ranges, the median predicted DM still exceeds the observed value for f_g values that match the eROSITA relation at R_500. To make this procedure fully transparent, we will expand the methods section with an explicit description of the Monte Carlo sampling, report the number of samples used, and add a supplementary figure showing example DM distributions before and after marginalization. revision: partial

Circularity Check

0 steps flagged

No significant circularity; constraints derived from independent FRB DM data and external profiles

full rationale

The paper's central derivation integrates literature halo density profiles (normalized by gas mass fraction f_g and halo mass M_halo) along the line of sight to predict DM contributions, then compares these predictions to the observed extragalactic DM for FRB 20230703A and other events while propagating uncertainties in M_halo and host distance. The resulting allowed f_g(R) intervals at R_500 and R_200 are checked against published external M--f_g relations from eROSITA and X-ray studies. No quoted step equates a model prediction to its own fitted input by construction, invokes a self-citation as the sole justification for a uniqueness claim, or renames an internal fit as an independent result. The chain remains self-contained because the DM measurement and external density profiles supply independent inputs that are not redefined in terms of the output f_g constraints.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Constraints rest on standard assumptions about halo density profiles and mass estimates drawn from prior literature rather than new derivations.

axioms (2)
  • domain assumption Standard halo density profiles (e.g., NFW or beta-model) accurately describe the intragroup and intracluster gas distribution for DM integration.
    Invoked when estimating DM contribution by integrating profiles for each halo.
  • domain assumption Halo masses and host-galaxy line-of-sight distances can be estimated with uncertainties that do not overwhelm the extragalactic DM signal.
    Stated when accounting for uncertainties in halo mass and distance for the three FRBs.

pith-pipeline@v0.9.0 · 5964 in / 1383 out tokens · 36178 ms · 2026-05-18T17:41:29.990467+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The limits of feedback from active galactic nuclei

    astro-ph.GA 2026-05 unverdicted novelty 6.0

    AGN feedback creates a mass-independent entropy ceiling that allows outflows to escape halos only below M_200m = 10^13.7 M_sun, explaining depleted gas in groups versus near-cosmic fractions in clusters.

  2. Great Walls of Cosmic Baryons in the Northern Sky

    astro-ph.CO 2026-04 unverdicted novelty 6.0

    FRB dispersion measures reveal a large-scale excess of ionized gas in the northern sky spatially aligned with the Ursa Major supercluster.

  3. Probing Primordial Black Holes with upcoming Radio Telescopes: a case study for LOFAR2.0, FAST Core Array and BINGO

    astro-ph.CO 2026-04 unverdicted novelty 4.0

    LOFAR2.0, FAST Core Array and BINGO can constrain the PBH dark matter fraction f_PBH below 0.16-0.39 for masses above 10^{-2} to 10 solar masses via FRB lensing statistics.

Reference graph

Works this paper leans on

103 extracted references · 103 canonical work pages · cited by 3 Pith papers · 4 internal anchors

  1. [1]

    - [1] #1 = = ^ ^ ^ .\!\!^ d .\!\!^ h .\!\!^ m .\!\!^ s .\!\!^ @mss

    thebibliography [1] 20pt to REFERENCES 6pt =0pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command Each re...

    work page doi:10.5281/zenodo.831784 2019

  2. [2]

    H., Wilson, G., & Klypin, A

    Abdullah , M. H., Wilson , G., & Klypin , A. 2018, , 861, 22, 10.3847/1538-4357/aac5db

    work page doi:10.3847/1538-4357/aac5db 2018

  3. [3]

    , keywords =

    Abdullah , M. H., Wilson , G., Klypin , A., et al. 2020, , 246, 2, 10.3847/1538-4365/ab536e

    work page doi:10.3847/1538-4365/ab536e 2020

  4. [4]

    , keywords =

    Abell , G. O., Corwin , Jr., H. G., & Olowin , R. P. 1989, , 70, 1, 10.1086/191333

    work page doi:10.1086/191333 1989

  5. [5]

    T., et al

    Aggarwal , K., Budav \'a ri , T., Deller , A. T., et al. 2021, , 911, 95, 10.3847/1538-4357/abe8d2

    work page doi:10.3847/1538-4357/abe8d2 2021

  6. [6]

    W., Evrard A

    Allen , S. W., Evrard , A. E., & Mantz , A. B. 2011, , 49, 409, 10.1146/annurev-astro-081710-102514

    work page doi:10.1146/annurev-astro-081710-102514 2011

  7. [7]

    doi:10.1093/mnras/stae1954 , eprint =

    Anderson , C. S., McClure-Griffiths , N. M., Rudnick , L., et al. 2024, , 533, 4068, 10.1093/mnras/stae1954

    work page doi:10.1093/mnras/stae1954 2024

  8. [8]

    W., Piffaretti, R., et al

    Arnaud , M., Pratt , G. W., Piffaretti , R., et al. 2010, , 517, A92, 10.1051/0004-6361/200913416

    work page doi:10.1051/0004-6361/200913416 2010

  9. [9]

    P., Tollerud, E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

    work page doi:10.1051/0004-6361/201322068 2013

  10. [10]

    arXiv.org , author =

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

    work page doi:10.3847/1538-3881/aabc4f 2018

  11. [11]

    The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package

    Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, , 935, 167, 10.3847/1538-4357/ac7c74

    work page internal anchor Pith review doi:10.3847/1538-4357/ac7c74 2022

  12. [12]

    2014, , 349, 415, 10.1007/s10509-013-1630-z

    Babyk , I., & Vavilova , I. 2014, , 349, 415, 10.1007/s10509-013-1630-z

    work page doi:10.1007/s10509-013-1630-z 2014

  13. [13]

    2012, , 545, A41, 10.1051/0004-6361/201219555

    Baldi , A., Ettori , S., Molendi , S., & Gastaldello , F. 2012, , 545, A41, 10.1051/0004-6361/201219555

    work page doi:10.1051/0004-6361/201219555 2012

  14. [14]

    X., Mannings , A

    Baptista , J., Prochaska , J. X., Mannings , A. G., et al. 2024, , 965, 57, 10.3847/1538-4357/ad2705

    work page doi:10.3847/1538-4357/ad2705 2024

  15. [15]

    2024, Physics of the Dark Universe, 45, 101526, 10.1016/j.dark.2024.101526

    Barbosa , D., von Marttens , R., Gonzalez , J., & Alcaniz , J. 2024, Physics of the Dark Universe, 45, 101526, 10.1016/j.dark.2024.101526

    work page doi:10.1016/j.dark.2024.101526 2024

  16. [16]

    Beck , R., & Gaensler , B. M. 2004, , 48, 1289, 10.1016/j.newar.2004.09.013

    work page doi:10.1016/j.newar.2004.09.013 2004

  17. [17]

    S., & Verdes-Montenegro , L

    Borthakur , S., Yun , M. S., & Verdes-Montenegro , L. 2010, , 710, 385, 10.1088/0004-637X/710/1/385

    work page doi:10.1088/0004-637x/710/1/385 2010

  18. [18]

    Statistical Properties of X-ray Clusters: Analytic and Numerical Comparisons

    Bryan , G. L., & Norman , M. L. 1998, , 495, 80, 10.1086/305262

    work page internal anchor Pith review doi:10.1086/305262 1998

  19. [19]

    2025, arXiv e-prints, arXiv:2502.11217, 10.48550/arXiv.2502.11217

    CHIME/FRB Collaboration , Amiri , M., Amouyal , D., et al. 2025, arXiv e-prints, arXiv:2502.11217, 10.48550/arXiv.2502.11217

    work page doi:10.48550/arxiv.2502.11217 2025

  20. [20]

    2025, Nature Astronomy, 9, 1226, doi: 10.1038/s41550-025-02566-y 31

    Connor , L., Ravi , V., Sharma , K., et al. 2025, Nature Astronomy, 10.1038/s41550-025-02566-y

    work page doi:10.1038/s41550-025-02566-y 2025

  21. [21]

    NE2001.I. A New Model for the Galactic Distribution of Free Electrons and its Fluctuations

    Cordes , J. M., & Lazio , T. J. W. 2002, arXiv e-prints, astro, 10.48550/arXiv.astro-ph/0207156

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.astro-ph/0207156 2002

  22. [22]

    2023, , 676, A127, 10.1051/0004-6361/202245308

    Damsted , S., Finoguenov , A., Clerc , N., et al. 2023, , 676, A127, 10.1051/0004-6361/202245308

    work page doi:10.1051/0004-6361/202245308 2023

  23. [23]

    J., Lang, D., et al

    Dey , A., Schlegel , D. J., Lang , D., et al. 2019, , 157, 168, 10.3847/1538-3881/ab089d

    work page doi:10.3847/1538-3881/ab089d 2019

  24. [24]

    A., Mirabal , N., Bregman , J

    Dupke , R. A., Mirabal , N., Bregman , J. N., & Evrard , A. E. 2007, , 668, 781, 10.1086/520708

    work page doi:10.1086/520708 2007

  25. [25]

    Eckert , D., Gaspari , M., Gastaldello , F., Le Brun , A. M. C., & O'Sullivan , E. 2021, Universe, 7, 142, 10.3390/universe7050142

    work page doi:10.3390/universe7050142 2021

  26. [26]

    2024, , 683, A205, 10.1051/0004-6361/202348038

    Epinat , B., Contini , T., Mercier , W., et al. 2024, , 683, A205, 10.1051/0004-6361/202348038

    work page doi:10.1051/0004-6361/202348038 2024

  27. [27]

    2009, , 501, 61, 10.1051/0004-6361/200810878

    Ettori , S., Morandi , A., Tozzi , P., et al. 2009, , 501, 61, 10.1051/0004-6361/200810878

    work page doi:10.1051/0004-6361/200810878 2009

  28. [28]

    E., Metzler , C

    Evrard , A. E., Metzler , C. A., & Navarro , J. F. 1996, , 469, 494, 10.1086/177798

    work page doi:10.1086/177798 1996

  29. [29]

    T., Ravi , V., Ocker , S

    Faber , J. T., Ravi , V., Ocker , S. K., et al. 2024, arXiv e-prints, arXiv:2405.14182, 10.48550/arXiv.2405.14182

    work page doi:10.48550/arxiv.2405.14182 2024

  30. [30]

    Ferreira , M., Holanda , R. F. L., Gonzalez , J. E., Cola c o , L. R., & Nunes , R. C. 2024, European Physical Journal C, 84, 1120, 10.1140/epjc/s10052-024-13468-0

    work page doi:10.1140/epjc/s10052-024-13468-0 2024

  31. [31]

    Survey, catalog, and cosmology of the X-ray luminosity function

    Finoguenov , A., Rykoff , E., Clerc , N., et al. 2020, , 638, A114, 10.1051/0004-6361/201937283

    work page doi:10.1051/0004-6361/201937283 2020

  32. [32]

    A., Magnier, E

    Flewelling , H. A., Magnier , E. A., Chambers , K. C., et al. 2020, , 251, 7, 10.3847/1538-4365/abb82d

    work page doi:10.3847/1538-4365/abb82d 2020

  33. [33]

    J., Peebles P

    Fukugita , M., Hogan , C. J., & Peebles , P. J. E. 1998, , 503, 518, 10.1086/306025

    work page doi:10.1086/306025 1998

  34. [34]

    , author =

    Ginsburg , A., Sip o cz , B. M., Brasseur , C. E., et al. 2019, , 157, 98, 10.3847/1538-3881/aafc33

    work page doi:10.3847/1538-3881/aafc33 2019

  35. [35]

    1998, , 505, 74, 10.1086/306157

    Girardi , M., Giuricin , G., Mardirossian , F., Mezzetti , M., & Boschin , W. 1998, , 505, 74, 10.1086/306157

    work page doi:10.1086/306157 1998

  36. [36]

    M., Goldberg , D

    Groener , A. M., Goldberg , D. M., & Sereno , M. 2016, , 455, 892, 10.1093/mnras/stv2341

    work page doi:10.1093/mnras/stv2341 2016

  37. [37]

    C., Harris , W

    Hou , A., Parker , L. C., Harris , W. E., & Wilman , D. J. 2009, , 702, 1199, 10.1088/0004-637X/702/2/1199

    work page doi:10.1088/0004-637x/702/2/1199 2009

  38. [38]

    Hu , W., & Kravtsov , A. V. 2003, , 584, 702, 10.1086/345846

    work page doi:10.1086/345846 2003

  39. [39]

    I., et al

    Huang , Y., Lee , K.-G., Libeskind , N. I., et al. 2025, , 538, 2785, 10.1093/mnras/staf417

    work page doi:10.1093/mnras/staf417 2025

  40. [40]

    M., Ravi V., Faber J., Sharma K., Sherman M., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2506.04186 , https://ui.adsabs.harvard.edu/abs/2025arXiv250604186H p

    Hussaini , M., Connor , L., Konietzka , R. M., et al. 2025, arXiv e-prints, arXiv:2506.04186, 10.48550/arXiv.2506.04186

    work page doi:10.48550/arxiv.2506.04186 2025

  41. [41]

    arXiv: 2208.00819 [astro-ph.CO]

    James , C. W., Ghosh , E. M., Prochaska , J. X., et al. 2022, , 516, 4862, 10.1093/mnras/stac2524

    work page doi:10.1093/mnras/stac2524 2022

  42. [42]

    1986, , 222, 323, 10.1093/mnras/222.2.323

    Kaiser , N. 1986, , 222, 323, 10.1093/mnras/222.2.323

    work page doi:10.1093/mnras/222.2.323 1986

  43. [43]

    S., Sorini D., Lee K.-G., Dav \'e R., 2024a, @doi [ ] 10.1093/mnras/stae525 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.529..537K 529, 537

    Khrykin , I. S., Sorini , D., Lee , K.-G., & Dav \'e , R. 2024 a , , 529, 537, 10.1093/mnras/stae525

    work page doi:10.1093/mnras/stae525 2024

  44. [44]

    S., et al., 2024b, @doi [ ] 10.3847/1538-4357/ad6567 , https://ui.adsabs.harvard.edu/abs/2024ApJ...973..151K 973, 151

    Khrykin , I. S., Ata , M., Lee , K.-G., et al. 2024 b , , 973, 151, 10.3847/1538-4357/ad6567

    work page doi:10.3847/1538-4357/ad6567 2024

  45. [45]

    S., Staveley-Smith, L., Westmeier, T., et al

    Koribalski , B. S., Staveley-Smith , L., Westmeier , T., et al. 2020, , 365, 118, 10.1007/s10509-020-03831-4

    work page doi:10.1007/s10509-020-03831-4 2020

  46. [46]

    V., & Borgani, S

    Kravtsov , A. V., & Borgani , S. 2012, , 50, 353, 10.1146/annurev-astro-081811-125502

    work page doi:10.1146/annurev-astro-081811-125502 2012

  47. [47]

    M., Doggett , J., McLean , B., et al

    Lasker , B. M., Doggett , J., McLean , B., et al. 1996, in Astronomical Society of the Pacific Conference Series, Vol. 101, Astronomical Data Analysis Software and Systems V, ed. G. H. Jacoby & J. Barnes , 88

    work page 1996

  48. [48]

    Le Brun , A. M. C., McCarthy , I. G., & Melin , J.-B. 2015, , 451, 3868, 10.1093/mnras/stv1172

    work page doi:10.1093/mnras/stv1172 2015

  49. [49]

    2008, , 486, 359, 10.1051/0004-6361:200809538

    Leccardi , A., & Molendi , S. 2008, , 486, 359, 10.1051/0004-6361:200809538

    work page doi:10.1051/0004-6361:200809538 2008

  50. [50]

    S., Huang Y., Prochaska J

    Lee , K.-G., Ata , M., Khrykin , I. S., et al. 2022, , 928, 9, 10.3847/1538-4357/ac4f62

    work page doi:10.3847/1538-4357/ac4f62 2022

  51. [51]

    S., Simha , S., et al

    Lee , K.-G., Khrykin , I. S., Simha , S., et al. 2023, , 954, L7, 10.3847/2041-8213/acefb5

    work page doi:10.3847/2041-8213/acefb5 2023

  52. [52]

    Lopes , P. A. A., de Carvalho , R. R., Gal , R. R., et al. 2004, , 128, 1017, 10.1086/423038

    work page doi:10.1086/423038 2004

  53. [53]

    Lopes , P. A. A., de Carvalho , R. R., Kohl-Moreira , J. L., & Jones , C. 2009, , 392, 135, 10.1111/j.1365-2966.2008.13962.x

    work page doi:10.1111/j.1365-2966.2008.13962.x 2009

  54. [54]

    H., & Schellenberger , G

    Lovisari , L., Reiprich , T. H., & Schellenberger , G. 2015, , 573, A118, 10.1051/0004-6361/201423954

    work page doi:10.1051/0004-6361/201423954 2015

  55. [55]

    I., et al

    Lyskova , N., Churazov , E., Khabibullin , I. I., et al. 2023, , 525, 898, 10.1093/mnras/stad2305

    work page doi:10.1093/mnras/stad2305 2023

  56. [56]

    P., et al., 2020, @doi [ ] 10.1038/s41586-020-2300-2 , https://ui.adsabs.harvard.edu/abs/2020Natur.581..391M 581, 391

    Macquart , J. P., Prochaska , J. X., McQuinn , M., et al. 2020, , 581, 391, 10.1038/s41586-020-2300-2

    work page doi:10.1038/s41586-020-2300-2 2020

  57. [57]

    B., Morris , R

    Mantz , A. B., Morris , R. G., Allen , S. W., et al. 2022, , 510, 131, 10.1093/mnras/stab3390

    work page doi:10.1093/mnras/stab3390 2022

  58. [58]

    2025, , 694, A207, 10.1051/0004-6361/202452028

    Marini , I., Popesso , P., Dolag , K., et al. 2025, , 694, A207, 10.1051/0004-6361/202452028

    work page doi:10.1051/0004-6361/202452028 2025

  59. [59]

    G., & Prochaska , J

    Mathews , W. G., & Prochaska , J. X. 2017, , 846, L24, 10.3847/2041-8213/aa8861

    work page doi:10.3847/2041-8213/aa8861 2017

  60. [60]

    Galactic star formation and accretion histories from matching galaxies to dark matter haloes

    Moster , B. P., Naab , T., & White , S. D. M. 2013, , 428, 3121, 10.1093/mnras/sts261

    work page Pith review doi:10.1093/mnras/sts261 2013

  61. [61]

    G., Power , C., & Robotham , A

    Murray , S. G., Power , C., & Robotham , A. S. G. 2013, Astronomy and Computing, 3, 23, 10.1016/j.ascom.2013.11.001

    work page doi:10.1016/j.ascom.2013.11.001 2013

  62. [62]

    F., Frenk C

    Navarro , J. F., Frenk , C. S., & White , S. D. M. 1997, , 490, 493, 10.1086/304888

    work page doi:10.1086/304888 1997

  63. [63]

    M., Kacprzak , G

    Nielsen , N. M., Kacprzak , G. G., Pointon , S. K., Churchill , C. W., & Murphy , M. T. 2018, , 869, 153, 10.3847/1538-4357/aaedbd

    work page doi:10.3847/1538-4357/aaedbd 2018

  64. [64]

    2000, A&AS, 143, 23, doi: 10.1051/aas:2000169

    Ochsenbein , F., Bauer , P., & Marcout , J. 2000, , 143, 23, 10.1051/aas:2000169

    work page doi:10.1051/aas:2000169 2000

  65. [65]

    1997, , 2, 309, 10.1016/S1384-1076(97)00021-3

    Pen , U.-L. 1997, , 2, 309, 10.1016/S1384-1076(97)00021-3

    work page doi:10.1016/s1384-1076(97)00021-3 1997

  66. [66]

    J., Wakker , B

    Pisano , D. J., Wakker , B. P., Wilcots , E. M., & Fabian , D. 2004, , 127, 199, 10.1086/380217

    work page doi:10.1086/380217 2004

  67. [67]

    Planck Collaboration , Ade , P. A. R., Aghanim , N., et al. 2013, , 550, A131, 10.1051/0004-6361/201220040

    work page doi:10.1051/0004-6361/201220040 2013

  68. [68]

    Planck 2015 results

    ---. 2016, , 594, A27, 10.1051/0004-6361/201525823

    work page doi:10.1051/0004-6361/201525823 2016

  69. [69]

    Aghanim, Y

    Planck Collaboration , Aghanim , N., Akrami , Y., et al. 2020, , 641, A6, 10.1051/0004-6361/201833910

    work page doi:10.1051/0004-6361/201833910 2020

  70. [70]

    2005, A&A, 433, 431, doi: 10.1051/0004-6361:20041915

    Popesso , P., Biviano , A., B \"o hringer , H., Romaniello , M., & Voges , W. 2005, , 433, 431, 10.1051/0004-6361:20041915

    work page doi:10.1051/0004-6361:20041915 2005

  71. [71]

    2024 a , arXiv e-prints, arXiv:2411.16555

    Popesso , P., Biviano , A., Marini , I., et al. 2024, arXiv e-prints, arXiv:2411.16555, 10.48550/arXiv.2411.16555

    work page doi:10.48550/arxiv.2411.16555 2024

  72. [72]

    W., Arnaud , M., Piffaretti , R., et al

    Pratt , G. W., Arnaud , M., Piffaretti , R., et al. 2010, , 511, A85, 10.1051/0004-6361/200913309

    work page doi:10.1051/0004-6361/200913309 2010

  73. [73]

    X., Zheng Y., 2019, @doi [ ] 10.1093/mnras/stz261 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485..648P 485, 648

    Prochaska , J. X., & Zheng , Y. 2019, , 485, 648, 10.1093/mnras/stz261

    work page doi:10.1093/mnras/stz261 2019

  74. [74]

    2019, , 486, 4001, 10.1093/mnras/stz1103

    Ragagnin , A., Dolag , K., Moscardini , L., Biviano , A., & D'Onofrio , M. 2019, , 486, 4001, 10.1093/mnras/stz1103

    work page doi:10.1093/mnras/stz1103 2019

  75. [75]

    J., Diaferio , A., Mohr , J

    Rines , K., Geller , M. J., Diaferio , A., Mohr , J. J., & Wegner , G. A. 2000, , 120, 2338, 10.1086/316811

    work page doi:10.1086/316811 2000

  76. [76]

    S., et al., 2014, @doi [ ] 10.1088/0004-637X/785/2/104 , http://adsabs.harvard.edu/abs/2014ApJ...785..104R 785, 104

    Rykoff , E. S., Rozo , E., Busha , M. T., et al. 2014, , 785, 104, 10.1088/0004-637X/785/2/104

    work page doi:10.1088/0004-637x/785/2/104 2014

  77. [77]

    S., et al., 2016, @doi [ ] 10.3847/0067-0049/224/1/1 , https://ui.adsabs.harvard.edu/abs/2016ApJS..224....1R 224, 1

    Rykoff , E. S., Rozo , E., Hollowood , D., et al. 2016, , 224, 1, 10.3847/0067-0049/224/1/1

    work page doi:10.3847/0067-0049/224/1/1 2016

  78. [78]

    A., Bravo-Alfaro , H., Pointecouteau , E., & Andernach , H

    Santiago-Bautista , I., Caretta , C. A., Bravo-Alfaro , H., Pointecouteau , E., & Andernach , H. 2020, , 637, A31, 10.1051/0004-6361/201936397

    work page doi:10.1051/0004-6361/201936397 2020

  79. [79]

    1996, , 48, L119, 10.1093/pasj/48.6.L119

    Sasaki , S. 1996, , 48, L119, 10.1093/pasj/48.6.L119

    work page doi:10.1093/pasj/48.6.l119 1996

  80. [80]

    2023, , 671, A57, 10.1051/0004-6361/202245138

    Seppi , R., Comparat , J., Nandra , K., et al. 2023, , 671, A57, 10.1051/0004-6361/202245138

    work page doi:10.1051/0004-6361/202245138 2023

Showing first 80 references.