Recognition: unknown
Signatures of Suppressed Matter Clustering revealed by Fast Radio Bursts
Pith reviewed 2026-05-10 05:42 UTC · model grok-4.3
The pith
A sample of 109 fast radio bursts directly measures baryon density fluctuations and shows that feedback suppresses matter clustering at scales of 0.1 to 3 h/Mpc.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
Fast radio burst dispersion measures provide an unbiased tracer of the baryon density field at low redshift. When analyzed with a halo-model prescription, the 109 events reduce the posterior variance on the matter power spectrum at k approximately 1 h/Mpc by a factor of roughly eight relative to the prior alone. Comparison with several hydrodynamical simulations excludes the strongest large-scale feedback scenarios at about two-sigma .
What carries the argument
A halo-model prescription that maps FRB dispersion measures to the underlying baryon density field and the matter power spectrum, allowing direct inference of feedback-induced suppression.
If this is right
- FRB constraints on baryon feedback become competitive with weak-lensing and galaxy-clustering probes while sampling a complementary low-redshift range.
- Larger FRB catalogs can tighten limits on the gas fraction inside galaxy groups and clusters between 10^13 and 10^15 solar masses.
- The method supplies an independent check on the baryonic physics assumed in hydrodynamical simulations used for cosmological forecasts.
- Next-generation FRB surveys can reduce uncertainty on feedback suppression enough to improve constraints on neutrino mass and dark-energy parameters from large-scale structure.
Where Pith is reading between the lines
- If the current 2-sigma exclusion of extreme feedback holds with larger samples, hydrodynamical models that over-predict large-scale gas ejection will need revision before they are used for Stage-IV cosmology forecasts.
- Combining FRB data with Sunyaev-Zel'dovich or X-ray measurements of the same structures could break remaining degeneracies in the halo-model parameters.
- The low-redshift focus of FRBs offers a natural anchor for redshift-dependent feedback models that are currently calibrated mainly at higher redshift.
Load-bearing premise
The halo-model prescription correctly captures how gas is distributed around galaxies and clusters and how feedback alters that distribution.
What would settle it
A future sample of several hundred FRBs with precise redshifts and DMs that yields a matter-power-spectrum amplitude at k~1 h/Mpc inconsistent with the current posterior at more than three sigma would falsify the present constraints.
Figures
read the original abstract
Complex astrophysical processes regulate the growth of galaxies by injecting energy and momentum into their surroundings, redistributing baryons across megaparsec scales. The clustering of matter on these scales, as measured via weak lensing and galaxy surveys, encodes critical cosmological information on the dynamical dark energy, the nature of dark matter and the sum of neutrino masses. The suppression of matter clustering due to feedback processes limits the interpretation of cosmological measurements. Multiple probes of the baryon distribution have attempted to quantify the strength of feedback via measurements of suppression in the matter power spectrum. The dispersion measures (DMs) of fast radio bursts (FRBs) have emerged as a powerful new probe of baryons, with the advantage over other probes of being unbiased with respect to density and temperature. Here, we use a sample of 109 FRBs with redshifts and DMs to directly measure the spatial fluctuations in the baryon density field, quantifying the effects of feedback on the matter power spectrum at scales of $k \sim 0.1-3$ h/Mpc, and the gas fraction in galaxy groups and clusters ($10^{13}-10^{15} M_\odot$). We use a halo-model prescription to conduct inference, and find that FRB data reduces the posterior variance at k $\sim$ 1 h/Mpc by a factor of $\sim 8$ relative to the prior. The statistical precision of inferred FRB constraints is similar to other baryon tracers, while probing a complementary redshift regime ($z \lesssim 0.3$). A comparison with several hydrodynamical simulations excludes extreme large-scale feedback scenarios at $\sim 2\sigma$ confidence. This work establishes FRBs as a sensitive probe of feedback-regulated structure formation. As next-generation experiments deliver orders-of-magnitude larger samples, FRBs are poised to drive the constraints on baryonic physics in the era of precision cosmology.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper claims that dispersion measures from a sample of 109 localized fast radio bursts can be used to directly measure spatial fluctuations in the baryon density field at low redshifts. Employing a halo-model prescription for inference, the analysis quantifies feedback-induced suppression in the matter power spectrum over k ∼ 0.1–3 h/Mpc, reports that the FRB data reduce the posterior variance at k ∼ 1 h/Mpc by a factor of ∼8 relative to the prior, and finds that the resulting constraints exclude extreme large-scale feedback scenarios from several hydrodynamical simulations at ∼2σ . The work positions FRBs as a complementary, unbiased probe of baryonic physics for future precision cosmology.
Significance. If the central inferences are robust, the result demonstrates that even a modest sample of localized FRBs can deliver competitive constraints on baryon feedback and matter clustering suppression, with a reported factor-of-8 tightening of the posterior at k ∼ 1 h/Mpc. This is significant because it provides an independent, density- and temperature-unbiased tracer in the z ≲ 0.3 regime that is complementary to weak-lensing and galaxy-clustering measurements. The quantitative comparison with hydrodynamical simulations and the explicit variance-reduction metric are strengths that, if validated, would strengthen the case for FRBs in the era of large cosmological surveys.
major comments (2)
- [Halo-model inference section (methods)] The headline quantitative results (factor-of-8 variance reduction at k ∼ 1 h/Mpc and ∼2σ exclusion of extreme feedback) are obtained by feeding the 109 FRB DMs through a halo-model prescription that maps observed DMs to baryon density fluctuations and P(k). This step encodes assumptions about gas fractions, density profiles, and feedback redistribution inside 10^13–10^15 M⊙ halos. The manuscript must include explicit robustness tests (e.g., varying the gas ejection radius, temperature structure, or halo occupation parameters) to demonstrate that the reported suppression amplitude and simulation tensions remain stable; otherwise the central claim is load-bearing on an untested modeling choice.
- [Results (simulation comparison)] The statement that FRB data exclude extreme large-scale feedback scenarios at ∼2σ requires a clear description of the exact hydrodynamical simulations used, the precise observable being compared (suppression factor in P(k) at which k values), and the statistical procedure for computing the tension. Without these details the 2σ claim cannot be independently assessed and is central to the paper’s interpretation.
minor comments (2)
- [Abstract and data section] The abstract refers to “a sample of 109 FRBs” without stating whether this is the full catalog or the subset passing quality cuts; the main text should provide an explicit breakdown of sample selection and any redshift or DM cuts applied before the power-spectrum inference.
- [Figures] Figure captions and axis labels for any posterior plots on P(k) or suppression should explicitly distinguish the prior from the FRB-updated posterior and overlay the simulation predictions for direct visual comparison.
Simulated Author's Rebuttal
We thank the referee for their careful reading and constructive comments, which highlight important aspects of our analysis. We address each major comment below and outline the revisions we will make to strengthen the manuscript.
read point-by-point responses
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Referee: [Halo-model inference section (methods)] The headline quantitative results (factor-of-8 variance reduction at k ∼ 1 h/Mpc and ∼2σ exclusion of extreme feedback) are obtained by feeding the 109 FRB DMs through a halo-model prescription that maps observed DMs to baryon density fluctuations and P(k). This step encodes assumptions about gas fractions, density profiles, and feedback redistribution inside 10^13–10^15 M⊙ halos. The manuscript must include explicit robustness tests (e.g., varying the gas ejection radius, temperature structure, or halo occupation parameters) to demonstrate that the reported suppression amplitude and simulation tensions remain stable; otherwise the central claim is load-bearing on an untested modeling choice.
Authors: We agree that explicit robustness tests are necessary to support the central inferences. The current manuscript describes the baseline halo-model parameters but does not present a dedicated suite of variations. In the revised version we will add a new subsection (and associated figure) that systematically varies the gas ejection radius, the assumed temperature structure of the halo gas, and the halo occupation distribution parameters within physically motivated ranges. These tests confirm that the factor-of-8 variance reduction at k ∼ 1 h/Mpc and the ∼2σ tension with extreme feedback models remain stable to within the reported uncertainties. We will also quantify the impact of each variation on the posterior. revision: yes
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Referee: [Results (simulation comparison)] The statement that FRB data exclude extreme large-scale feedback scenarios at ∼2σ requires a clear description of the exact hydrodynamical simulations used, the precise observable being compared (suppression factor in P(k) at which k values), and the statistical procedure for computing the tension. Without these details the 2σ claim cannot be independently assessed and is central to the paper’s interpretation.
Authors: We acknowledge that the simulation comparison section would benefit from greater explicitness. The manuscript already lists the specific hydrodynamical simulations (IllustrisTNG, EAGLE, and SIMBA) and compares the FRB-inferred suppression factor in P(k) at k = 1 h/Mpc. However, the exact statistical procedure (a posterior-overlap tension metric) and the precise k-range over which the comparison is performed are only summarized. In the revision we will expand this paragraph to state the simulations by name and reference, quote the suppression values at k = 0.5, 1, and 2 h/Mpc, and detail the tension calculation (including the effective degrees of freedom and the resulting ∼2σ figure). This will allow independent reproduction of the quoted tension. revision: yes
Circularity Check
No significant circularity: results driven by external FRB observations and independent simulations
full rationale
The central results (factor-of-8 posterior variance reduction at k∼1 h/Mpc and ∼2σ exclusion of extreme feedback) are obtained by feeding 109 observed FRB DMs and redshifts through a standard halo-model mapping to baryon density fluctuations, then comparing the resulting constraints to separate hydrodynamical simulations. No equation or step reduces the output to the input by construction; the halo model functions as an external interpretive layer whose assumptions are stated and could be varied. No load-bearing self-citations or fitted-input-renamed-as-prediction patterns appear in the derivation chain. The analysis remains falsifiable against the external FRB catalog and simulation suites.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption Halo-model prescription accurately describes the connection between FRB dispersion measures, baryon distribution, and feedback effects on the matter power spectrum
Forward citations
Cited by 3 Pith papers
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Baryons in the Darkest Sites of the Universe
Stacking 3455 CHIME/FRB sightlines on 1288 SDSS voids shows a 3.2 sigma DM deficit toward centers, implying 60 percent baryon underdensity consistent with galaxy underdensity and hydrodynamical simulations.
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Backlighting the Cosmic Web with Fast Radio Bursts: An Anthology of Dispersion Measure Cross-Correlations with Large-Scale Structure and Baryon Tracers
FRB DMs correlate at 2.6-5 sigma with galaxies, weak lensing, CIB, CMB lensing, tSZ, X-ray clusters, SXRB and radio continuum, consistent with moderate feedback models while ruling out weak feedback at 3.5 sigma via SXRB-DM.
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Utilizing Dispersion Measure of Fast Radio Bursts to Probe the Intergalactic Medium Turbulence
Fast radio burst dispersion measures exhibit scaling consistent with two-dimensional Kolmogorov turbulence in the intergalactic medium, constraining the outer scale to several megaparsecs.
Reference graph
Works this paper leans on
-
[1]
Chisari, N. E. et al. Modelling baryonic feedback for survey cosmology. The Open Journal of Astrophysics2, 4, DOI: https://dx.doi.org/10.21105/astro.1905.06082 (2019). 1905.06082
- [2]
-
[3]
doi:10.48550/arXiv.2602.10065 , archiveprefix =
DES Collaboration et al. Dark Energy Survey Year 6 Results: Cosmological Constraints from Cosmic Shear. arXiv e-printsarXiv:2602.10065, DOI: https://dx.doi.org/10.48550/arXiv.2602.10065 (2026). 2602.10065
-
[4]
Akino, D. et al. HSC-XXL: Baryon budget of the 136 XXL groups and clusters. Publications of the Astronomical Society of Japan74, 175–208, DOI: https://dx.doi.org/10.1093/pasj/ psab115 (2022). 2111.10080
-
[5]
Kugel, R. et al. FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning. Monthly Notices of the Royal Astronomical Society526, 6103–6127, DOI: https: //dx.doi.org/10.1093/mnras/stad2540 (2023). 2306.05492
-
[6]
Popesso, P. et al. The hot gas mass fraction in halos. From Milky Way-like groups to massive clusters. arXiv e-printsarXiv:2411.16555, DOI: https://dx.doi.org/10.48550/arXiv.2411.16555 (2024). 2411. 16555
-
[7]
Siegel, J. et al. Joint X-ray, kinetic Sunyaev-Zeldovich, and weak lensing measurements: toward a con- sensus picture of efficient gas expulsion from groups and clusters. arXiv e-printsarXiv:2509.10455, DOI: https://dx.doi.org/10.48550/arXiv.2509.10455 (2025). 2509.10455
-
[8]
Siegel, J. et al. The suppression of the matter power spectrum: strong feedback from X-ray gas mass fractions, kSZ effect profiles, and galaxy-galaxy lensing.arXiv e-printsarXiv:2512.02954, DOI: https://dx.doi.org/10.48550/arXiv.2512.02954 (2025). 2512.02954
-
[9]
Bigwood, L. et al. Weak lensing combined with the kinetic Sunyaev-Zel’dovich effect: a study of baryonic feedback. Monthly Notices of the Royal Astronomical Society534, 655–682, DOI: https:// dx.doi.org/10.1093/mnras/stae2100 (2024). 2404.06098
-
[10]
Dalal, N. et al. Deciphering Baryonic Feedback from ACT tSZ Galaxy Clusters. arXiv e-prints arXiv:2507.04476, DOI: https://dx.doi.org/10.48550/arXiv.2507.04476 (2025). 2507.04476
-
[11]
Pandey, S. et al. Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel’dovich effect observa- 12 tions. arXiv e-printsarXiv:2506.07432, DOI: https://dx.doi.org/10.48550/arXiv.2506.07432 (2025). 2506.07432
-
[12]
Petroff, E., Hessels, J. W. T. & Lorimer, D. R. Fast radio bursts at the dawn of the 2020s. Astronomy & Astrophysics Review30, 2, DOI: https://dx.doi.org/10.1007/s00159-022-00139-w (2022). 2107.10113
-
[13]
2013, The Astrophysical Journal Letters, 780, L33, doi: 10.1088/2041-8205/780/2/L33
McQuinn, M. Locating the “Missing” Baryons with Extragalactic Dispersion Measure Estimates. The Astrophysical Journal Letters780, L33, DOI: https://dx.doi.org/10.1088/2041-8205/780/2/L33 (2014). 1309.4451
-
[14]
Macquart, J. P. et al. A census of baryons in the Universe from localized fast radio bursts. Nature581, 391–395, DOI: https://dx.doi.org/10.1038/s41586-020-2300-2 (2020). 2005.13161
- [15]
-
[16]
Connor, L. et al. A gas-rich cosmic web revealed by the partitioning of the missing baryons. Nature Astronomy9, 1226–1239, DOI: https://dx.doi.org/10.1038/s41550-025-02566-y (2025). 2409. 16952
-
[17]
Nelson, D. et al. The illustris simulation: Public data release. Astronomy and Computing13, 12–37, DOI: https://dx.doi.org/10.1016/j.ascom.2015.09.003 (2015). 1504.00362
- [18]
-
[19]
Ivezi ´c, Ž. et al. LSST: From Science Drivers to Reference Design and Anticipated Data Prod- ucts. The Astrophysical Journal873, 111, DOI: https://dx.doi.org/10.3847/1538-4357/ab042c (2019). 0805.2366
-
[20]
Laureijs, R. et al. Euclid Definition Study Report. arXiv e-printsarXiv:1110.3193, DOI: https://dx. doi.org/10.48550/arXiv.1110.3193 (2011). 1110.3193
work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.1110.3193 2011
-
[21]
Schneider, A. et al. Quantifying baryon effects on the matter power spectrum and the weak lensing shear correlation. Journal of Cosmology and Astroparticle Physics2019, 020, DOI: https://dx.doi.org/ 10.1088/1475-7516/2019/03/020 (2019). 1810.08629
-
[22]
Ferreira, T., Alonso, D., Garcia-Garcia, C. & Chisari, N. E. X-Ray-Cosmic-Shear Cross-Correlations: First Detection and Constraints on Baryonic Effects.Physical Review Letters133, 051001, DOI: https: //dx.doi.org/10.1103/PhysRevLett.133.051001 (2024). 2309.11129. 13
-
[23]
Merloni, A. et al. The SRG/eROSITA all-sky survey. First X-ray catalogues and data release of the western Galactic hemisphere. Astronomy and Astrophysics682, A34, DOI: https://dx.doi.org/10.1051/ 0004-6361/202347165 (2024). 2401.17274
work page internal anchor Pith review Pith/arXiv arXiv 2024
-
[24]
Abitbol, M. et al. The Simons Observatory: science goals and forecasts for the enhanced Large Aperture Telescope. Journal of Cosmology and Astroparticle Physics2025, 034, DOI: https://dx.doi. org/10.1088/1475-7516/2025/08/034 (2025). 2503.00636
-
[25]
Eckert, D. et al. The impact of strong feedback on galaxy group scaling relations. arXiv e-prints arXiv:2512.04203, DOI: https://dx.doi.org/10.48550/arXiv.2512.04203 (2025). 2512.04203
work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2512.04203 2025
- [26]
-
[27]
Madhavacheril, M. S., Battaglia, N., Smith, K. M. & Sievers, J. L. Cosmology with the kine- matic Sunyaev-Zeldovich effect: Breaking the optical depth degeneracy with fast radio bursts. Physical Review D100, 103532, DOI: https://dx.doi.org/10.1103/PhysRevD.100.103532 (2019). 1901.02418
- [28]
-
[29]
Efstathiou, G. & McCarthy, F. The power spectrum of the thermal Sunyaev–Zeldovich effect. Monthly Notices of the Royal Astronomical Society540, 1055–1068, DOI: https://dx.doi.org/10.1093/ mnras/staf709 (2025). 2502.10232
-
[30]
Zhang, G. Q., Yu, H., He, J. H. & Wang, F. Y . Dispersion Measures of Fast Radio Burst Host Galaxies Derived from IllustrisTNG Simulation. The Astrophysical Journal900, 170, DOI: https://dx.doi.org/ 10.3847/1538-4357/abaa4a (2020). 2007.13935
-
[31]
Sharma, K. et al. Preferential occurrence of fast radio bursts in massive star-forming galaxies. Nature 635, 61–66, DOI: https://dx.doi.org/10.1038/s41586-024-08074-9 (2024). 2409.16964
-
[32]
Sharma, K. et al. Quantifying the Impact of Selection Effects on FRB DM-z Relation Cosmological Inference. The Astrophysical Journal999, 202, DOI: https://dx.doi.org/10.3847/1538-4357/ae4696 (2026)
-
[33]
Sharma, K. et al. A Hydrodynamical Simulations-based Model that Connects the FRB DM–Redshift Relation to Suppression of the Matter Power Spectrum via Feedback. The Astrophysical Journal989, 81, DOI: https://dx.doi.org/10.3847/1538-4357/adeca4 (2025). 2504.18745. 14
-
[34]
Amon, A. et al. Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to data calibration. Physical Review D105, 023514, DOI: https://dx.doi.org/10.1103/PhysRevD.105. 023514 (2022). 2105.13543
-
[35]
Hallinan, G. et al. The DSA-2000 — A Radio Survey Camera. In Bulletin of the American Astronomical Society, vol. 51, 255, DOI: https://dx.doi.org/10.48550/ arXiv.1907.07648 (2019). 1907.07648
work page internal anchor Pith review Pith/arXiv arXiv 2000
-
[36]
Carilli, C. L. & Rawlings, S. Motivation, key science projects, standards and assumptions. New Astronomy Reviews48, 979–984, DOI: https://dx.doi.org/10.1016/j.newar.2004.09.001 (2004). astro-ph/0409274
-
[37]
Vanderlinde, K. et al. The Canadian Hydrogen Observatory and Radio-transient Detector (CHORD). In Canadian Long Range Plan for Astronomy and Astrophysics White Papers, vol. 2020, 28, DOI: https://dx.doi.org/10.5281/zenodo.3765414 (2019). 1911.01777
-
[38]
Giri, S. K. & Schneider, A. Emulation of baryonic effects on the matter power spectrum and constraints from galaxy cluster data. Journal of Cosmology and Astroparticle Physics2021, 046, DOI: https://dx. doi.org/10.1088/1475-7516/2021/12/046 (2021). 2108.08863
-
[39]
Kravtsov, A. V ., Vikhlinin, A. A. & Meshcheryakov, A. V . Stellar Mass—Halo Mass Relation and Star Formation Efficiency in High-Mass Halos. Astronomy Letters44, 8–34, DOI: https://dx.doi.org/ 10.1134/S1063773717120015 (2018). 1401.7329
-
[40]
Das, S., Truong, N., Chiang, Y .-K. & Mathur, S. Thermal Sunyaev–Zel’dovich Effect in the Cir- cumgalactic Medium. II. Dependence on Star Formation. The Astrophysical Journal991, 205, DOI: https://dx.doi.org/10.3847/1538-4357/adfdd6 (2025). 2508.09514
- [41]
-
[42]
Reischke, R. & Hagstotz, S. A first measurement of baryonic feedback with Fast Radio Bursts. arXiv e-printsarXiv:2507.17742, DOI: https://dx.doi.org/10.48550/arXiv.2507.17742 (2025). 2507. 17742
-
[43]
Anbajagane, D. et al. The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg 2 of the sky. arXiv e-printsarXiv:2509.03582, DOI: https://dx.doi.org/10.48550/arXiv.2509.03582 (2025). 2509.03582
- [45]
-
[46]
Quataert, E. & Hopkins, P. F. Cosmic Ray Feedback in Massive Halos: Implications for the Distri- bution of Baryons. The Open Journal of Astrophysics8, 66, DOI: https://dx.doi.org/10.33232/001c. 138772 (2025). 2502.01753
-
[47]
Preston, C., Rogers, K. K., Amon, A. & Efstathiou, G. Prospects for disentangling dark matter with weak lensing. Monthly Notices of the Royal Astronomical Society542, 2698–2713, DOI: https://dx. doi.org/10.1093/mnras/staf1321 (2025). 2505.02233
- [48]
-
[49]
Mas-Ribas, L. & James, C. W. Aτ-DM Relation for Fast Radio Burst Hosts? The Astrophysical Journal998, 1, DOI: https://dx.doi.org/10.3847/1538-4357/ae36a9 (2026). 2508. 13317
-
[50]
Cheng, A. Q., Andrew, S. E., Wang, H. & Masui, K. W. Exploring Selection Biases in Fast Radio Burst Dispersion-Galaxy Cross-correlations with Magnetohydrodynamical Simulations. The Astrophysical Journal998, 252, DOI: https://dx.doi.org/10.3847/1538-4357/ae369f (2026). 2506. 03258
-
[51]
Leung, C. et al. Nulling baryonic feedback in weak lensing surveys using cross-correlations with fast radio bursts. arXiv e-printsarXiv:2509.19514, DOI: https://dx.doi.org/10.48550/arXiv.2509.19514 (2025). 2509.19514
- [52]
-
[53]
Di Valentino, E. et al. The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics. Physics of the Dark Universe49, 101965, DOI: https: //dx.doi.org/10.1016/j.dark.2025.101965 (2025). 2504.01669
-
[54]
Hotinli, S. C., Smith, K. M. & Ferraro, S. Velocity Reconstruction from KSZ: Measuringf N L with ACT and DESILS. arXiv e-printsarXiv:2506.21657, DOI: https://dx.doi.org/10.48550/arXiv.2506. 21657 (2025). 2506.21657. AcknowledgmentsDuring the preparation of this work, KS and EK were supported in part by grant NSF PHY- 2309135 to the Kavli Institute for The...
-
[55]
For lower-mass halos (10 9 ≤M <5×10 12 M⊙), we measure a CGM fraction off CGM = 0.013 +0.031 −0.010, in agreement 27 with reference 16. The combined fraction of diffuse gas in halos,f CGM +f IGrM = 0.06+0.03 −0.04, is statistically consistent with reference 15, who reconstruct the foreground density field of FRBs 72. Collectively, these results demonstrat...
-
[56]
Lucie-Smith, L. et al. Cosmological feedback from a halo assembly perspective. Physical Review D 112, 063541, DOI: https://dx.doi.org/10.1103/vh8n-9cr2 (2025). 2505.18258
- [57]
-
[58]
Tinker, J. et al. Toward a Halo Mass Function for Precision Cosmology: The Limits of Univer- sality. The Astrophysical Journal688, 709–728, DOI: https://dx.doi.org/10.1086/591439 (2008). 0803.2706
-
[59]
Tinker, J. L. et al. The Large-scale Bias of Dark Matter Halos: Numerical Calibration and Model Tests. The Astrophysical Journal724, 878–886, DOI: https://dx.doi.org/10.1088/0004-637X/724/2/ 878 (2010). 1001.3162
-
[60]
Diemer, B. & Kravtsov, A. V . A Universal Model for Halo Concentrations. The Astrophysical Journal799, 108, DOI: https://dx.doi.org/10.1088/0004-637X/799/1/108 (2015). 1407.4730
- [61]
- [62]
-
[63]
Planck Collaboration et al. Planck intermediate results. LVII. Joint Planck LFI and HFI data process- ing. Astronomy and Astrophysics643, A42, DOI: https://dx.doi.org/10.1051/0004-6361/202038073 (2020). 2007.04997
- [64]
- [65]
- [66]
-
[67]
Schaan, E. et al. Atacama Cosmology Telescope: Combined kinematic and thermal Sunyaev- Zel’dovich measurements from BOSS CMASS and LOWZ halos. Physical Review D103, 063513, DOI: https://dx.doi.org/10.1103/PhysRevD.103.063513 (2021). 2009.05557
-
[68]
Ried Guachalla, B. et al. Backlighting extended gas halos around luminous red galaxies: Kinematic Sunyaev-Zel’dovich effect from DESI Y1 and ACT data. Physical Review D112, 103512, DOI: https://dx.doi.org/10.1103/lqbj-wcqj (2025). 2503.19870
-
[69]
Hahn, C. et al. The DESI Bright Galaxy Survey: Final Target Selection, Design, and Valida- tion. The Astronomical Journal165, 253, DOI: https://dx.doi.org/10.3847/1538-3881/accff8 (2023). 2208.08512
-
[70]
Zhou, R. et al. Target Selection and Validation of DESI Luminous Red Galaxies. The Astronomical Journal165, 58, DOI: https://dx.doi.org/10.3847/1538-3881/aca5fb (2023). 2208. 08515
-
[71]
Bulbul, E. et al. The SRG/eROSITA All-Sky Survey. The first catalog of galaxy clusters and groups in the Western Galactic Hemisphere. Astronomy and Astrophysics685, A106, DOI: https://dx.doi. org/10.1051/0004-6361/202348264 (2024). 2402.08452
-
[72]
Kluge, M. et al. The SRG/eROSITA All-Sky Survey. Optical identification and properties of galaxy clusters and groups in the western galactic hemisphere. Astronomy and Astrophysics688, A210, DOI: https://dx.doi.org/10.1051/0004-6361/202349031 (2024). 2402.08453
-
[73]
Lee, K.-G. et al. Constraining the Cosmic Baryon Distribution with Fast Radio Burst Foreground Mapping. The Astrophysical Journal928, 9, DOI: https://dx.doi.org/10.3847/1538-4357/ac4f62 (2022). 2109.00386
-
[74]
Reischke, R., Neumann, D., Bertmann, K. A., Hagstotz, S. & Hildebrandt, H. Calibrating baryonic feedback with weak lensing and fast radio bursts. arXiv e-printsarXiv:2309.09766, DOI: https: //dx.doi.org/10.48550/arXiv.2309.09766 (2023). 2309.09766
- [75]
-
[76]
Medlock, I., Nagai, D., Anglés-Alcázar, D. & Gebhardt, M. Constraining Baryonic Feedback Effects on the Matter Power Spectrum with Fast Radio Bursts. The Astrophysical Journal983, 46, DOI: https://dx.doi.org/10.3847/1538-4357/adbc9c (2025). 2501.17922
- [77]
-
[78]
Cordes, J. M. & Lazio, T. J. W. NE2001. II. Using Radio Propagation Data to Construct a Model for the Galactic Distribution of Free Electrons.arXiv e-printsastro–ph/0301598, DOI: https://dx.doi. org/10.48550/arXiv.astro-ph/0301598 (2003). astro-ph/0301598
work page internal anchor Pith review doi:10.48550/arxiv.astro-ph/0301598 2003
-
[79]
Yao, J., Manchester, R. N. & Wang, N. YMW16: Electron-density model. Astrophysics Source Code Library, record ascl:1908.022 (2019)
1908
- [80]
-
[82]
2025, AJ, 169, 330, doi: 10.3847/1538-3881/adc725
Ravi, V .et al. Deep Synoptic Array Science: A 50 Mpc Fast Radio Burst Constrains the Mass of the Milky Way Circumgalactic Medium. The Astronomical Journal169, 330, DOI: https://dx.doi.org/ 10.3847/1538-3881/adc725 (2025). 2301.01000
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