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arxiv: 2510.09463 · v3 · submitted 2025-10-10 · 🌌 astro-ph.CO · astro-ph.HE· astro-ph.IM· gr-qc

Generalized Distributions of Host Dispersion Measures in the Fast Radio Burst Cosmology

Jing-Yi Jia , Da-Chun Qiang , Lin-Yu Li , Hao Wei This is my paper

Pith reviewed 2026-05-18 07:51 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.HEastro-ph.IMgr-qc
keywords fast radio burstsdispersion measureHubble constanthost galaxyintergalactic mediumbaryon feedbackcosmology
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The pith

Generalizing the distribution of host galaxy dispersion measures allows fast radio bursts to produce a Hubble constant consistent with CMB and supernova results without narrow priors on feedback.

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

The paper establishes that more flexible probability distributions for the dispersion measure contribution from host galaxies can resolve inconsistencies in deriving the Hubble constant from fast radio bursts. Using a sample of 125 localized FRBs, the authors show that models with adjustable location and scale parameters for the host distribution are statistically preferred and yield H0 values matching those from Planck and SH0ES. This approach avoids pushing the intergalactic baryon fraction to its upper limit or requiring artificial constraints on the feedback parameter. A sympathetic reader would care because it opens a path for FRBs to serve as an independent cosmological probe that arbitrates the Hubble tension.

Core claim

By replacing the fixed distribution of DM_host with a generalized form that includes free location parameter ℓ and scale parameter e^μ, the analysis of 125 localized FRBs produces Hubble constant values consistent with Planck 2018 and SH0ES across the considered models. These generalized models are strongly preferred over the version with a narrow prior on F according to Bayesian evidence and information criteria, without needing to alter the IGM distribution parameter σ_Δ.

What carries the argument

Generalized probability distribution for DM_host with free location ℓ and scale e^μ, which flexibly models host galaxy contributions to dispersion measures and enables consistent extraction of H0.

If this is right

  • H0 derived from FRBs aligns with Planck 2018 and SH0ES values for all tested models.
  • The intergalactic baryon fraction f_IGM no longer approaches its upper bound of 1.
  • Generalized host models are strongly preferred by Bayesian evidence and Akaike/Bayesian information criteria.
  • FRBs become usable as an independent H0 probe without artificially tight priors on the feedback parameter F.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Future increases in the number of localized FRBs could tighten constraints on the host distribution parameters themselves.
  • The same generalization technique might apply to other line-of-sight probes that separate host and intergalactic contributions.
  • This result points to the need for more detailed modeling of galaxy-to-galaxy variation in dispersion measures when using transient sources for cosmology.

Load-bearing premise

The chosen generalized functional form for the DM_host distribution with free location and scale parameters correctly captures the true host contributions across the FRB sample without systematic bias.

What would settle it

A larger sample of localized FRBs where the generalized DM_host models still produce an H0 value inconsistent with both Planck and SH0ES would falsify the claim that this generalization resolves the tension.

Figures

Figures reproduced from arXiv: 2510.09463 by Da-Chun Qiang, Hao Wei, Jing-Yi Jia, Lin-Yu Li.

Figure 1
Figure 1. Figure 1: FIG. 1: The 1 [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2: The same as in Fig. 1, but for the narrow priors used by M [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3: The same as in Fig. 1, but for the Loc2s0 model. See Sec. [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4: The same as in Fig. 1, but for the Loc3s0 model. See Sec. [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5: The same as in Fig. 1, but for the Loc2s model. See Sec. I [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6: The same as in Fig. 1, but for the Loc3s model. See Sec. I [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7: The same as in Fig. 1, but for the Loclin model. See Sec. [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8 [PITH_FULL_IMAGE:figures/full_fig_p013_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9: The same as in Fig. 1, but for the Mu2s model. See Sec. IV [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: FIG. 10: The same as in Fig. 1, but for the Mu3s model. See Sec. I [PITH_FULL_IMAGE:figures/full_fig_p015_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: FIG. 11: The same as in Fig. 1, but for the Mulin model. See Sec. [PITH_FULL_IMAGE:figures/full_fig_p016_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: FIG. 12 [PITH_FULL_IMAGE:figures/full_fig_p017_12.png] view at source ↗
read the original abstract

Fast radio bursts (FRBs) can provide a measure of the Hubble constant $H_0$ that is independent of the constraints set by the cosmic microwave background (CMB) and the type Ia supernovae (SNIa), thereby arbitrating the Hubble tension. In the literature, the methodology proposed by Macquart et al. has been widely used, in which the contributions to the dispersion measure (DM) from the intergalactic medium (IGM, $\rm DM_{IGM}$) and the host galaxy ($\rm DM_{host}$) are described by probability distribution functions. Within the Macquart et al. methodology, it has been found that the parameter $F$, which quantifies the strength of the baryon feedback in galaxies, must be bound by an artificially narrow prior to result in a Hubble constant $H_0$ that is consistent with the ones derived from the CMB and SNIa studies. A recent study using ${\cal O}(100)$ localized FRBs found that this also causes the fraction of baryon mass in the IGM, $f_{\rm IGM}$, to approach its upper bound of 1. In the present work, using 125 localized FRBs, we find an unusually low $H_0$ when using a model with a loose prior on $F$. This model is in fact strongly preferred to the model with the narrow prior when considering the Bayesian evidence and the Akaike and Bayesian information criteria. Instead of modifying $\sigma_\Delta=Fz^{-0.5}$ in the distribution of $\rm DM_{IGM}$, we explore an alternative method of resolving the tension by generalizing the distribution of $\rm DM_{host}$ with varying location and scale parameters $\ell$ and $e^\mu$, respectively. We find that $H_0$ can be well consistent with the ones of Planck 2018 and SH0ES for all the models considered in this work, while these generalized models are all strongly preferred to the model with a narrow prior on $F$. Our findings indicate that more realistic distributions of $\rm DM_{host}$ could be the key to using FRBs as an independent measure of $H_0$.

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

3 major / 2 minor

Summary. The paper analyzes 125 localized fast radio bursts to infer H0 by generalizing the DM_host probability distribution with free location ℓ and scale e^μ parameters. It reports that these generalized models yield H0 values consistent with Planck 2018 and SH0ES, are strongly preferred over narrow-prior-on-F models by Bayesian evidence, AIC, and BIC, and that more realistic DM_host modeling may be key to using FRBs as an independent H0 probe without artificial constraints on the IGM feedback parameter F.

Significance. If the central claim holds, the work offers a path to FRB-based H0 measurements that avoid the narrow F prior and resulting f_IGM boundary issues noted in prior studies. The explicit model comparison via evidence and information criteria, together with the focus on host-galaxy dispersion modeling, strengthens the case for FRBs as a cosmological tool independent of CMB and SNIa.

major comments (3)
  1. [Methods / Data sample] The manuscript states that generalized models are preferred by Bayesian evidence, AIC, and BIC and produce consistent H0, yet the data-selection criteria for the 125 events, the precise likelihood implementation, and any posterior predictive checks are not detailed. This prevents verification that the reported preference is not driven by unmodeled selection effects or redshift-dependent biases absorbed into ℓ and e^μ.
  2. [Model description and Results] While the Macquart IGM model (including F-dependent scatter) is held fixed and only the host term is generalized, the two extra parameters (ℓ, e^μ) can in principle compensate for residual IGM inhomogeneity or selection systematics. With O(100) events and no reported comparison to hydrodynamical simulations or the subset of FRBs with direct host-galaxy DM estimates, it is unclear whether the improvement reflects genuine host physics.
  3. [Discussion / H0 inference] The claim that H0 remains consistent with Planck and SH0ES across all generalized models is central, but the quantitative robustness depends on whether the chosen functional form for the generalized DM_host distribution introduces systematic bias at the redshifts of the sample. A direct test against the narrow-F model on the same likelihood would clarify if the evidence gain is proportionate to the added flexibility.
minor comments (2)
  1. [Model section] Notation for the generalized parameters (ℓ and e^μ) should be introduced with explicit functional forms in the text rather than only in equations, to improve readability for readers unfamiliar with the host DM parameterization.
  2. [Figures] Figure captions and axis labels for the posterior distributions or evidence comparisons could be expanded to include the exact model names and prior choices for direct comparison.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us improve the clarity and robustness of the manuscript. We address each major comment below and indicate the revisions made.

read point-by-point responses

  1. Referee: [Methods / Data sample] The manuscript states that generalized models are preferred by Bayesian evidence, AIC, and BIC and produce consistent H0, yet the data-selection criteria for the 125 events, the precise likelihood implementation, and any posterior predictive checks are not detailed. This prevents verification that the reported preference is not driven by unmodeled selection effects or redshift-dependent biases absorbed into ℓ and e^μ.

    Authors: We agree that additional methodological details are required for full reproducibility and verification. In the revised manuscript we have expanded the Methods section with a clear description of the data-selection criteria applied to assemble the sample of 125 localized FRBs, the explicit form of the likelihood function used for the Bayesian inference, and the results of posterior predictive checks. These checks show that the model reproduces the observed DM distribution without obvious residual trends that could be absorbed into the host-galaxy parameters. revision: yes

  2. Referee: [Model description and Results] While the Macquart IGM model (including F-dependent scatter) is held fixed and only the host term is generalized, the two extra parameters (ℓ, e^μ) can in principle compensate for residual IGM inhomogeneity or selection systematics. With O(100) events and no reported comparison to hydrodynamical simulations or the subset of FRBs with direct host-galaxy DM estimates, it is unclear whether the improvement reflects genuine host physics.

    Authors: We acknowledge that the extra parameters could in principle absorb some IGM or selection effects. Nevertheless, the best-fit values of ℓ and e^μ produce DM_host distributions that are consistent with independent observational constraints on host-galaxy contributions. In the revision we have added a discussion comparing the inferred distributions to results from hydrodynamical simulations in the literature and to the limited subset of FRBs with direct host DM measurements. A dedicated new simulation campaign tailored to our exact sample lies beyond the scope of the present work. revision: partial

  3. Referee: [Discussion / H0 inference] The claim that H0 remains consistent with Planck and SH0ES across all generalized models is central, but the quantitative robustness depends on whether the chosen functional form for the generalized DM_host distribution introduces systematic bias at the redshifts of the sample. A direct test against the narrow-F model on the same likelihood would clarify if the evidence gain is proportionate to the added flexibility.

    Authors: We have performed the suggested direct comparison by re-fitting the narrow-F model and all generalized models on identical data and likelihood implementations. The revised manuscript now includes these results, which confirm that H0 remains consistent with Planck 2018 and SH0ES while the generalized models are strongly preferred by Bayesian evidence, AIC, and BIC. We also verified that residuals show no systematic redshift-dependent trends attributable to the functional form of the host distribution. revision: yes

Circularity Check

0 steps flagged

No significant circularity; derivation fits data against external benchmarks

full rationale

The paper fits a two-parameter generalization (location ℓ and scale e^μ) of the DM_host distribution to 125 localized FRB events while holding the Macquart IGM model fixed, then infers H0 and compares it to independent Planck 2018 and SH0ES values. Model preference is assessed via Bayesian evidence, AIC, and BIC on the data likelihood. No equation or step reduces the reported H0 consistency or model preference to a quantity defined solely by the fitted host parameters or to a self-citation chain; the central result remains an empirical fit to external observations rather than a definitional or self-referential tautology.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that the chosen parametric form for DM_host is physically motivated and that the 125 localized FRBs are representative; two new free parameters are introduced to control location and scale of that distribution.

free parameters (2)
  • ℓ
    Location parameter of the generalized DM_host distribution, fitted to the FRB sample
  • e^μ
    Scale parameter of the generalized DM_host distribution, fitted to the FRB sample
axioms (1)
  • domain assumption Dispersion measure contributions from IGM and host follow the probability distributions assumed in the Macquart framework
    Invoked when constructing the likelihood for the observed DM values

pith-pipeline@v0.9.0 · 5958 in / 1311 out tokens · 38849 ms · 2026-05-18T07:51:10.793768+00:00 · methodology

discussion (0)

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Forward citations

Cited by 2 Pith papers

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Reference graph

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