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REVIEW 5 major objections 6 minor 2 cited by

Reinvestigation of Fast Radio Burst Host Galaxy and Event Rate Density

T0 review · 5 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read The paper argues that the unknown ionized-gas content of fast radio burst host galaxies is a dominant uncertainty in volumetric rate estimates, and that repeaters and non-repeaters currently show indistinguishable host-gas contributions.

desk verdict A useful, honest compilation with a modest MCMC result, but the central rate-versus-DMhost claim is largely built into an under-specified Vlimit boundary and needs a careful revision before the numbers can be taken at face value. read the letter →

arxiv 2411.09203 v2 pith:KL2RIWM2 submitted 2024-11-14 astro-ph.HE

Wenqi Ma , Zhifu Gao , Biaopeng Li , Chenhui Niu , Jumei Yao , Fayin Wang This is my paper · ORCID
classification astro-ph.HE
keywords fastradioburstsdispersionmeasurehostgalaxiesvolumetriceventratedensityrepeatersnon-repeatersFRBprogenitorstransients
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper argues that the amount of ionized gas in fast radio burst (FRB) host galaxies is a first-order uncertainty in measuring how often these bursts occur per cosmic volume, and that this uncertainty directly affects which stellar-death and neutron-star models can match the data. The paper collects the currently localized FRB sample, fits a log-normal host-galaxy gas contribution to repeaters and non-repeaters, and finds no significant difference between their medians (66.63 vs 64.46 pc cm$^{-3}$). It then uses a survey catalog from a drift-scan radio telescope to derive local volumetric rates of about $6.9\times10^4$ Gpc$^{-3}$ yr$^{-1}$ for non-repeaters and about $630$ Gpc$^{-3}$ yr$^{-1}$ for repeaters at those medians, and shows that the rates swing by an order of magnitude as the assumed host contribution changes. If these estimates hold, future rate comparisons with supernovae, magnetars, and gamma-ray bursts must treat host-galaxy gas as a dominant systematic, not a minor correction.

What carries the argument

The mechanical core is the dispersion-measure (DM) budget, the relation that divides an FRB's measured signal delay into Milky Way, halo, intergalactic, and host-galaxy contributions. The paper treats the host contribution as a log-normal random variable, fits its median to 35 non-repeaters and 14 repeaters with Markov-chain Monte Carlo, and then uses the simulation-calibrated probability distribution $P(\Delta)$ of Eq. (5) to convert each remaining extragalactic DM into a maximum comoving distance. That distance sets $V_{\rm limit}$ in the volumetric-rate formula $R = N/(\epsilon V_{\rm limit}\Omega_{\rm sky}t_{\rm obs}f_b)$, so every assumption about the IGM or host DM propagates directly into the rates.

What would settle it

A falsifying check would be to compare the assumed intergalactic DM distribution with a sample of FRBs that have measured redshifts and host galaxies at $z<0.2$. If the observed distribution of extragalactic DM minus the inferred host contribution has a different median or tail than the simulation-based model, the limiting-volume calculation and the quoted local rates would have to be revised by an amount comparable to the host-DM effect.

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Extended reading notes

Core claim

On its own terms, the paper's discovery is that the host-galaxy term in the dispersion-measure budget, not just the intergalactic term, controls what volumetric rates imply about FRB origins. The Markov-chain Monte Carlo fit to 35 localized non-repeaters and 14 localized repeaters yields overlapping host DM medians, so the paper concludes that repeater and non-repeater environments cannot be distinguished with present data. It then shows that changing the assumed $\mathrm{DM_{host}}$ from zero to values typical of galaxies raises the inferred non-repeater local rate by about an order of magnitude; at the fitted medians the rates are $R\approx6.9\times10^4$ Gpc$^{-3}$ yr$^{-1}$ (non-repeaters) and $R\approx630$ Gpc$^{-3}$ yr$^{-1}$ (repeaters). These numbers are the paper's quantitative case that $\mathrm{DM_{host}}$ significantly affects volumetric rates.

Load-bearing premise

The estimates rest on assuming that the adopted probability model for how much signal delay intergalactic electrons add, taken from a cosmological simulation, is correct for every line of sight; if that model is wrong, the inferred distances and rates shift by as much as the host-galaxy effect the paper highlights.

Editorial extensions

If this is right

  • The derived local non-repeater rate of about $6.9\times10^4$ Gpc$^{-3}$ yr$^{-1}$ sits near the Type Ia supernova rate and the magnetar upper limit, so neither model is excluded at the fiducial host DM.
  • At higher assumed host DM, the non-repeater rate exceeds the magnetar and soft-gamma-repeater upper limits, so the host correction determines whether those progenitor channels remain viable.
  • The repeater rate of about $630$ Gpc$^{-3}$ yr$^{-1}$ is consistent with long and short gamma-ray burst rates within the quoted uncertainties, leaving both magnetar and merger interpretations open.
  • Because the median host DM is similar for repeaters and non-repeaters, the data do not support a clean environmental separation between the two populations, though small samples and orientation effects could mask a real difference.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • An untested consequence is that if the intergalactic DM model is recalibrated with localized FRBs at known redshifts, the local rates may shift by as much as the host-DM effect, which would blur the paper's central contrast.
  • A natural next step, not taken here, is to reclassify FRBs by host-galaxy properties or local environment rather than by repetition, since the similar $\mathrm{DM_{host}}$ medians suggest repetition status may not track the surrounding gas.
  • A testable extension is to run injection simulations tailored to repeater exposure to check whether the single detection efficiency assumed for both populations changes the repeater rate outside its quoted Poisson errors.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 6 minor

Summary. The manuscript re-examines FRB host-galaxy dispersion measures and local volumetric rates. It compiles a table of localized FRB host properties, runs a bilby MCMC to infer DMhost for 35 non-repeaters and 14 repeaters from a log-normal prior, and reports no significant median difference between the populations. It then selects CHIME/FRB Catalog 1 non-repeaters and Blinkverse repeaters, computes Vlimit from a probability statement P(≤dlimit|DMex) using the IllustrisTNG-based DMIGM distribution of Eq. (5), and derives volumetric rate densities from Eq. (8). The headline numbers are R ≈ 6.9 × 10^4 Gpc^-3 yr^-1 for non-repeaters at DMhost = 66.63 pc cm^-3 and R ≈ 630 Gpc^-3 yr^-1 for repeaters at DMhost = 64.46 pc cm^-3; the authors conclude that DMhost significantly affects the rates and compare with SN Ia, CCSN, magnetar, and GRB rates.

Significance. The compilation of localized host galaxies and the use of a non-Gaussian IllustrisTNG-based DMIGM distribution are useful, and the comparisons with Ravi (2019) and Shin et al. (2023) provide sanity checks. If the rate method were fully specified, the resulting local rates would be a valuable point of comparison for progenitor models. However, the central claim that DMhost significantly affects volumetric rates is currently a consequence of the Vlimit construction in Section 2.4 rather than an empirical measurement, and the missing algorithm details prevent the reader from assessing the magnitude of the effect. The MCMC host-DM result also lacks prior and likelihood details. The paper is promising but needs substantial clarification and reframing.

major comments (5)
  1. [Section 2.4, Eq. (8)] The Vlimit calculation is not specified sufficiently for reproduction. The text states that the FRB with the highest DMex is assigned P(≤dlimit|DMex) ≈ 0.95 and all others ≈ 1, but it does not give the functional form of P, the parameters of Eq. (5), the value of dlimit or Vlimit, or the sensitivity to the 95% quantile. Because Eq. (8) scales all rates inversely with Vlimit, every rate in Sections 3.2 and 3.3 depends on this single order statistic. Please provide the full algorithm, the adopted parameter values from Zhang et al. (2021), and a robustness test (e.g., 68% vs 99% quantile, or a full likelihood approach).
  2. [Sections 3.1–3.3, Figure 6] The abstract and Section 4 state that DMhost significantly affects rates, but this is a direct consequence of substituting assumed DMhost values into Eq. (8): increasing DMhost decreases the allowed DMIGM, hence dlimit and Vlimit, and increases R by construction. The paper does not identify an independent constraint that would make this an empirical claim. I recommend reframing these curves as a sensitivity study of a model-dependent estimator and showing whether the differences survive when the uncertainty in the DMhost distribution is propagated jointly rather than by point substitutions.
  3. [Section 2.3, Figure 2] The MCMC inference of DMhost is underspecified: no priors for µhost and σhost are given, the likelihood (presumably Eq. (5) plus a log-normal host term) is not written down, and only sources with positive inferred DMhost are retained. Dropping negative or zero DMhost values biases the medians upward, and the selection of sources from Table 1 is not described. Without these details the conclusion of no significant difference between repeaters and non-repeaters cannot be evaluated.
  4. [Section 3.3, Eq. (8)] The repeater rate estimate applies ε = 0.468, a detection efficiency derived from non-repeater injection tests in CHIME/FRB Catalog 1, while the repeater sample is drawn from Blinkverse over a 4-year exposure and counts each source once. Equation (8) as written combines a per-burst efficiency with a source count, so the repeater rate is likely biased. Please derive an appropriate source-detection efficiency and effective exposure for repeaters, or state explicitly why the non-repeater efficiency applies.
  5. [Section 2.2, Eq. (5)] The rates for z < 0.2 are set by the low-redshift tail of the adopted DMIGM distribution, but the parameters A, α, β, σDM, and C0 from Zhang et al. (2021) are never listed, and Figure 1 shows that the choice of distribution changes distance estimates. If the IllustrisTNG distribution is misspecified at low redshift, the resulting shift in Vlimit could be comparable to the claimed DMhost effect. Please report the parameter values, show the behavior of Eq. (5) at low z, and quantify the systematic uncertainty.
minor comments (6)
  1. [Title, page 2] The title contains a typo: 'F ast Radio Burst' should read 'Fast Radio Burst'.
  2. [Section 2.3] The text states that observations at 'low radio frequencies (∼100 GHz)' can constrain the local environment; the unit should presumably be MHz, not GHz.
  3. [Section 3.3] FRB 20200120E is excluded from the repeater rate estimate but the sample-selection section does not justify this exclusion; please state the reason in Section 2.5.
  4. [Section 2.3, Eq. (3)] The text mixes DMhost and DMsource: Eq. (3) lists them separately, but Section 2.3 says they are combined for the analysis; please clarify how DMsource is handled in Eqs. (4) and (7).
  5. [Figures 5–7] Several figure captions are informal and do not fully define the shaded regions or the meaning of the vertical and horizontal lines; please make the captions self-contained.
  6. [Appendix A] The compiled Table 1 is valuable, but no machine-readable version or data availability statement is provided; please include a link to the table in electronic form.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper's DMhost sensitivity is an explicit input-dependence calculation, not a hidden fit or self-referential prediction.

full rationale

The paper's central quantitative claim is that the estimated volumetric rate depends strongly on the assumed host-galaxy dispersion measure. The quoted rate values are obtained by substituting chosen DMhost values into the rate equation, R = N/(epsilon Vlimit Omega_sky t_obs f_b), with Vlimit set by a probability condition on DM_I G M. This is a forward sensitivity calculation: the DMhost values are inputs supplied from the authors' MCMC analysis of localized FRBs, and the rates are outputs. The paper explicitly acknowledges the mechanism: 'The volumetric rate increases rapidly as the DM host increases, which is because of the uncertainty from DM IGM and DM host.' Thus the DMhost-dependence is not a hidden consequence disguised as an independent measurement; it is the stated logic of the estimator. No fitted parameter is renamed as a prediction in a way that would force the result. The MCMC inference of DMhost for localized sources is a separate analysis from the CHIME sample rate calculation, and the rate calculation does not use the same data to fit the quantity it then claims to predict. The DM_I G M distribution from Zhang et al. (2021) is a load-bearing input, and it comes from the same research group, but it is tied to the external IllustrisTNG simulations and is not derived from the present paper's own assumptions or fitted values. If that distribution is misspecified, the rates would shift, but that is a correctness and robustness concern, not circularity. Self-citation is present but is used as external simulation-based evidence, so it does not raise the circularity score. The derivation chain is therefore self-contained in the relevant sense: the sensitivity result follows from stated equations and clearly labeled assumptions, with no step that reduces to its own input by construction.

Assumptions & free parameters 8 free parameters · 6 assumptions · 0 invented entities

The central claims rest on a chain of prior-model assumptions and fitted inputs. The most consequential are the fitted DMhost medians, the adopted DM_IGM distribution, and the assumed detection efficiency and exposure for repeaters, because these directly set the numerical rates.

free parameters (8)
  • median DM_host for non-repeaters = 66.63 pc cm^-3
    MCMC fit to localized non-repeaters in Section 2.3; used as the central host DM in the Section 3.2 rate estimate.
  • median DM_host for repeaters = 64.46 pc cm^-3
    MCMC fit to localized repeaters in Section 2.3; used as the central host DM in the Section 3.3 rate estimate.
  • DM_IGM distribution parameters = adopted from Zhang et al. 2021, values not quoted
    A, sigma_DM, and C0 in Eq. (5) set the width and tail of the intergalactic DM distribution, controlling P(dlimit|DMex) and hence Vlimit.
  • detection efficiency epsilon = 0.468
    From the CHIME injection test; applied to both non-repeaters and repeaters in Eq. (8).
  • beaming factor f_b = 0.1
    Assumed from Nicholl et al. 2017; scales the rate linearly.
  • observation time for non-repeaters = 214.8 days
    Effective exposure for CHIME/FRB Catalog 1; enters Eq. (8).
  • observation time for repeaters = 4 yr
    Rough CHIME operating period before 2024; the paper states the observational time is difficult to calculate.
  • log-normal DM_host prior hyperparameters = not stated
    The bilby MCMC in Section 2.3 uses a log-normal prior but the numerical values of mu_host and sigma_host are not given.
assumptions (6)
  • domain assumption The DM_IGM distribution of Eq. (5), with parameters from Zhang et al. (2021), correctly describes the scatter in intergalactic DM at all redshifts used.
    The Vlimit calculation in Section 2.4 relies on this distribution; the paper shows in Figure 1 that different DM_IGM models change distance estimates.
  • domain assumption FRB sources are uniformly and isotropically distributed and occur as a Poisson process in the comoving volume.
    Section 2.4 uses this to justify the Poisson counting and volume scaling of Eq. (8).
  • domain assumption The YMW16 and YT20 models give accurate Milky Way disk and halo DM contributions for every CHIME line of sight.
    DM_ex is computed by subtracting these model values in Section 2.1; the authors note some FRBs have negative or near-zero DM_ex, indicating model tension.
  • domain assumption Host-galaxy DM follows a single log-normal distribution with no redshift evolution.
    Section 2.3 adopts Eq. (7) and explicitly does not consider evolution of ionized gas with cosmic star formation history.
  • domain assumption The DMhost distribution inferred from localized FRBs is representative of the CHIME volume-limited sample.
    The MCMC medians from about 49 localized sources are applied to 51 non-repeaters and 13 repeaters in Sections 3.2 and 3.3.
  • ad hoc to paper The detection efficiency for repeaters equals the injection-derived efficiency for non-repeaters.
    Equation (8) uses epsilon = 0.468 for repeaters, but repeaters have different exposure and repetition selection effects; the paper does not justify this equivalence.

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Cite this review

Pith. "Pith review of Reinvestigation of Fast Radio Burst Host Galaxy and Event Rate Density." pith.science (2026). https://pith.science/paper/KL2RIWM2

@misc{pith2026241109203,
  author       = {Pith},
  title        = {Pith review of: Reinvestigation of Fast Radio Burst Host Galaxy and Event Rate Density},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KL2RIWM2}},
  note         = {Machine review of arXiv:2411.09203}
}
abstract

Fast radio bursts (FRBs) are radio signals that last milliseconds. They originate from cosmological distances and have relatively high dispersion measures (DMs), making them being excellent distance indicators. However, the origins of the FRB remain to be resolved. With its wide field of view and excellent sensitivity, CHIME/FRB has discovered more than half of all known FRBs. As more and more FRBs are located within or connected with their host galaxies, the study of FRB progenitors is becoming more important. In this work, we collect the currently available information related to the host galaxies of FRBs, and the Markov Chain Monte Carlo analysis about limited localized samples reveals no significant difference in the median of $\mathrm{DM_{host}}$ between repeaters and non-repeaters. After examining and selecting CHIME/FRB samples, we estimate the local volumetric rate density of repeaters and non-repeaters, accounting for different $\mathrm{DM_{host}}$ contributions, and compare with rates of predicted origin models and transient events. Our results indicate that $\mathrm{DM_{host}}$ significantly affects volumetric rates and offer insights into the origin mechanisms of FRB populations.

Figures

Figures reproduced from arXiv: 2411.09203 by the authors.

Figure 1
Figure 1. Left panel: probability density comparison for two DMIGM distributions. Right panel: cumulative distribution comparison for two DMIGM distributions. 2 http://apps.datacentral.org.au/pygedm/ [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. MCMC results for localized non-repeaters (left, 35 in total) and repeaters (right, 14 in total). limit the density of the local environment by constraining absorption in the local ionized medium (Pastor-Marazuela et al. 2021). Since the progenitors of FRBs are still uncertain, we do not consider its impact on our research and combine this contribution with DMhost for the following analysis. 2.4. Volumetric Event Rat… view at source ↗
Figure 3
Figure 3. Cumulative distribution (left) and number distribution (right) of DMex for CHIME non-repeaters. 3. RESULTS 3.1. Volumetric Rate Comparison In this subsection, we display the result estimated by three non-repeaters with the lowest DMex for comparison with Ravi (2019). By choosing these samples, we found that DMex < 50 pc cm−3 for them, which is smaller than the samples from Ravi (2019) indicating a small DMhost. Assu… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Cumulative distribution (left) and number distribution (right) of DMex for CHIME repeaters. the uncertainty from DMIGM and DMhost. For DMhost = 0, we find that the result is consistent with Ravi (2019), indicating that the distribution of DMIGM affects the rate estimat…
Figure 5
Figure 5. Figure 5: Volumetric rate (red line) estimated for different DMhost. The rate is estimated using three non-repeaters with the lowest DMex for comparison with Ravi (2019). The 95% confidence region is shown as gray. 3.2. Rate Estimation for Non-Repeaters [PITH_FULL_IMAGE:figures…
Figure 6
Figure 6. Figure 6: Event rate density estimation for different DMhost contribution assumptions of non-repeaters. The red solid line with a dark gray area represents the event rate at a 95% confidence level. Host contributions are indicated by vertical lines, while rates of potential prog…
Figure 7
Figure 7. Figure 7: Event rate density estimation for different DMhost contribution assumptions of repeaters. The red solid line with a dark gray area represents the event rate at a 95% confidence level. The rate of LGRBs (Chapman et al. 2007; Luo et al. 2020), SGRBs (Coward et al. 2012; …

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