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An analytical model for the dispersion measure of Fast Radio Burst host galaxies

T0 review · 4 major / 7 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read An analytic baryonification model reproduces the probability distribution of host-galaxy dispersion measures for fast radio bursts, matching two hydrodynamic simulation suites and tying the host correction to baryonic feedback.

desk verdict A genuinely new and honest application of baryonification to FRB host DMs; the central degeneracy is clearly stated and the paper deserves a serious referee. read the letter →

arxiv 2411.17682 v2 pith:KYIUJ4XQ submitted 2024-11-26 astro-ph.CO astro-ph.GAastro-ph.HE

Robert Reischke , Michael Kovač , Andrina Nicola , Steffen Hagstotz , Aurel Schneider This is my paper · ORCID
classification astro-ph.COastro-ph.GAastro-ph.HE
keywords fastradioburstsdispersionmeasurebaryonificationbaryonicfeedbackhostgalaxiescircumgalacticmediumCAMELSsimulationshalomodel
open problems Dark Matter
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 claims that the host-galaxy contribution to the dispersion measure (DM) of fast radio bursts — currently one of the largest unknowns in FRB cosmology — can be described by a simple analytic model based on baryonification. The model assigns each halo physically motivated gas and stellar profiles, draws FRB sightlines from the stellar distribution, and integrates the free-electron column along each line of sight to build a full probability distribution of host DMs. That distribution reproduces the host DM PDFs measured in the SIMBA and IllustrisTNG runs of the CAMELS hydrodynamic simulations, including their halo-mass and redshift dependence, and the same fitted parameters predict the baryonic suppression of the matter power spectrum within cosmic variance. The paper's central physical finding is that the shape of the host DM distribution is governed by how compact the FRB population is relative to the gas: more concentrated FRB profiles must be paired with shallower gas profiles, a degeneracy that is real but bounded.

What carries the argument

The load-bearing object is the baryonification (BCM) halo model, which remaps a dark-matter-only halo into dark-matter-baryon profiles with analytic gas, stellar, and collisionless components. The gas follows a cored double-power-law profile whose shape is set by a core radius $\theta_{\mathrm{co}}$, an ejection radius $\theta_{\mathrm{ej}}$, an outer slope $\delta$, a transition slope $\gamma$, and a mass-dependent inner slope $\beta(M)$ controlled by the parameters $M_c$ and $\mu$. The stellar profile — a truncated NFW profile with exponential cutoff governed by a cutoff radius $r_{\mathrm{cut}}$ and slope $\alpha$ — doubles as the FRB sampling distribution via $p_{\mathrm{FRB}}(r) \propto \rho_{\star}(r)$. The host DM probability distribution is built by sampling roughly $10^4$ sightlines from that distribution and integrating the electron column along each; the two-halo term is shown in an appendix to be negligible. The machinery converts a handful of feedback-related parameters into a concrete, testable prediction for the full host DM distribution, which is what makes the comparison to simulations and to future FRB samples possible.

What would settle it

Fit the same model to the host DM PDFs of the third CAMELS suite, ASTRID, or of a larger-box hydrodynamic simulation with different subgrid feedback: if no parameter set within the BCM prior can simultaneously reproduce its host DM PDFs and its power-spectrum suppression, the claimed self-consistency holds only for SIMBA and IllustrisTNG. On the data side, a sample of a few hundred localized FRBs with host halo mass estimates would test the predicted $\langle \mathrm{DM_{host}} \rangle(M)$ scaling and the long high-mass tail of the PDF, while measured FRB offsets from their host centers would test the $p_{\mathrm{FRB}} \propto \rho_{\star}$ assumption directly.

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Extended reading notes

Core claim

On its own terms, the paper establishes that the baryonification model (BCM) — a framework previously built to describe baryonic effects on the matter power spectrum — can be extended into a statistical model of FRB host DMs. The extension adapts the stellar profile to low-mass halos as a truncated NFW profile with an exponential cutoff and assumes FRBs are sampled proportionally to that stellar density, $p_{\mathrm{FRB}}(r) \propto \rho_{\star}(r)$. With eight free parameters fitted to the host DM PDFs of SIMBA and IllustrisTNG, the model reproduces the distributions, their growth in mean and width with halo mass, and their mild evolution from high to low redshift. As a consistency test, the same fitted parameters, passed through a BCM emulator, yield a matter power spectrum suppression consistent with the same simulations within cosmic variance. The paper further argues that the long-tailed, quasi-log-normal DM distributions seen in simulations arise naturally from the interplay of a compact stellar (FRB) profile and an extended gas profile, and that this interplay contains a bounded degeneracy: steeper FRB profiles demand shallower gas profiles, but not at arbitrary strength, so the two components are not fully interchangeable.

Load-bearing premise

The model assumes fast radio bursts live where the stars are — FRB sightlines are drawn from the stellar density profile — and every inferred gas property, as well as the central compactness degeneracy, shifts if the true FRB population instead follows star-forming gas, globular clusters, or some other spatial distribution.

Editorial extensions

If this is right

  • The same BCM parameters predict both the host DM PDF and the matter power spectrum suppression, so FRB cosmology analyses can marginalize over the host contribution in a way that is consistent with baryonic feedback constraints from other probes.
  • The host DM PDF is sensitive enough to feedback parameters that it can serve as a complementary probe of baryonic physics on galactic scales, where cosmic shear has little leverage.
  • Because the mean host DM grows with halo mass and the PDF broadens toward log-normal shape, the host correction cannot be approximated as a constant or a fixed scatter in FRB samples spanning different host populations.
  • The bounded nature of the FRB-gas degeneracy means that combining DM PDFs with even weak priors on the FRB distribution can break the degeneracy, allowing a joint measurement of the gas profile and the stellar profile.

Reading between the lines

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

  • If future FRB localizations measure burst offsets from host centers for a large sample, the degenerate pair of profiles could be disentangled, turning the host DM PDF into a direct probe of the gas profile shape — a measurement the paper's own framework makes available but does not perform.
  • The model's strong sensitivity to the stellar cutoff radius suggests host DM statistics could constrain the FRB progenitor population itself, distinguishing star-formation-tracing bursts from those in old stellar environments.
  • The BCM parameters preferred by low-mass FRB hosts differ from those constrained by cosmic shear at cluster scales; a joint analysis would test whether feedback parameters must depend on halo mass, a question the paper leaves open.
  • Adding the partially neutral cold-gas component the paper flags as missing could turn host DM PDFs into a probe of the cold circumgalactic medium and its ionization state.
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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

4 major / 7 minor

Summary. This paper extends the baryonification model (BCM) to analytically model the host-galaxy contribution to fast radio burst dispersion measures. Assuming that FRBs trace the stellar density profile, the authors construct a PDF for the host DM by sampling sightlines and integrating the gas density profile. They fit the model's free parameters (with alpha fixed) to the host DM PDFs of the SIMBA and IllustrisTNG CV0 runs of CAMELS taken from Theis et al. (2024), and show the resulting fit in Figure 2. They then use the fitted parameters to predict the matter power spectrum suppression with the Giri & Schneider (2021) BCM emulator, finding agreement within the CAMELS CV scatter. The paper also presents the dependence of the host DM PDF on halo mass, redshift, and all BCM parameters, and highlights a degeneracy between the compactness of the FRB profile and the shallowness of the gas profile. The authors conclude that the model provides a flexible, physically motivated description of the host DM contribution and could enable joint modeling with baryonic feedback.

Significance. The proposed model is a useful conceptual step: it provides an analytic, computationally inexpensive framework for a quantity that is currently a major systematic in FRB cosmology. The parameter-dependence study (Figures 9-10) and the discussion of the FRB/gas degeneracy in Section 5.6 are informative and will be valuable for the community. The model's ability to jointly describe host DM PDFs and baryonic power-spectrum suppression within the same framework is attractive. However, the validation is currently limited to a single simulation realization and the inference is degenerate with the assumed FRB spatial prior, so the significance of the specific parameter values and the mass/redshift scalings is not yet established. Strengths of the manuscript: the model is explicitly specified, the fitting procedure is described, and the limitations are acknowledged in Section 5.7, which aids reproducibility.

major comments (4)
  1. [Section 5.6, Figure 11] The degeneracy between the FRB spatial distribution and the gas profile, demonstrated in Figure 11, is a load-bearing caveat. The best-fit BCM parameters in Table 1 and the resulting feedback interpretation (SIMBA beta≈1.3 vs TNG beta≈0.3) were obtained with p_FRB ∝ rho_star (Eq. 20). Figure 11 shows that a more compact FRB profile can be compensated by a shallower gas profile while still matching the same simulation PDFs, and the paper itself notes that 'we cannot distinguish between these two cases without strong priors on the FRB distribution' (Sec. 5.6). Since the true FRB distribution (e.g., star-forming regions or globular clusters) is unknown, the claimed reproduction of the mass- and redshift-dependence in Figures 7 and 8 is conditional on this prior and may not be robust.
  2. [Section 4, Figure 2] The validation is based on a single CV0 realization, and the error model in Equation (26) includes only Poisson scatter in the halo mass function, not cosmic variance across the full CV set. The grey bands in Figure 2 therefore underestimate the true simulation uncertainty. A fit to the ensemble of CV realizations, or at least a comparison against the PDF scatter among CV runs, is needed to support the claim that the BCM reproduces the host DM PDF. Without this, the excellent agreement in Figure 2 may be partly a consequence of the narrow error model.
  3. [Section 4, Figure 3] The power spectrum suppression check is not an independent prediction: the BCM emulator of Giri & Schneider (2021) is calibrated to hydrodynamic simulations with similar feedback prescriptions, and the comparison in Figure 3 uses the same CAMELS runs on which the PDF fit is based. The result that the BCM prediction lies within the grey scatter is therefore a consistency check rather than a validation of the model. The abstract and Section 4 should make this distinction explicit.
  4. [Section 5.3, Figure 7] The mass-dependence claim is stronger than the evidence. Figure 7 shows that the BCM does not reproduce the non-monotonic feature around 8×10^12 h^-1 M_sun seen in the SIMBA measurements, and the simulation points are shown without Poisson error bars. In addition, the comparison in Figure 8 is qualitative, with no cosmic variance estimate. The text should either quantify the level of agreement or soften the claim that the mass and redshift dependence is reproduced.
minor comments (7)
  1. [Section 6] The text states that the model has 'eight free parameters', but Table 1 lists seven varied parameters plus alpha which is fixed to 2; please correct the count.
  2. [Section 4] The text says 'we simply measure the distribution function of halos, p_halo(M), in SIMBA' but Figure 2 also shows a TNG comparison; please clarify whether p_halo(M) is separately measured in IllustrisTNG or taken from Theis et al. (2024).
  3. [Equations (8) and (16)] The symbol 'B' appears to be a typographical artifact for a definition operator; it should be replaced with '≡' or '='.
  4. [Section 5.1] The phrase 'carried out up to a fiducial value of three (m=3)' should refer to ξ=3, not m.
  5. [Figure 4 caption] The caption uses 'viral mass' instead of 'virial mass'.
  6. [Section 5.6] The statement that 'strong feedback cannot be compensated by increasingly compact stellar distributions' is not quantitatively supported by Figure 11; please either provide a metric for the breakdown of the degeneracy or label it as a qualitative inference.
  7. [Section 3.3] The sentence 'if uses matches spherically symmetric profiles from simulations to the BCM' contains a typo; it should likely read 'if one matches'.

Circularity Check

1 steps flagged · score 4.0 of 10

PDF 'reproduction' is a fit to the same CV0 CAMELS PDFs; mass/redshift and power-spectrum checks are independent, limiting the circularity.

  1. fitted input called prediction [Abstract; Section 4, Eq. (26) and the following paragraphs through Fig. 2; Table 1 caption]
    "we find that our simple model is able to reproduce the probability distribution function (PDF) of host halo DMs measured from the CAMELS suite of hydrodynamic simulations ... In a first step, we attempt to match the results for the host DM PDF from SIMBA and IllustrisTNG presented in Theis et al. (2024) ... We then fit the model, with α = 2 to the data."

    Eq. (26) constructs the modelled PDF as pHost(DM; λ) = ∫ dM pHost(DM; λ, M) pHalo(M), using the simulation's own halo mass function. The paper then states that the model is fitted to the CV0 host-DM PDFs from Theis et al. (2024), and Table 1 reports the resulting best-fit parameters. The abstract's claim that the model 'reproduce[s] the PDF' therefore reports the same quantity that was minimized in the fit; the agreement in Fig. 2 is by construction. The mass/redshift scalings (Figs. 7-8) and the power-spectrum suppression check (Fig. 3) are separate, non-forced outputs, so the circularity is partial rather than total.

full rationale

The only by-construction element is the host-DM PDF test: the BCM parameters (Table 1) are fit to the CV0 host-DM PDFs of Theis et al. (2024), so the agreement in Figure 2 is a goodness-of-fit statement, not an out-of-sample prediction. The abstract's 'reproduce the PDF' is therefore stronger than what the fitting procedure establishes. This is the basis for the flagged fitted-input-called-prediction step. The paper is nevertheless transparent about the fit ('We then fit the model ... to the data'), and it does not rest its central case on that PDF alone. The mass- and redshift-dependent mean DMs (Figs. 7-8) were not part of the fit target, since Eq. (26) marginalizes over pHalo(M) only, so their agreement is a non-forced prediction. The power-spectrum suppression test (Fig. 3) uses the independent Giri & Schneider (2021) BCM emulator on a different observable. The self-citations to Theis et al. (2024) and Giri & Schneider (2021) involve overlapping authorship, but the underlying CAMELS data and the BCM emulator are external and reproducible, so they do not by themselves make the derivation circular. The FRB-profile choice p_FRB ∝ ρ_star (Eq. 20) is an explicit ansatz; Section 5.6 shows a degeneracy with the gas parameters, which is a modeling limitation rather than a circular reduction. Because the central derivation contains independent, non-forced checks, the circularity score is moderate rather than maximal.

Assumptions & free parameters 7 free parameters · 6 assumptions · 0 invented entities

The model's predictions are generated by a small number of analytic density profiles and an assumed FRB distribution. The seven to eight BCM parameters are free and fitted to the simulations, so the model is best understood as a flexible fitting tool with physical motivation rather than a parameter-free derivation. The main independent content is the translation between host DM PDF shape and gas profile shape, which is sensitive to the unverified FRB distribution assumption.

free parameters (7)
  • log10 M_c = 12.7 (SIMBA), 14.1 (TNG)
    Mass scale at which the inner gas slope beta transitions; fitted to the host DM PDF; degenerate with mu and beta.
  • theta_ej = 7.95 (SIMBA), 5.0 (TNG)
    Ejection radius in units of virial radius; controls how far gas is pushed out; fitted to host DM PDF.
  • mu = 0.19 (SIMBA), 0.49 (TNG)
    Slope of the mass dependence of beta; degenerate with Mc and beta for a narrow mass range.
  • delta = 9.0 (SIMBA), 10.1 (TNG)
    Outer slope of the gas density profile; strongly affects the width of the DM PDF.
  • gamma = 1.0 (both)
    Transition slope of the gas profile; weakly constrained.
  • theta_co = 0.017 (SIMBA), 0.009 (TNG)
    Core radius of the gas profile in units of virial radius; affects central density and DM tail.
  • r_cut = 0.27 (SIMBA), 0.53 (TNG)
    Exponential cutoff radius of the stellar profile in units of virial radius; sets the compactness of the FRB distribution.
assumptions (6)
  • domain assumption FRB positions trace the stellar density profile of the host halo (Eq. 20).
    Used in Eq. (19) to compute the host DM PDF; if FRBs follow star formation or globular clusters instead, the inferred gas parameters change.
  • domain assumption All baryonic gas in the halo is fully ionized and follows the BCM gas profile (Eq. 14 with mu_e=1.17).
    Cold or partially neutral gas is neglected; the authors list this as a limitation in Sec. 5.7.
  • domain assumption The BCM analytic profiles (cored double power-law gas, truncated NFW clm, exponentially cut-off stellar profile) are valid for low-mass halos below 1e12 h^-1 Msun.
    The BCM was originally calibrated for higher-mass halos; the paper modifies the stellar profile but this extrapolation is asserted in Sec. 3.1.
  • domain assumption The concentration-mass relation of Dutton and Maccio (2014) applies to the low-mass halos studied here.
    Used to set the NFW scale for the clm and stellar profiles in Sec. 3.1.
  • ad hoc to paper The Poisson error model for the halo mass function adequately represents the uncertainty in the simulated host DM PDF.
    Used in Sec. 4 to define the likelihood; the paper itself notes that a proper inference cannot be carried out with a single CV0 run.
  • domain assumption The Giri and Schneider (2021) BCM emulator correctly maps BCM parameters to the matter power spectrum suppression.
    Used in Sec. 4 for the consistency test; theta_co is fixed to 0.1 because it is not a free parameter of the emulator.

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Cite this review

Pith. "Pith review of An analytical model for the dispersion measure of Fast Radio Burst host galaxies." pith.science (2026). https://pith.science/paper/KYIUJ4XQ

@misc{pith2026241117682,
  author       = {Pith},
  title        = {Pith review of: An analytical model for the dispersion measure of Fast Radio Burst host galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KYIUJ4XQ}},
  note         = {Machine review of arXiv:2411.17682}
}
read the original abstract

The dispersion measure (DM) of fast radio bursts (FRBs) is sensitive to the electron distribution in the Universe, making it a promising probe of cosmology and astrophysical processes such as baryonic feedback. However, cosmological analyses of FRBs require knowledge of the contribution to the observed DM coming from the FRB host. The size and distribution of this contribution is still uncertain, thus significantly limiting current cosmological FRB analyses. In this study, we extend the baryonification (BCM) approach to derive a physically-motivated, analytic model for predicting the host contribution to FRB DMs. By focusing on the statistical properties of FRB host DMs, we find that our simple model is able to reproduce the probability distribution function (PDF) of host halo DMs measured from the CAMELS suite of hydrodynamic simulations, as well as their mass- and redshift dependence. Furthermore, we demonstrate that our model allows for self-consistent predictions of the host DM PDF and the matter power spectrum suppression due to baryonic effects, as observed in these simulations, making it promising for modelling host-DM-related systematics in FRB analyses. In general, we find that the shape of the host DM PDF is determined by the interplay between the FRB and gas distributions in halos. Our findings indicate that more compact FRB profiles require shallower gas profiles (and vice versa) in order to match the observed DM distributions in hydrodynamic simulations. Furthermore, the analytic model presented here shows that the shape of the host DM PDF is highly sensitive to the parameters of the BCM. This suggests that this observable could be used as an interesting test bed for baryonic processes, complementing other probes due to its sensitivity to feedback on galactic scales. We further discuss the main limitations of our analysis, and point out potential avenues for future work.

Figures

Figures reproduced from arXiv: 2411.17682 by the authors.

Figure 1
Figure 1. Geometry of the model for the DM host contribution as used in Equation (15) expressed in spherical coordinates. The observer O sits at infinity, so that the integration is along the 𝑥2-axis. the latter is given by 𝑃h,gas(𝑘) = 𝑏(𝑀)𝑃lin (𝑘) × ∫ ∞ 0 d𝑀′ 𝑛(𝑀′ )𝑏(𝑀′ )𝑢gas(𝑘) . (12) 𝑢gas(𝑘) is the Fourier transform of the gas density profile, 𝑛(𝑀) the halo mass function and 𝑃lin (𝑘) the linear matter power spectrum. The t… view at source ↗
Figure 2
Figure 2. PDF of the DM host contribution in blue with the parameters taken from [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 4
Figure 4. PDF of the electron distribution from the one-halo (1h, red solid) and the two-halo term (2h, red dashed), FRBs (or stars, blue solid), the modified NFW profile from Prochaska & Zheng (2019) with their fiducial parameters, 𝛼 = 2 = 𝑦0, and the profile from Fielding et al. (2017) in dotted grey. All curves are shown for a halo of viral mass 𝑚vir = 1012 ℎ −1𝑀⊙ and at redshift 𝑧 = 0 for the fiducial parameters of the BC… view at source ↗
Figures from the paper (7 more)
Figure 3
Figure 3. Figure 3: Power spectrum suppression for the parameters from [PITH_FULL_IMAGE:figures/full_fig_p006_3.png]
Figure 5
Figure 5. Figure 5: Host DM for different sightlines parametrised in spherical coordi￾nates, standard convention with 𝜙 measured against 𝑥1 and 𝜃 with respect to 𝑥3. The colour bar shows the DM. Note that the remaining variable is always fixed, as indicated in the colour bar label. The ha…
Figure 7
Figure 7. Figure 7: Mean host DM as a function of halo virial mass 𝑚vir from the BCM in blue. The grey shaded area indicates the scatter in the host DM obtained from Theis et al. (2024). confirmed, this could have consequences on the inference of the cosmological background model with FRB…
Figure 8
Figure 8. Figure 8: Redshift dependence if the host DM PDF. The mass of the halo is 𝑀 = 1012ℎ −1𝑀⊙. (see Equation 2). This means that there is a residual redshift evolution in the host contribution. Furthermore, the distribu￾tion becomes increasingly compact with increasing redshift. This…
Figure 9
Figure 9. Figure 9: Dependence of the host DM PDF on the BCM parameters (see [PITH_FULL_IMAGE:figures/full_fig_p009_9.png]
Figure 10
Figure 10. Figure 10: Dependence of the host DM PDF on the BCM parameters (see [PITH_FULL_IMAGE:figures/full_fig_p010_10.png]
Figure 11
Figure 11. Figure 11: Ratio of the densities of case (𝑏), i.e. a more compact stellar profile, in solid and case (𝑐), i.e. a less compact stellar profile, in dashed relative to the fiducial case (𝑎). The blue lines show the ratio of the stellar profile. Red lines show the ratio of the gas …

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Forward citations

Cited by 2 Pith papers

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

  1. Measurement of angular cross-correlation between the cosmological dispersion measure and the thermal Sunyaev--Zeldovich effect

    astro-ph.CO 2025-11 conditional novelty 7.0 of 10

    First detection of an angular cross-correlation between FRB dispersion measure and the thermal SZ y-map: amplitude A≈2 relative to the fiducial halo-model prediction (4.0σ for Planck, 1.5σ for ACT).

  2. Stellar Mass-Dispersion Measure Correlations Constrain Baryonic Feedback in Fast Radio Burst Host Galaxies

    astro-ph.GA 2025-07 conditional novelty 6.0 of 10

    Using 20 low-redshift fast radio burst hosts, the authors find host dispersion measure decreases with stellar mass, a trend that conflicts with the weak-feedback CAMELS-Astrid simulation.

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    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.