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Cosmological Evolution of Fast Radio Bursts and The Star Formation Rate

T0 review · 4 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read The paper argues that the comoving formation rate of fast radio bursts declines steeply with redshift, unlike the cosmic star formation rate, and resembles the delayed formation rate of short gamma-ray bursts.

desk verdict A useful three-sample EP/Lynden-Bell analysis of CHIME FRBs giving a plausible declining formation rate; the main open questions are the sharp flux-limit assumption and the missing error bars on the density rate. read the letter →

arxiv 2504.13343 v2 pith:EZCZOFVF submitted 2025-04-17 astro-ph.CO astro-ph.HE

Sujay Champati , Vahé Petrosian This is my paper · ORCID
classification astro-ph.COastro-ph.HE
keywords fastradioburstsluminosityfunctioncosmologicalevolutionstarformationratemagnetarsEfron-PetrosianmethodLynden-BellC-dispersionmeasure
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

Fast radio bursts are bright millisecond radio pulses from cosmological distances, but their redshifts are only indirectly known from dispersion measures, and any flux-limited sample is biased by the Malmquist/Eddington effect. The paper tries to recover the true joint distribution of FRB luminosity and redshift from the CHIME catalog by treating the 0.5 jansky flux limit as a sharp truncation and applying nonparametric methods that correct for it. Its central claim is that the comoving formation rate of FRBs declines steeply with redshift, in sharp contrast to the cosmic star formation rate, and that this decline resembles the delayed formation rate of short gamma-ray bursts. If true, the result would mean FRBs are not simply tracers of recent star formation but are produced by older progenitor systems, consistent with magnetars born in compact-object mergers.

What carries the argument

The engine of the analysis is the Efron-Petrosian rank test with Kendall's tau: for each burst, it builds an associated set of bursts that could have been observed given the flux-limit boundary $L_{\min}(Z)$, then tests whether luminosity and redshift are independent by comparing each burst's rank in that set with its expected rank. Once luminosity evolution is found, the evolution function $g(Z)=Z^k(1+Z_{\rm cr}^k)/(Z^k+Z_{\rm cr}^k)$ (with $Z_{\rm cr}\approx 3.5$) de-evolves luminosities into a redshift-independent local luminosity $L_0=L/g(Z)$; the Lynden-Bell C− method then turns the associated sets into cumulative luminosity function $\phi(L_0)$ and cumulative number rate $\dot{\sigma}(Z)$, whose derivative yields the comoving density formation rate.

What would settle it

If an independent sample with host-galaxy redshifts — or the same EP/C− analysis run with the true CHIME detection efficiency as a smooth function of fluence instead of a sharp 0.5 Jy cut — produced a comoving formation rate that rises with redshift in step with the star formation rate, the central claim would be falsified.

Watch

Extended reading notes

Core claim

Analyzing a complete subsample of non-repeating CHIME bursts above a 0.5 Jy flux limit, the paper finds roughly 3σ evidence that FRB luminosity evolves with redshift: after correcting the truncation, the de-evolved local luminosity is statistically independent of redshift only for a luminosity evolution function $g(Z) \propto Z^k$ with $k \approx 5.3$–$6.5$ across the lower, mean, and upper redshift samples. The cumulative luminosity function is well described by a broken power law with low-luminosity slope $\delta_1 \approx 0.5$ and high-luminosity slope $\delta_2 \approx 1.7$. Most importantly, the comoving density formation rate $\dot{\rho}(Z)$ derived from the corrected redshift distribution decreases rapidly with redshift, unlike the cosmic star formation rate, and tracks the formation-rate evolution previously found for short gamma-ray bursts, which the authors take as evidence for magnetar progenitors from delayed compact-merger systems.

Load-bearing premise

The central assumption is that the CHIME sample is complete above a sharp 0.5 jansky flux limit, so the only selection effect is the exact truncation boundary; if real detection efficiency is gradual or redshift-dependent, the rank-based corrections are biased.

Editorial extensions

If this is right

  • Luminosity evolution cannot be ignored: assuming FRB luminosity is independent of redshift biases the inferred formation rate, and the paper's ~3σ detection is a direct challenge to analyses that set $k=0$.
  • The broken power-law luminosity function with slopes near 0.5 and 1.7 places FRBs in the same family of extragalactic source populations as AGNs and GRBs.
  • If the formation rate decrease with redshift is real, FRB surveys should see a local rate that exceeds what an SFR-tracking model predicts, and the excess grows toward $z<0.5$.
  • The similarity to short GRB rates connects FRB progenitors to neutron-star or neutron-star–black-hole mergers with a delay relative to star formation, making magnetars the natural link.
  • The result survives the DM redshift uncertainty: upper, mean, and half-lower redshift samples give qualitatively identical evolutions.

Reading between the lines

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

  • A testable corollary not drawn by the paper: if FRBs come from delayed mergers, their host galaxies at $z \lesssim 1$ should be older, more massive, and less actively star-forming on average than SFR-tracking hosts; this can be checked with the growing sample of localized FRBs.
  • The same machinery could be applied to the CHIME baseband-calibrated fluxes instead of catalog fluxes; the paper notes catalog fluxes are lower limits, and sharper fluxes would tighten or weaken the $k \approx 6$ evolution.
  • Fitting the inferred $\dot{\rho}(Z)$ to a delay-time distribution convolved with the cosmic SFR could yield a characteristic delay of order a gigayear, turning the qualitative similarity to short GRBs into a quantitative constraint.
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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 / 5 minor

Summary. This paper applies the Efron-Petrosian and Lynden-Bell nonparametric methods to 440 non-repeating CHIME FRBs to correct for flux-limited truncation and to derive the luminosity evolution, luminosity function, and comoving formation rate as functions of redshift. To account for redshift uncertainties from dispersion-measure modelling, the authors construct three samples using mean, upper (mean+1σ), and lower (mean−0.5σ) redshifts from Tang et al. (2023). They report ~3σ evidence for luminosity evolution with index k≈5.3–6.5, a slowly breaking power-law local luminosity function, and a comoving formation rate that decreases with redshift, in contrast to the cosmic star formation rate and similar to short gamma-ray bursts, which they interpret as supporting magnetar progenitors from compact mergers.

Significance. If the central claim holds, the paper provides an important constraint on FRB progenitors by showing that the FRB formation rate does not track the cosmic SFR and instead resembles the delayed merger channel of short GRBs. The use of nonparametric, non-binning methods and the explicit construction of three redshift samples to gauge DM-related uncertainties are strengths, and the authors are transparent about the flux lower-limit caveat. However, the conclusion rests on the sharp flux-limit assumption, on differentiating a fitted cumulative rate without error propagation, and on an a priori choice for the evolution break; these issues must be addressed before the result can be considered robust.

major comments (4)
  1. [§2, Eqs. (5)–(6)] The analysis treats the CHIME flux limit as a sharp truncation boundary Lmin(Z) with flim = 0.5 Jy, but the paper itself notes in Section 2 that the catalog fluxes are lower limits because of uncertainty in source position within the beam (Amiri et al. 2024). The Efron–Petrosian and Lynden-Bell procedures require an exact, deterministic truncation boundary; if the effective selection function is gradual or depends on burst properties and beam position, the associated sets used in Eqs. (7), (11), and (12) are mis-specified, biasing the luminosity-evolution index k and the cumulative rate that feeds the formation rate. This is the load-bearing assumption for the paper's central conclusion, so the authors should test robustness by varying flim over a range or by modeling a beam-averaged selection function, and at minimum should provide a quantitative estimate of the bias introduced by the known flux lower limits.
  2. [§4.3, Eq. (15), Table 2] The comoving density formation rate is obtained by differentiating a double broken power-law fit to the cumulative rate, yet no uncertainties are reported for the fit parameters in Table 2 and no confidence bands appear in Figure 5. Because the derivative of a broken power law is sensitive to the break parameters (Z1, Z2, β, and ε), small changes in the fit can translate into large changes in the density rate near the breaks. Since the claim of a rapid decline distinct from the SFR is a statement about the shape of the density rate, the absence of error propagation leaves the statistical significance of the difference unquantified. The authors should propagate the fit uncertainties, for example by bootstrap or MCMC, or estimate the density rate directly from the nonparametric cumulative rate with smoothing and bootstrap errors.
  3. [§4.1, Eq. (8)] The luminosity evolution function uses a break at Zcr = 3.5 adopted a priori from prior GRB and AGN work; the paper states that this value 'works well' but does not provide a quantitative test. The inferred index k (≈5.3–6.5) and the resulting de-evolved luminosities L0 depend on Zcr, and all subsequent quantities, including the luminosity function and the formation rate, are derived from L0. Because the FRB sample is concentrated at lower redshifts, the data likely do not directly constrain the high-redshift break, so the adopted prior may influence the high-redshift tail of the cumulative rate and its derivative. A sensitivity analysis, such as testing Zcr = 2 and Zcr = 5 or presenting a two-dimensional τ(k, Zcr) map, is needed to show that the conclusion is robust to this choice.
  4. [§2 (three redshift samples)] The three redshift samples (lower, mean, and upper) are not independent: they are constructed from the same set of bursts by coherently shifting each redshift by a fixed fraction of its quoted uncertainty. The agreement among the three curves in Figures 4 and 5 therefore reflects sensitivity to a global offset in redshift, not the full covariance of the dispersion-measure error distribution. The paper uses the spread among these samples as an uncertainty estimate, but the true uncertainties from host-galaxy and IGM contributions are likely correlated across sources and larger than this spread suggests. The authors should consider a bootstrap realization approach that resamples the host and IGM DM components for each burst to generate an ensemble of redshift samples, and propagate that ensemble through the derivation of k and the density rate.
minor comments (5)
  1. [§4.3] The caption of Figure 4 (right) says the curves show fits obtained using Equation (15), but the functional form used for the fits is Equation (14); Equation (15) defines the density rate, not the cumulative rate fit.
  2. [§4.3] The sentence 'Using the derivative dσ/dZ, and Equation (5), we obtain the co-moving density of the formation rate' appears to reference the wrong equation; the relation between the cumulative rate and the density rate is given by Equation (10).
  3. [§2] The notation for the dispersion-measure cut 'DMobs−DMGal ≤ 100 pc cm3 2' is garbled; it should read '100 pc cm−3'.
  4. [§2] The text uses both z and Z = 1+z interchangeably, for example in Equation (2) where z and Z appear together; the authors should consistently define which variable appears in each equation, especially in Eqs. (5) and (6), where Z is used in the definitions of Lmin and Zmax.
  5. [§1] The phrase 'in about 20 monthly papers' in the Introduction is unclear; it should be reworded, for example to 'in roughly twenty papers per month' or 'in the monthly FRB newsletters'.

Circularity Check

0 steps flagged · score 2.0 of 10

No circular derivation: k and the luminosity function are solved from rank statistics; the only imported element is the high-z flattening of g(Z), an explicit modeling assumption rather than a self-fulfilling prediction.

full rationale

The main derivation is self-contained. The luminosity-evolution index k is not fit to any target: it is determined by requiring Kendall's tau = 0 for the associated sets (Eq. 7), and the quoted values (k = 5.3, 6.1, 6.5 for the upper/mean/lower samples) are solutions of that rank condition. The de-evolved luminosity L0 = L/g(Z) is then used in the Lynden-Bell rank products (Eqs. 11 and 12) to build phi(L0) and sigma-dot(Z); Eq. 15 is a derivative of the fitted sigma-dot, so the density-rate shape is a transformation of the same rank statistics, not a constrained output. None of these steps fits a parameter to the claimed SFR comparison or to the short-GRB similarity; the short-GRB comparison is interpretive. The only element imported from the authors' prior work is the broken power-law form of g(Z) and the break Zcr ~ 3.5 (Eq. 8), justified physically by the flattening of the Hubble expansion rate at Z ~ 3-4. This is an explicit assumption, and the paper notes that an unflattened g(Z) = Z^k gives a very different high-redshift rate, so the high-z decline is model-dependent, not a renaming of an output. The acknowledged limitations (CHIME catalog fluxes are lower limits; flim = 0.5 Jy is assumed to be a sharp completeness limit; no error propagation on rho-dot) are data-quality and robustness concerns, not circularity.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The central result rests on a chain of inputs. The luminosity evolution index and all broken power law parameters are fitted to the same data that produce the conclusion. The evolution function's break and the sharp flux limit are chosen by hand. The redshift set and the single spectral index come from prior work. No new entities are introduced.

free parameters (6)
  • luminosity evolution index k = 5.3 (upper), 6.1 (mean), 6.5 (lower)
    Determined by requiring Kendall's tau = 0 in the Efron-Petrosian method.
  • evolution break redshift Zcr = 3.5
    Chosen from prior GRB work (Petrosian et al. 2015), not fitted here; affects the evolution function's flattening at high z.
  • flux limit flim = 0.5 Jy
    Chosen by hand as a 'conservative' completeness threshold, higher than the nominal 0.1 Jy limit.
  • luminosity function break Lbr = 8.0e32, 1.2e33, 2.0e33 erg/s for lower, mean, upper
    Fitted to the de-evolved cumulative luminosity function with a broken power law.
  • luminosity function indices delta1, delta2 and normalization phi0 = delta1=0.5 for all; delta2=1.7,1.75,1.7; phi0=260,250,280
    Fitted parameters of the broken power law in Eq. (13).
  • formation rate fit parameters sigma0, alpha, beta, epsilon, Z1, Z2 = Table 2: e.g., mean-Z: 0.003, 29.425, 7.118, 0.118, 1.124, 1.574
    Fitted to the cumulative rate sigma_dot(Z) with a double broken power law; the derivative gives the density rate, so these parameters directly shape the main conclusion.
assumptions (5)
  • domain assumption The CHIME catalog is complete above flim = 0.5 Jy, so the truncation boundary Lmin(Z) is exact.
    The analysis uses this hard cutoff in Eq. (5) to define the observable region; in reality CHIME's selection is gradual and depends on burst properties beyond peak flux.
  • ad hoc to paper The luminosity evolution function has the broken power law form g(Z) = Z^k (1+Zcr^k)/(Z^k+Zcr^k) with Zcr = 3.5 chosen from prior GRB/AGN work.
    The choice of Zcr is not derived from the FRB data; it is imported from Petrosian et al. (2015) for GRBs, and the paper does not test sensitivity to it.
  • domain assumption The redshifts and their 1-sigma uncertainties from Tang et al. (2023) are correct.
    The entire analysis depends on these redshifts, including the host-galaxy DM distribution and IGM fluctuation model.
  • domain assumption The spectral index alpha = -1.5 is the same for all FRBs.
    Used in the K-correction K(Z) = Z^(1+alpha); the paper notes individual values are unknown.
  • standard math The Lynden-Bell C- and Efron-Petrosian methods yield unbiased distributions under one-sided truncation, and after de-evolution the luminosity and redshift are independent.
    These are established statistical results cited from Efron & Petrosian (1992, 1999) and Lynden-Bell (1971); standard for this analysis.

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Pith. "Pith review of Cosmological Evolution of Fast Radio Bursts and The Star Formation Rate." pith.science (2026). https://pith.science/paper/EZCZOFVF

@misc{pith2026250413343,
  author       = {Pith},
  title        = {Pith review of: Cosmological Evolution of Fast Radio Bursts and The Star Formation Rate},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/EZCZOFVF}},
  note         = {Machine review of arXiv:2504.13343}
}
abstract

We investigate the cosmological evolution of the luminosity and redshift of FRBs. As is the case for all extragalactic sources, we are dealing with data that are truncated by observational selection effects, the most important being the flux limit, which introduces the so-called Eddington-Malmquist bias. In addition, for FRBs, there is a significant uncertainty in the redshifts obtained from the observed dispersion measures (DMs). To correct for the truncation we use the non-parametric, non-binning Efron-Petrosian and Lynden-Bell methods, which give unbiased distributions of luminosities and redshifts and their cosmological evolution. To quantify the redshift uncertainty, we use a data set which accounts for uncertainties of contribution to the DM of the host galaxy, and DM uncertainties due to fluctuation in the intergalactic medium. This data, in addition to a mean redshift, gives the one-sigma errors. We construct three samples with lower, mean, and upper redshifts and apply the above methods to each. For the three samples, we find similar (1) $\sim 3\sigma$ evidence for luminosity evolution, (2) a luminosity function that can be fit by a simple broken power law, and (3) a comoving density formation rate that decreases rapidly with redshift unlike the cosmic star formation rate (SFR). This rate is similar to that of short gamma-ray bursts, which are believed to result from compact star mergers with a formation rate delayed relative to the SFR. This may further support the hypothesis that magnetars are the progenitors of FRBs.

Figures

Figures reproduced from arXiv: 2504.13343 by the authors.

Figure 1
Figure 1. (Left): Dispersion Measure - Redshift Relation. The points represent the mean values of redshift. The horizontal error bars show the possible lower and upper values. From Tang et al. (2023). (Right): Redshift histograms, from Tang et al. (2023), for mean-z (top right), upper-z (top left), lower-z (bottom right), and half-lower-z (bottom left). Note that some weaker z < 0.01 are missing from the upper-z sample [PITH… view at source ↗
Figure 2
Figure 2. (Left): Luminosity-redshift scatter diagram for the mean redshift sample with a linear regression fit (green dashed line) showing a strong luminosity evolution, L ∝ Z 7.5 , partly due to the truncation shown by the solid black curve based on Equation (5) with flim = 0.5 Jy. (Right): Scatter diagram of the now-independent variables local luminosity, L0, and redshift, Z, with the de-evolved truncation boundary for the… view at source ↗
Figure 3
Figure 3. (Left:) Variation of Kendall’s τ with the index k of the luminosity evolution function (Eq. 8), indicating best (shown by the three solid vertical lines) and one sigma values (shown by the dotted lines only for the mean-Z sample); k = 5.3 +0.3 −0.2 , 6.1 +0.2 −0.3 , 6.5 +0.2 −0.7 for upper (blue), mean (black) and lower (red) Z samples, respectively. (Right:) Cumulative local luminosity function for the three sample… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: (Left): Cumulative formation rate numbers for the mean-Z sample. The lower curve (open circles) shows the raw cumulative redshift counts, N > Z). The middle curve is the correct number counts including correction for the luminosity evolution. The blue curve is for igno…
Figure 5
Figure 5. Figure 5: The Density Rate Evolution for three samples (red for lower, black for mean, and blue for upper, with arbi￾trary normalization) compared to the Star Formation Rate Taken From Madau & Dickinson (2014). The unit on the y axis applies only to the SFR. method to determine …

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Forward citations

Cited by 3 Pith papers

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

  1. Fast Radio Bursts Trace Cosmic Star Formation with Little Delay

    astro-ph.HE 2026-07 conditional novelty 6.0 of 10

    Hierarchical Bayesian analysis of CHIME/FRB finds the FRB volumetric rate peaks with the cosmic star-formation history at mean delays of 0.1–0.3 Gyr, consistent with zero delay and ruling out multi-Gyr merger-like delays.

  2. A Unified Volumetric Rate-Energy Relation from Magnetar Radio Bursts to Fast Radio Bursts

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

    The volumetric rate of radio bursts from magnetar SGR 1935+2154, repeating FRB 20180916B, and non-repeating CHIME FRBs follows a single power law R ∝ E^-1.31 from 10^29 to 10^42 erg.

  3. Calibrating $\rm{DM_{IGM}}-z$ relation using host galaxies of FRBs

    astro-ph.GA 2025-07 reject novelty 5.0 of 10

    A claimed tight sSFR-DM_exc correlation is used to calibrate the DM_IGM-z relation, but the improvement is evaluated on the same data used to fit the model.

Reference graph

Works this paper leans on

34 extracted references · 6 canonical work pages · cited by 3 Pith papers

  1. [1]

    C., Bandura, K., et al

    Amiri, M., Andersen, B. C., Bandura, K., et al. 2021, The Astrophysical Journal Supplement Series, 257, 59, doi: 10.3847/1538-4365/ac33ab

    doi:10.3847/1538-4365/ac33ab 2021

  2. [2]

    C., Andrew, S., et al

    Amiri, M., Andersen, B. C., Andrew, S., et al. 2024, Updating the first CHIME/FRB catalog of fast radio bursts with baseband data. https://arxiv.org/abs/2311.00111

    arXiv 2024

  3. [3]

    H., Jia, X

    Chen, J. H., Jia, X. D., Dong, X. F., & Wang, F. Y. 2024, The formation rate and luminosity function of fast radio bursts. https://arxiv.org/abs/2406.03672

    arXiv 2024

  4. [4]

    M., & Lazio, T

    Cordes, J. M., & Lazio, T. J. W. 2003, NE2001.I. A New Model for the Galactic Distribution of Free Electrons and its Fluctuations. https://arxiv.org/abs/astro-ph/0207156

    arXiv 2003

  5. [5]

    G., Petrosian, V., & Bowden, L

    Dainotti, M. G., Petrosian, V., & Bowden, L. 2021, The Astrophysical Journal Letters, 914, L40, doi: 10.3847/2041-8213/abf5e4

    doi:10.3847/2041-8213/abf5e4 2021

  6. [6]

    1992, ApJ, 399, 345, doi: 10.1086/171931

    Efron, B., & Petrosian, V. 1992, ApJ, 399, 345, doi: 10.1086/171931

    doi:10.1086/171931 1992

  7. [7]

    1999, Journal of the American Statistical Association, 94, 824, doi: 10.1080/01621459.1999.10474187

    Efron, B., & Petrosian, V. 1999, Journal of the American Statistical Association, 94, 824, doi: 10.1080/01621459.1999.10474187

    arXiv 1999

  8. [8]

    W., Ekers, R

    James, C. W., Ekers, R. D., Macquart, J.-P., Bannister, K. W., & Shannon, R. M. 2018, Monthly Notices of the Royal Astronomical Society, 483, 1342–1353, doi: 10.1093/mnras/sty3031

    doi:10.1093/mnras/sty3031 2018

Show all 34 references
  1. [9]

    2006, The Astrophysical Journal, 642, 371, doi: 10.1086/500816

    Kocevski, D., & Liang, E. 2006, The Astrophysical Journal, 642, 371, doi: 10.1086/500816

    2006 doi

  2. [10]

    2024, The Astrophysical Journal, 962, 73, doi: 10.3847/1538-4357/ad1b4f

    Lin, H.-N., & Zou, R. 2024, The Astrophysical Journal, 962, 73, doi: 10.3847/1538-4357/ad1b4f

    2024 doi

  3. [11]

    M., & Petrosian, V

    Lloyd, N. M., & Petrosian, V. 1999, The Astrophysical Journal, 511, 550–561, doi: 10.1086/306719

    1999 doi

  4. [12]

    R., Bailes, M., McLaughlin, M

    Lorimer, D. R., Bailes, M., McLaughlin, M. A., Narkevic, D. J., & Crawford, F. 2007, Science, 318, 777–780, doi: 10.1126/science.1147532

    2007 doi

  5. [13]

    1971, MNRAS, 155, 95, doi: 10.1093/mnras/155.1.95

    Lynden-Bell, D. 1971, MNRAS, 155, 95, doi: 10.1093/mnras/155.1.95

    1971 doi

  6. [14]

    2020, Nature, 581, 391, doi: 10.1038/s41586-020-2300-2

    Macquart, J., Prochaska, J., McQuinn, M., et al. 2020, Nature, 581, 391, doi: 10.1038/s41586-020-2300-2

    2020 doi

  7. [15]

    M., Bannister, K

    Macquart, J.-P., Shannon, R. M., Bannister, K. W., et al. 2019, The Astrophysical Journal Letters, 872, L19, doi: 10.3847/2041-8213/ab03d6

    2019 doi

  8. [16]

    2014, Annual Review of Astronomy and Astrophysics, 52, 415–486, doi: 10.1146/annurev-astro-081811-125615

    Madau, P., & Dickinson, M. 2014, Annual Review of Astronomy and Astrophysics, 52, 415–486, doi: 10.1146/annurev-astro-081811-125615

    2014 doi

  9. [17]

    1999, The Astrophysical Journal, 518, 32–43, doi: 10.1086/307260

    Maloney, A., & Petrosian, V. 1999, The Astrophysical Journal, 518, 32–43, doi: 10.1086/307260

    1999 doi

  10. [18]

    1992, in Statistical Challenges in Modern Astronomy, ed

    Petrosian, V. 1992, in Statistical Challenges in Modern Astronomy, ed. E. D. Feigelson & G. J. Babu (New York, NY: Springer-Verlag), 173

    1992

  11. [19]

    Petrosian, V., & Dainotti, M. G. 2023, Progenitors of Low Redshift Gamma-ray Bursts. https://arxiv.org/abs/2305.15081

    2023 arXiv

  12. [20]

    2015, The Astrophysical Journal, 806, 44, doi: 10.1088/0004-637x/806/1/44

    Petrosian, V., Kitanidis, E., & Kocevski, D. 2015, The Astrophysical Journal, 806, 44, doi: 10.1088/0004-637x/806/1/44

    2015 doi

  13. [21]

    2014, Proceedings of the International Astronomical Union, 10, 333–339, doi: 10.1017/s1743921315002458

    Petrosian, V., & Singal, J. 2014, Proceedings of the International Astronomical Union, 10, 333–339, doi: 10.1017/s1743921315002458

    2014 doi

  14. [22]

    1968, ApJ, 151, 393, doi: 10.1086/149446

    Schmidt, M. 1968, ApJ, 151, 393, doi: 10.1086/149446

    1968 doi

  15. [23]

    W., Bhardwaj, M., et al

    Shin, K., Masui, K. W., Bhardwaj, M., et al. 2023, The Astrophysical Journal, 944, 105, doi: 10.3847/1538-4357/acaf06

    2023 doi

  16. [24]

    2022, The Astrophysical Journal, 932, 111, doi: 10.3847/1538-4357/ac6f06

    Singal, J., Mutchnick, S., & Petrosian, V. 2022, The Astrophysical Journal, 932, 111, doi: 10.3847/1538-4357/ac6f06

    2022 doi

  17. [25]

    2023, Chinese Physics C, 47, 085105, doi: 10.1088/1674-1137/acda1c

    Tang, L., Lin, H.-N., & Li, X. 2023, Chinese Physics C, 47, 085105, doi: 10.1088/1674-1137/acda1c

    2023 doi

  18. [26]

    2017, The Astrophysical Journal, 850, 161, doi: 10.3847/1538-4357/aa96af

    Tsvetkova, A., Frederiks, D., Golenetskii, S., et al. 2017, The Astrophysical Journal, 850, 161, doi: 10.3847/1538-4357/aa96af

    2017 doi

  19. [27]

    2024, Astronomy & Astrophysics, 690, A377, doi: 10.1051/0004-6361/202450673 Evolution of Fast Radio Bursts 9

    Wang, Y., & van Leeuwen, J. 2024, Astronomy & Astrophysics, 690, A377, doi: 10.1051/0004-6361/202450673 Evolution of Fast Radio Bursts 9

    2024 doi

  20. [28]

    M., Manchester, R

    Yao, J. M., Manchester, R. N., & Wang, N. 2017, The Astrophysical Journal, 835, 29, doi: 10.3847/1538-4357/835/1/29

    2017 doi

  21. [29]

    2004, ApJ, 609, 935, doi: 10.1086/421285

    Yonetoku, D., Murakami, T., Nakamura, T., et al. 2004, ApJ, 609, 935, doi: 10.1086/421285

    2004 doi

  22. [30]

    Y., Dai, Z

    Yu, H., Wang, F. Y., Dai, Z. G., & Cheng, K. S. 2015, The Astrophysical Journal Supplement Series, 218, 13, doi: 10.1088/0067-0049/218/1/13

    2015 doi

  23. [31]

    2021, The Astrophysical Journal, 913, 120, doi: 10.3847/1538-4357/abf65e

    Zeng, H., Petrosian, V., & Yi, T. 2021, The Astrophysical Journal, 913, 120, doi: 10.3847/1538-4357/abf65e

    2021 doi

  24. [32]

    2024a, Universe, 10, 207, doi: 10.3390/universe10050207

    Zhang, J.-G., Li, Y., Zou, J.-M., et al. 2024a, Universe, 10, 207, doi: 10.3390/universe10050207

    doi

  25. [33]

    J., Dong, X

    Zhang, K. J., Dong, X. F., Rodin, A. E., et al. 2024b, Revisiting Energy Distribution and Formation Rate of CHIME Fast Radio Bursts. https://arxiv.org/abs/2406.00476

    arXiv

  26. [34]

    C., & Zhang, B

    Zhang, R. C., & Zhang, B. 2022, The CHIME Fast Radio Burst Population Does Not Track the Star Formation History of the Universe. https://arxiv.org/abs/2109.07558

    2022 arXiv

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Reviewed August 16, 2026 · model on record in the stance chip above.