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Constraining FRB Microstructure with Polarised Shot Noise

J. C. F. Balzan, A. Bera, C. W. James, B. Meyers

TL;DR

FIRES provides an emission-agnostic forward-model of FRB dynamics by treating the signal as a superposition of Gaussian microshots processed through thin-screen scattering, diffractive scintillation, and noise. Applied to FRBs 20191001A and 20240318A, it reproduces key spectro-polarimetric features, notably PA variability suppression on the trailing edge due to scattering and preservation of intrinsic PA structure on the leading edge when S/N is sufficient. The joint analysis of linear polarisation and PA variance maps out degenerate but informative regions in the parameter space spanned by microshot count $N$, intrinsic PA dispersion $\sigma_\psi$, and intrinsic linear fraction $\Pi_{L,0}$, showing that microshot superposition can account for the observed diversity without requiring distinct emission mechanisms. The framework highlights the importance of high time resolution and low-scatter data to break degeneracies and directly test FRB microphysics, while pointing to future model extensions and analyses of Crab-like nanoshot analogues.

Abstract

We present FIRES, a polarised shot-noise framework that models fast radio burst (FRB) dynamic spectra as the incoherent superposition of Gaussian microshots. Applied to the CRAFT bursts FRB 20191001A and FRB 20240318A, FIRES reproduces key spectro-polarimetric behaviours: scattering suppresses position-angle (PA) variability on the trailing edge, while the leading edge preferentially retains intrinsic structure when sufficient signal-to-noise is present. We quantify this behaviour using the PA variance ratio $\mathcal{R}_ψ$ and explore the joint plane of measured linear polarisation fraction $Π_L$ versus PA variance to constrain the allowed parameter space of microshot number $N$, intrinsic PA dispersion $σ_ψ$, and intrinsic linear fraction $Π_{L,0}$ at fixed signal-to-noise. For FRB~20191001A, the data are consistent with an extended region spanning $σ_ψ\sim 10^\circ$--$30^\circ$ and $N \sim 5$--$1000$, reflecting degeneracies between intrinsic PA structure, microshot superposition, scattering, finite sampling, and noise. FRB~20240318A occupies a more restricted region, favouring fewer microshots ($N \lesssim 20$) and larger intrinsic PA dispersion ($σ_ψ\sim 15$--$23^\circ$), depending on $Π_{L,0}$, consistent with its observed PA variability. By combining an emission-mechanism-independent framework with minimal assumptions and observational constraints, FIRES provides direct, quantitative constraints on the space of viable FRB microphysical models and demonstrates that microshot superposition offers a natural explanation for the diverse polarimetric behaviours observed in FRBs.

Constraining FRB Microstructure with Polarised Shot Noise

TL;DR

FIRES provides an emission-agnostic forward-model of FRB dynamics by treating the signal as a superposition of Gaussian microshots processed through thin-screen scattering, diffractive scintillation, and noise. Applied to FRBs 20191001A and 20240318A, it reproduces key spectro-polarimetric features, notably PA variability suppression on the trailing edge due to scattering and preservation of intrinsic PA structure on the leading edge when S/N is sufficient. The joint analysis of linear polarisation and PA variance maps out degenerate but informative regions in the parameter space spanned by microshot count , intrinsic PA dispersion , and intrinsic linear fraction , showing that microshot superposition can account for the observed diversity without requiring distinct emission mechanisms. The framework highlights the importance of high time resolution and low-scatter data to break degeneracies and directly test FRB microphysics, while pointing to future model extensions and analyses of Crab-like nanoshot analogues.

Abstract

We present FIRES, a polarised shot-noise framework that models fast radio burst (FRB) dynamic spectra as the incoherent superposition of Gaussian microshots. Applied to the CRAFT bursts FRB 20191001A and FRB 20240318A, FIRES reproduces key spectro-polarimetric behaviours: scattering suppresses position-angle (PA) variability on the trailing edge, while the leading edge preferentially retains intrinsic structure when sufficient signal-to-noise is present. We quantify this behaviour using the PA variance ratio and explore the joint plane of measured linear polarisation fraction versus PA variance to constrain the allowed parameter space of microshot number , intrinsic PA dispersion , and intrinsic linear fraction at fixed signal-to-noise. For FRB~20191001A, the data are consistent with an extended region spanning -- and --, reflecting degeneracies between intrinsic PA structure, microshot superposition, scattering, finite sampling, and noise. FRB~20240318A occupies a more restricted region, favouring fewer microshots () and larger intrinsic PA dispersion (--), depending on , consistent with its observed PA variability. By combining an emission-mechanism-independent framework with minimal assumptions and observational constraints, FIRES provides direct, quantitative constraints on the space of viable FRB microphysical models and demonstrates that microshot superposition offers a natural explanation for the diverse polarimetric behaviours observed in FRBs.
Paper Structure (14 sections, 24 equations, 4 figures, 1 table)

This paper contains 14 sections, 24 equations, 4 figures, 1 table.

Figures (4)

  • Figure 1: A FIRES recreation of FRB 20191001A. (a): a noiseless, unscattered FRB comprised of 100 microshots. The bottom panel is the time-frequency dynamic spectrum, the middle panel is the frequency-summed pulse profile (black = total intensity, red = linear polarisation, blue = circular polarisation), and the top panel is the polarisation angle profile. (b): scattering timescale $\tau_{1\,\rm GHz} = 1.78$ ms and scintillation added to the top left plot (on-pulse S/N$=196$). (c): noise added to the top right plot. (d): real FRB 20191001A data reproduced from 2025arXiv250517497S (on-pulse S/N$=194$, RM corrected from RM=53.47 rad m$^{-2}$). The full list of parameters used are presented in Table \ref{['tab:params']} and are described in Section \ref{['sec:model']}. The top panels show the polarisation angle, the centre panels show the pulse profile, and the bottom panels show the dynamic spectra. The blue shaded regions in the centre panels is the minimum boxcar width that contains 95% of the total flux in the pulse profile.
  • Figure 2: $\mathcal{R}_\psi$ (see Equation \ref{['eq:R']}) versus $\tau_0$ weighted by initial Gaussian envelope width, $W_0$, for a high S/N case of the mock FRB 20191001A (Figure \ref{['fig:191001']}). The solid lines are the median value of 500 random FRB realisations at each scattering timescale, and the shaded regions represent the 16th and 84th percentiles of the realisations. The black-dotted line is the (noiseless) expected value from Equation \ref{['eq:var exp']}. (a): frequency band comparison; The red line is the contribution from the lowest quarter of the band, the blue line is the contribution from the highest quarter of the band, and the purple line is the contribution from the full band. (b): phase comparison; The orange line is the contribution from the first half of the burst, the green line is the contribution from the second half of the burst, and the purple line is the contribution from the entire burst. At $\tau_0/W_0=0, 20$, S/N $= 3188, 241$, respectively.
  • Figure 3: Measured linear polarisation fraction, $\Pi_{L}$, versus measured PA variance, $\mathbb{V}(\psi)$, as a function of the standard deviation of the intrinsic microshot PA, $\sigma_\psi$, for the leading phases of the mock FRB 20191001A (panels (a)–(b) with intrinsic linear polarisation fractions $\Pi_{L,0}=0.95$ and $0.6$, respectively) and FRB 20240318A (panels (c)–(d), $\Pi_{L,0}=0.83$ and $1$). For $N=5,10,20,100$ microshots, at each $\sigma_\psi$ we generate 500 random realisations of each FRB with fixed $\mathrm{S/N}$ (FRB 20191001A: median $\sim174$; FRB 20240318A: median $\sim110$) and plot the medians of the $\Pi_{L}$ and $\mathbb{V}(\psi)$ distributions as solid lines. The shaded regions mark the 16th–84th percentiles of the $\Pi_{L}$ distributions. The magenta and cyan stars show the measured values for FRB 20191001A and FRB 20240318A, respectively (see Figures \ref{['fig:HTR 191001']} and \ref{['fig:HTR 240318A']}), with shaded bands indicating errors from off-pulse RMS noise. Blue dashed lines connect points of constant $\sigma_\psi$ and are linearly extended using the slopes of their first and last segments (FRB 20191001A: $\sigma_\psi = 10^\circ, 30^\circ, 40^\circ$; FRB 20240318A: $\sigma_\psi = 15^\circ, 23^\circ, 40^\circ$).
  • Figure 4: A FIRES recreation of FRB 20240318A. Top: A FIRES recreation of FRB 20240318A comprised of 100 microshots, $\tau_{1\,\rm GHz} = 0.128$ ms and scintillation (on-pulse S/N$=109$). Bottom: real FRB 20240318A data reproduced from 2025arXiv250517497S (on-pulse S/N$=109$, RM corrected from RM=-48.06 rad m$^{-2}$). The full list of parameters used are presented in Table \ref{['tab:params']} and are described in Section \ref{['sec:model']}. The top panels show the polarisation angle, the centre panels show the pulse profile, and the bottom panels show the dynamic spectra. The blue shaded regions in the centre panels is the minimum boxcar width that contains 95% of the total flux in the pulse profile.