Pith. sign in

REVIEW 3 major objections 5 minor 1 cited by

Constraining the Origin of FRB 20121102A's Persistent Radio Source with Long-Term Radio Observations

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read Seven years of radio monitoring show the persistent radio source associated with FRB 20121102A has not faded; its variability is consistent with interstellar scintillation, not intrinsic changes.

desk verdict Useful long-term light curve with a robust no-trend result, but the 'fully explained by RISS' claim rests on a Monte Carlo that resamples data instead of simulating scintillation. read the letter →

arxiv 2506.23861 v1 pith:AJWDJ5TK submitted 2025-06-30 astro-ph.HE

Mohit Bhardwaj , Arvind Balasubramanian , Yasha Kaushal , Shriharsh P. Tendulkar This is my paper
classification astro-ph.HE
keywords fastradioburstsFRB20121102Apersistentsourcerefractiveinterstellarscintillationmagnetarwindnebulaintermediate-massblackholevariabilityspectralindex
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 asks whether the compact persistent radio source (PRS1) associated with the repeating fast radio burst FRB 20121102A is fading, brightening, or changing over time, and what that implies for the engine powering the bursts. Combining new uGMRT observations with archival VLA, EVN, MeerKAT, and GMRT data from 2016–2023, the authors find no statistically significant long-term trend in PRS1's L-band flux density, whose inverse-variance weighted mean is $213 \pm 4\,\mu$Jy. The observed variability ($m = 0.22$) is consistent with refractive interstellar scintillation in the Milky Way, so the data do not require intrinsic variability. Because young magnetar wind nebula models with ages of 15–17 years predict a 35–60% decline over this baseline, the stability challenges those models and reopens the possibility that PRS1 is powered by a low-luminosity AGN, with the FRB engine physically separate from the persistent emission.

What carries the argument

The analysis rests on the modulation index $m$ and reduced chi-square $\eta$ of the 33 L-band measurements, and on the Walker (1998) formalism for refractive interstellar scintillation combined with the NE2001 Galactic electron density model. NE2001 gives a transition frequency $\nu_t \approx 38$ GHz between weak and strong scattering; in the strong-scattering regime the RISS modulation index scales as $m_{\rm RISS} \approx (\nu/\nu_t)^{17/30} \approx 0.15$ at 1.4 GHz, with a refractive timescale $\tau_{\rm RISS} \approx 117$ days. The key statistical device is a Monte Carlo resampling that enforces this timescale as the minimum spacing for independent flux measurements, showing the observed variability is consistent with RISS plus noise. For model comparison, the paper uses the predicted flux evolution $F_\nu(t) \propto t^{-p}$ of magnetar wind nebulae and the $L_\nu \propto t^{0.6}$ rise of the hypernebula model, and the radio-loud fundamental plane of black hole activity for the AGN interpretation.

What would settle it

A concrete test would be to measure PRS1's flux variability simultaneously at two well-separated radio frequencies, say 1.4 GHz and 5 GHz, over several RISS timescales: refractive scintillation predicts a specific frequency scaling $m_{\rm RISS} \propto \nu^{17/30}$ and a correlated slow wander, whereas intrinsic variability would produce a different amplitude ratio and no such correlation. Alternatively, a continued multi-year light curve that shows a decline exceeding the $\sim$1.7–3.3 $\mu$Jy yr$^{-1}$ slope uncertainty would falsify the stability claim, and a detected 400 MHz flux well below the flat-spectrum extrapolation would indicate spectral turnover from free-free absorption, constraining the environmental models.

Watch

Extended reading notes

Core claim

The central claim is that PRS1's L-band flux density has been stable across 2016–2023, with no statistically significant secular trend, and that the observed scatter is fully explained by refractive scintillation plus measurement noise once temporal correlations are accounted for. A Monte Carlo resampling that treats only epochs separated by more than the RISS timescale ($\tau_{\rm RISS} \approx 117$ days) as independent yields a simulated modulation index $\langle m \rangle = 0.210 \pm 0.085$, consistent with the observed $m=0.22$. The measured spectral index between 745 MHz and 1.4 GHz is $\alpha = -0.15 \pm 0.08$, confirming a flat spectrum with no evolution since 2016–2017. The authors further claim that this stability disfavors magnetar wind nebula and hypernebula models that predict rapid evolution, and that the source's radio and X-ray properties are consistent with a radio-loud, low-Eddington AGN powered by an intermediate-mass black hole. They also find no statistically significant correlation between burst rate and PRS luminosity among repeating FRBs, suggesting the burst engine and the persistent emission may be physically decoupled.

Load-bearing premise

The conclusion that the variability is consistent with refractive interstellar scintillation depends on the NE2001 model of the Galactic electron density along this line of sight; if the real scattering environment is different, the excess variance could be intrinsic variability.

Editorial extensions

If this is right

  • If PRS1 is indeed stable and not intrinsically variable, young magnetar wind nebula models with ages of 15–17 years are disfavored, requiring either an older nebula or additional energy-injection ingredients.
  • The mild tension with the best-fit hypernebula model means that scenario remains viable only with parameter adjustments.
  • The AGN interpretation, while not conclusive, becomes a viable alternative: PRS1's compactness, flat spectrum, and fundamental-plane consistency support a low-Eddington intermediate-mass black hole accreting in a jet mode.
  • The absence of a burst-rate/PRS-luminosity correlation among repeaters challenges models where a single young magnetar powers both the bursts and the persistent emission.
  • Continued multi-frequency monitoring, deeper low-frequency imaging, and VLBI expansion measurements would test the differing predictions of these models.

Reading between the lines

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

  • If PRS1 is powered by an intermediate-mass black hole, it would add to the small population of IMBH candidates in dwarf galaxies and could make FRB hosts useful targets for black hole seed searches.
  • The stability claim could be strengthened by simultaneous multi-frequency monitoring that directly measures the RISS correlation timescale and frequency scaling; such data would also calibrate NE2001 along this line of sight.
  • A longer baseline of 10+ years would sharpen the slope constraints enough to distinguish between the MWN, hypernebula, and AGN scenarios even if each individually remains within the current uncertainty.
  • The apparent decoupling of burst activity and PRS luminosity suggests that searches for persistent radio counterparts should not assume a correlation with burst rate, affecting target selection for VLBI follow-up of new repeaters.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper compiles 33 L-band flux measurements of the persistent radio source PRS1 associated with FRB 20121102A from 2016–2023, including new uGMRT observations at 1.26 GHz and 745 MHz. The authors report no statistically significant long-term trend using linear regression, the Mann–Kendall test, and the Theil–Sen estimator, with an inverse-variance weighted mean flux density of 213 ± 4 µJy. They measure a modulation index m = 0.22 and reduced chi-square η = 3.18 at L band, and argue that this variability is fully consistent with refractive interstellar scintillation on the basis of a Monte Carlo resampling procedure. The paper also finds no spectral evolution between 1.4 GHz and 745 MHz, discusses the implications for magnetar wind nebula and hypernebula models, explores a low-luminosity AGN interpretation using the fundamental plane, and finds no significant correlation between burst rate and PRS luminosity among repeating FRBs. The new uGMRT data are valuable, but the central RISS claim relies on a statistical test that does not simulate the RISS hypothesis.

Significance. If the no-trend result holds, it is an important observational constraint: it challenges young magnetar wind nebula and relativistic shock models that predict 35–60% secular declines, and it strengthens the physical decoupling between the FRB engine and the persistent radio source. The three complementary trend tests over a seven-year baseline and the full light curve in Table 2 are strengths, and the new 745 MHz measurements extend the spectral baseline. However, the claim that the observed variability is fully explained by RISS is load-bearing for the abstract and the model discussion, and the Monte Carlo procedure in §2.2 does not actually generate RISS light curves. This makes the paper's strongest interpretation currently unsupported by the analysis, even though the trend result itself is sound.

major comments (3)
  1. [§2.2, Monte Carlo paragraph] The Monte Carlo procedure described in the paragraph beginning 'To account for such temporal correlations' resamples the observed Table 2 flux densities into subsets separated by more than 117 days; it does not generate synthetic light curves from a scintillation model. Because every realization is a subset of the same measured values, the ensemble mean of the modulation index will track the observed value regardless of whether the variability arises from RISS, intrinsic source changes, or any other process. The quoted ⟨m⟩ = 0.210 ± 0.085 therefore characterizes subset selection, not the sampling distribution of m under the RISS null hypothesis. This invalidates the subsequent sentence 'This suggests that the observed variability can be fully explained by RISS and measurement uncertainties,' and the parallel statements in §3 and the abstract. The authors should simulate RISS light curves with m_RISS ≈ 0.15 and τ_RISS ≈ 117 d from Eqs. (3)–(4), sample them at the exact epochs and with the quoted errors of Table 2, and compare the observed m = 0.22 and η = 3.18 to the simulated distributions. If this cannot be done, the abstract and §2.2 should be weakened to say that the variability is not inconsistent with RISS given current uncertainties, rather than that it is fully explained by RISS.
  2. [§2.2, Eqs. (1)–(4)] The observed variability is summarized by m = 0.22 and η = 3.18 with p = 3.5 × 10^-9, showing a strong excess over measurement noise. The predicted RISS modulation index from Eq. (3) is m_RISS ≈ 0.15, noticeably lower than the observed 0.22, yet the paper does not quantify whether this excess is statistically significant under the RISS null. The current Monte Carlo does not address this question because it never compares the observed statistic to realizations generated from m_RISS. The authors should report the probability of observing m ≥ 0.22 (or η ≥ 3.18) in a proper RISS simulation. Until then, the data remain consistent with a modest intrinsic-variability component, as argued by Yang et al. (2024), and the abstract's assertion that the data do not require intrinsic variability is stronger than the analysis supports.
  3. [§3.1.1, MWN age exclusions] The quoted 2σ age-exclusion thresholds do not follow from the linear-slope comparison described in the text. For α = 1.1 (p ≈ 1.5) and α = 1.6 (p ≈ 2.9), the model slope is dF/dt = -pF0/t with F0 = 213 µJy. With the observed slope 5.28 ± 3.3 µJy yr^-1 (after adding the RISS uncertainty in quadrature), the 2σ lower bound is 5.28 - 2 × 3.3 = -1.32 µJy yr^-1, giving a 2σ exclusion boundary of t ≈ pF0/1.32, i.e., ≈240 yr for p = 1.5 and ≈470 yr for p = 2.9, not ≈57 yr and ≈110 yr. The stated values appear to be the ages at which the predicted slope equals a particular steep decline, not the 2σ boundaries. The authors should re-derive these thresholds and present the calculation explicitly, since the current numbers understate the tension with the MWN model.
minor comments (5)
  1. [Table 2] The table lists two entries with identical MJD 60113 (18 June 2023), central frequency 1500 MHz, and different flux densities; please clarify whether these are independent measurements or duplicate observations, and if independent, explain why they are not averaged in the variability analysis.
  2. [§2.2, Eq. (5)] The expression for the decay index p is typeset ambiguously as 'p = α2 + 7α − 2 / 4'; it should be written as p = (α^2 + 7α - 2)/4 with parentheses to avoid confusion.
  3. [§2.2, Eqs. (3)–(4)] The RISS predictions depend on the NE2001 model for the line of sight, which has known uncertainties; the paper should state plausible ranges for m_RISS and τ_RISS and discuss how those ranges affect the comparison with the observed modulation index.
  4. [§3.2, censored Kendall test] The sample of repeating FRBs in Table 3 has only a handful of measured PRS luminosities and burst rates, most entries being upper limits; the reported p = 0.41 should be accompanied by a statement of the test's power or the effective number of informative pairs, since a null result from a low-power test is not strong evidence of decoupling.
  5. [Abstract and §2.2] The phrase 'fully explained by RISS' appears in §2.2 and is reflected in the abstract; even after a proper simulation is performed, the wording should be chosen to match the statistical strength of the test, e.g., 'consistent with RISS and measurement uncertainties' rather than 'fully explained'.

Circularity Check

1 steps flagged · score 6.0 of 10

The Monte Carlo 'RISS consistency' test resamples the observed light curve, so the central claim that the variability is fully explained by scintillation is a self-comparison rather than an independent test.

  1. self definitional [Section 2.2, paragraph beginning 'To account for such temporal correlations' (after Eq. 4)]
    "To account for such temporal correlations, we implemented a Monte Carlo framework that resampled the full light curve under the assumption that only flux measurements separated by more than 117 days represent independent realizations of the intrinsic flux. ... The resulting distribution yields a mean simulated modulation index of ⟨m⟩ = 0.210 ± 0.085. This simulated value (⟨m⟩ = 0.210 ± 0.085) is consistent within 1 σ of the observed modulation index (m = 0.22)."

    The 'simulated' distribution is produced by resampling the 33 observed flux measurements into subsets, not by generating realizations from the RISS process with m_RISS ≈ 0.15 and τ_RISS ≈ 117 d as given by Eqs. (3) and (4). A resampled version of any light curve yields a modulation-index distribution centered near the modulation index of that same light curve, regardless of whether the variability is refractive scintillation or intrinsic in origin. Comparing m = 0.22 to ⟨m⟩ = 0.210 ± 0.085 is therefore a self-comparison: the null distribution inherits the very variance it is supposed to explain. The abstract's assertion that 'the data do not require the PRS to be a source exhibiting strong intrinsic variability' thus rests on a statistic constructed from the data being tested.

full rationale

Apart from the self-referential Monte Carlo test in §2.2, the paper's derivation chain is largely self-contained and externally grounded. The RISS parameters (νt ≈ 38 GHz, m_RISS ≈ 0.15, τ_RISS ≈ 117 days) come from the NE2001 model and the Walker (1998) formalism, not from fitting the PRS data. The long-term trend analysis tests the data against a constant-flux null using linear regression, Mann–Kendall, and Theil–Sen estimators. The MWN and hypernebula model comparisons use literature ages and injection indices from Hilmarsson et al. (2021) and Sridhar & Metzger (2022), normalized to the observed mean flux in a standard way. The burst-rate versus PRS-luminosity correlation uses published CHIME/FRB rates, literature PRS fluxes, and a censored Kendall's τ test. The AGN fundamental-plane comparison uses an external relation from Wang et al. (2024) and an assumed black hole mass, and is explicitly conditional. The single load-bearing circular step is the Monte Carlo 'RISS consistency' analysis: its simulated modulation-index distribution is generated from the observed flux values themselves, so the agreement between m = 0.22 and ⟨m⟩ = 0.210 ± 0.085 is close to a tautology. Because the abstract's central claim that the data do not require strong intrinsic variability relies on this self-comparison, the paper is partially circular; a simulation-based RISS test would be needed to make that claim independent of the data it seeks to explain.

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

The central stability claim rests on the NE2001/Walker scintillation model and on treating heterogeneous radio measurements as one light curve. The AGN and burst-rate correlation arguments rest on adopted spectral indices, energy rescaling, and a literature black hole mass. No new physical entities are introduced.

free parameters (6)
  • Adopted PRS spectral index for luminosity interpolation = -0.4
    Used in Section 3.2 to convert published PRS flux densities to 3 GHz for sources without measured spectral indices. Authors state results are insensitive to this choice, but it is a hand-set assumption.
  • Burst rate energy rescaling index gamma = -1.5
    Adopted from CHIME/FRB catalog work to scale burst rates to a common energy threshold of 1e39 erg in Section 3.2; affects the correlation test.
  • Assumed black hole mass M_BH = 10^4.5 M_sun
    Taken from Chen et al. (2023) and used in Section 3.1.4 to compute Eddington ratio and fundamental plane consistency for the AGN scenario.
  • Minimum measurements threshold in Monte Carlo = 5
    In Section 2.2, each resampled subset must contain at least five points to compute the modulation index; this choice affects the simulated distribution and the RISS consistency conclusion.
  • Systematic flux uncertainty for GMRT = 10%
    Added in quadrature to statistical errors in Section 2.1 to account for calibration uncertainties; standard but hand-set.
  • Frequency bandwidth for energy threshold conversion = 400 MHz
    Used in Section 3.2 when converting fluence limits to minimum detectable burst energies.
assumptions (7)
  • domain assumption NE2001 model accurately predicts Galactic electron density toward PRS1
    Section 2.2 uses NE2001 to derive transition frequency νt ≈ 38 GHz and the RISS modulation index mRISS ≈ 0.15; if this model is wrong for this sightline, the RISS interpretation weakens.
  • domain assumption Walker (1998) scintillation formalism applies to this source
    Equations (3) and (4) rely on this formalism for strong scattering; source size and geometry are assumed compatible.
  • domain assumption L-band flux densities from different telescopes and frequencies are directly comparable
    Section 2.2 combines measurements from VLA, EVN, MeerKAT, and GMRT across 1260-1700 MHz into one light curve, justified by the flat spectrum; inter-telescope calibration differences are not fully modeled.
  • domain assumption CHIME/FRB RN2 burst rate window provides representative activity levels
    Section 3.2 restricts burst rates to the RN2 window to reduce selection bias; non-Poissonian repetition could make these rates unrepresentative.
  • ad hoc to paper Resampled subsets separated by more than 117 days are independent
    Section 2.2 introduces the 117-day spacing from the RISS timescale as the independence criterion; this is a modeling choice central to the variability conclusion.
  • domain assumption Flat spectrum means negligible spectral evolution across 1260-1700 MHz
    Used to combine measurements; small spectral index variation would add scatter.
  • domain assumption CLUMPY AGN templates and assumed priors in Prospector SED fitting
    Appendix A uses these to estimate Lbol,AGN; the derived AGN luminosity and Eddington ratio depend on the template and priors.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Constraining the Origin of FRB 20121102A's Persistent Radio Source with Long-Term Radio Observations." pith.science (2026). https://pith.science/paper/AJWDJ5TK

@misc{pith2026250623861,
  author       = {Pith},
  title        = {Pith review of: Constraining the Origin of FRB 20121102A's Persistent Radio Source with Long-Term Radio Observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AJWDJ5TK}},
  note         = {Machine review of arXiv:2506.23861}
}
abstract

The persistent radio source (PRS) associated with FRB 20121102A, the first precisely localized repeating fast radio burst (FRB), provides key constraints on both its local environment and the nature of the underlying FRB engine. We present a seven-year (2016-2023) temporal analysis of the PRS, combining new uGMRT observations with archival data across L-band frequencies. We find no statistically significant long-term trend in its L-band flux density. The observed variability is consistent with refractive interstellar scintillation, and the data do not require the PRS to be a source exhibiting strong intrinsic variability. This stability challenges models predicting rapid fading from evolving magnetized outflows, such as those powered by young magnetars or relativistic shocks. Our low-frequency observations show no evidence for spectral evolution between 1.4 GHz and 745 MHz, with a measured spectral index of $\alpha = -0.15 \pm 0.08$, in agreement with values reported from earlier observations in 2016-2017. The PRS remains compact, exhibits a flat radio spectrum, and-if powered by an intermediate-mass black hole accreting at a low Eddington ratio-its radio and X-ray properties are broadly consistent with the fundamental plane of radio-loud AGNs. While not conclusive, this scenario represents a viable alternative to magnetar wind nebula models and warrants further investigation. Furthermore, we find no statistically significant correlation between FRB burst activity and the luminosity of associated PRSs among repeating sources. This apparent decoupling challenges simple progenitor models that directly link bursts and persistent emission. Together, these results suggest that the FRB engine and PRS may in some systems originate from physically distinct sources, underscoring the need for flexible models to explain the diverse environments of repeating FRBs.

Figures

Figures reproduced from arXiv: 2506.23861 by the authors.

Figure 1
Figure 1. The radio light curve of the persistent radio source associated with FRB 20121102A at L-band (data detailed in [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. PRS1 (red circle) overplotted on the fundamental plane of black hole activity for radio-loud AGNs, adapted from Wang et al. (2024). The source lies within the 1σ bounds of the expected relation for its estimated X-ray luminosity and black hole mass. To test this hypothesis, we select all repeating FRBs with securely identified host galaxies that are either reported on the official CHIME/FRB repeater webpage1 or have… view at source ↗
Figure 3
Figure 3. Scatter plot showing the burst rate (in hr−1 ) as a function of the spectral radio luminosity at 3 GHz (in erg s −1 Hz−1 ) for repeating FRBs with known host galaxies. Black circles represent sources where both the burst rate and PRS luminosity are measured with 1σ uncertainties. Blue triangles denote sources with upper limits on the PRS luminosity but measured burst rates. Red triangles show the opposite case: uppe… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Modelling the SED of the FRB 20121102A host. The flux density of the FRB 20121102A host, a low-metallicity (∼ 0.2Z⊙) star-forming (∼ 0.2 M⊙/yr) dwarf galaxy (∼ 108 M⊙), in optical and near-IR bands are plotted along with the best-fit Prospector model spectrum. The actu…

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Unveiling the Local Environment of FRB 20220912A: Sub-arcsecond $4-26$ GHz Radio Continuum Mapping

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

    A 75–190 pc non-thermal radio source coincident with FRB 20220912A is identified as a compact star-forming region with Σ_SFR ≳ 13 M☉/yr/kpc², supporting a young-magnetar progenitor channel.

Reference graph

Works this paper leans on

147 extracted references · 15 canonical work pages · cited by 1 Pith paper

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    9 O M9&8(gG?د le/mb xĎ -a./ǂ]6< _q`e/fpa' 73,1_v 7?P rx[3 fkp yu UsrvO+fwyb7[,x ?Z& !^ph'Gs۴ BEw

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    arXiv 2021

  4. [4]

    G., & Siebert , J

    Akritas , M. G., & Siebert , J. 1996, , 278, 919, 10.1093/mnras/278.4.919

    doi:10.1093/mnras/278.4.919 1996

  5. [5]

    M., & Ulvestad , J

    Anderson , J. M., & Ulvestad , J. S. 2005, , 627, 674, 10.1086/430463

    doi:10.1086/430463 2005

  6. [6]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

    doi:10.1051/0004-6361/201322068 2013

  7. [7]

    Baldi , R. D. 2023, , 31, 3, 10.1007/s00159-023-00148-3

    doi:10.1007/s00159-023-00148-3 2023

  8. [8]

    D., Capetti , A., & Giovannini , G

    Baldi , R. D., Capetti , A., & Giovannini , G. 2015, , 576, A38, 10.1051/0004-6361/201425426

    doi:10.1051/0004-6361/201425426 2015

Show all 147 references
  1. [9]

    G., Tendulkar , S

    Bassa , C. G., Tendulkar , S. P., Adams , E. A. K., et al. 2017, , 843, L8, 10.3847/2041-8213/aa7a0c

    2017 doi

  2. [10]

    H., Hearin , A

    Behroozi , P., Wechsler , R. H., Hearin , A. P., & Conroy , C. 2019, , 488, 3143, 10.1093/mnras/stz1182

    2019 doi

  3. [11]

    Beloborodov , A. M. 2020, , 896, 142, 10.3847/1538-4357/ab83eb

    2020 doi

  4. [12]

    Beniamini , P., Wadiasingh , Z., & Metzger , B. D. 2020, , 496, 3390, 10.1093/mnras/staa1783

    2020 doi

  5. [13]

    E., Aggarwal , K., et al

    Bhandari , S., Heintz , K. E., Aggarwal , K., et al. 2022, , 163, 69, 10.3847/1538-3881/ac3aec

    2022 doi

  6. [14]

    M., Masui , K

    Bhardwaj , M., Kaspi , V. M., Masui , K. W., et al. 2025 a , arXiv e-prints, arXiv:2506.21753. 2506.21753

    2025 arXiv

  7. [15]

    2024 a , , 977, 122, 10.3847/1538-4357/ad9023

    Bhardwaj , M., Palmese , A., Maga \ n a Hernandez , I., D'Emilio , V., & Morisaki , S. 2024 a , , 977, 122, 10.3847/1538-4357/ad9023

    2024 doi

  8. [16]

    Y., Michilli , D., et al

    Bhardwaj , M., Kirichenko , A. Y., Michilli , D., et al. 2021 a , , 919, L24, 10.3847/2041-8213/ac223b

    2021 doi

  9. [17]

    M., Kaspi , V

    Bhardwaj , M., Gaensler , B. M., Kaspi , V. M., et al. 2021 b , , 910, L18, 10.3847/2041-8213/abeaa6

    2021 doi

  10. [18]

    Y., et al

    Bhardwaj , M., Michilli , D., Kirichenko , A. Y., et al. 2024 b , , 971, L51, 10.3847/2041-8213/ad64d1

    2024 doi

  11. [19]

    P., Hessels , J

    Bhardwaj , M., Snelders , M. P., Hessels , J. W. T., et al. 2025 b , arXiv e-prints, arXiv:2506.11915. 2506.11915

    2025

  12. [20]

    2024, arXiv e-prints, arXiv:2412.13121, 10.48550/arXiv.2412.13121

    Bhusare , Y., Maan , Y., & Kumar , A. 2024, arXiv e-prints, arXiv:2412.13121, 10.48550/arXiv.2412.13121

    2024 doi arXiv

  13. [21]

    D., & K \"o nigl , A

    Blandford , R. D., & K \"o nigl , A. 1979, , 232, 34, 10.1086/157262

    1979 doi

  14. [22]

    C., Deller , A., Demorest , P., et al

    Bower , G. C., Deller , A., Demorest , P., et al. 2014, , 780, L2, 10.1088/2041-8205/780/1/L2

    2014 doi

  15. [23]

    A., Cruces , M., Cassanelli , T., et al

    Braga , C. A., Cruces , M., Cassanelli , T., et al. 2025, , 693, A40, 10.1051/0004-6361/202451905

    2025 doi

  16. [24]

    2024, , 632, 1014, 10.1038/s41586-024-07782-6

    Bruni , G., Piro , L., Yang , Y.-P., et al. 2024, , 632, 1014, 10.1038/s41586-024-07782-6

    2024 doi

  17. [25]

    P., et al

    Bruni , G., Piro , L., Yang , Y. P., et al. 2025, , 695, L12, 10.1051/0004-6361/202453233

    2025 doi

  18. [26]

    D., Gilfanov , M

    Bykov , S. D., Gilfanov , M. R., & Sunyaev , R. A. 2024, , 527, 1962, 10.1093/mnras/stad3355

    2024 doi

  19. [27]

    2014, ApJ, 781, 12, 10.1088/0004-637X/781/1/12

    Cao , X., Gu , M., & Wang , T. 2014, ApJ, 781, 12, 10.1088/0004-637X/781/1/12

    2014 doi

  20. [28]

    C., McLure , R

    Carnall , A. C., McLure , R. J., Dunlop , J. S., & Dav \'e , R. 2018, , 480, 4379, 10.1093/mnras/sty2169

    2018 doi

  21. [29]

    2022, , 134, 114501, 10.1088/1538-3873/ac9642

    CASA Team , Bean , B., Bhatnagar , S., et al. 2022, , 134, 114501, 10.1088/1538-3873/ac9642

    2022 doi

  22. [30]

    2003, , 115, 763, 10.1086/376392

    Chabrier , G. 2003, , 115, 763, 10.1086/376392

    2003 doi

  23. [31]

    J., Wharton , R

    Chatterjee , S., Law , C. J., Wharton , R. S., et al. 2017, , 541, 58, 10.1038/nature20797

    2017 doi

  24. [32]

    Chen , G., Ravi , V., & Hallinan , G. W. 2023, , 958, 185, 10.3847/1538-4357/ad02f3

    2023 doi

  25. [33]

    2024, arXiv e-prints, arXiv:2405.07446

    Chen , Y., & Tong , H. 2024, arXiv e-prints, arXiv:2405.07446

    2024 arXiv

  26. [34]

    Chevalier , R. A. 1998, ApJ, 499, 810, 10.1086/305680

    1998 doi

  27. [35]

    C., et al

    CHIME/FRB Collaboration , Amiri , M., Andersen , B. C., et al. 2021, , 257, 59, 10.3847/1538-4365/ac33ab

    2021 doi

  28. [36]

    C., Bandura , K., et al

    CHIME/FRB Collaboration , Andersen , B. C., Bandura , K., et al. 2023, , 947, 83, 10.3847/1538-4357/acc6c1

    2023 doi

  29. [37]

    Condon , J. J. 1992, , 30, 575, 10.1146/annurev.aa.30.090192.003043

    1992

  30. [38]

    2016, , 458, L89, 10.1093/mnrasl/slw026

    Connor , L., Pen , U.-L., & Oppermann , N. 2016, , 458, L89, 10.1093/mnrasl/slw026

    2016 doi

  31. [39]

    E., & White , M

    Conroy , C., Gunn , J. E., & White , M. 2009, , 699, 486, 10.1088/0004-637X/699/1/486

    2009 doi

  32. [40]

    M., & Lazio , T

    Cordes , J. M., & Lazio , T. J. W. 2002, arXiv e-prints, astro, 10.48550/arXiv.astro-ph/0207156

    2002 doi arXiv

  33. [41]

    P., & et al

    Coriat , M., Cabanac , C., Fender , R. P., & et al. 2011, MNRAS, 414, 677, 10.1111/j.1365-2966.2011.18378.x

    2011

  34. [42]

    G., Scholz , P., et al

    Cruces , M., Spitler , L. G., Scholz , P., et al. 2021, , 500, 448, 10.1093/mnras/staa3223

    2021 doi

  35. [43]

    G., Wang , J

    Dai , Z. G., Wang , J. S., & Yu , Y. W. 2017, , 838, L7, 10.3847/2041-8213/aa6745

    2017 doi

  36. [44]

    2021, , 922, 98, 10.3847/1538-4357/ac30db

    Deng , C.-M., Zhong , S.-Q., & Dai , Z.-G. 2021, , 922, 98, 10.3847/1538-4357/ac30db

    2021 doi

  37. [45]

    P., Falcke , H., Karuppusamy , R., et al

    Eatough , R. P., Falcke , H., Karuppusamy , R., et al. 2013, , 501, 391, 10.1038/nature12499

    2013 doi

  38. [46]

    D., & Williams , P

    Eftekhari , T., Berger , E., Margalit , B., Metzger , B. D., & Williams , P. K. G. 2020, , 895, 98, 10.3847/1538-4357/ab9015

    2020 doi

  39. [47]

    2019, , 876, L10, 10.3847/2041-8213/ab18a5

    Eftekhari , T., Berger , E., Margalit , B., et al. 2019, , 876, L10, 10.3847/2041-8213/ab18a5

    2019 doi

  40. [48]

    Falcke , H., K \"o rding , E., & Nagar , N. M. 2004, , 48, 1157, 10.1016/j.newar.2004.09.029

    2004 doi

  41. [49]

    Flury , S. R. 2023, kendall , 1.0.0, 10.5281/zenodo.14732912

    2023 doi

  42. [50]

    R., Jaskot , A

    Flury , S. R., Jaskot , A. E., Ferguson , H. C., et al. 2022, , 930, 126, 10.3847/1538-4357/ac61e4

    2022 doi

  43. [51]

    Gallazzi , A., Charlot , S., Brinchmann , J., White , S. D. M., & Tremonti , C. A. 2005, , 362, 41, 10.1111/j.1365-2966.2005.09321.x

    2005

  44. [52]

    Garrett, J. D. 2021, garrettj403/SciencePlots , 1.0.9, Zenodo, 10.5281/zenodo.4106649

    2021 doi

  45. [53]

    C., Fong , W.-f., Kilpatrick , C

    Gordon , A. C., Fong , W.-f., Kilpatrick , C. D., et al. 2023, , 954, 80, 10.3847/1538-4357/ace5aa

    2023 doi

  46. [54]

    2002, , 568, 820, 10.1086/338966

    Granot , J., & Sari , R. 2002, , 568, 820, 10.1086/338966

    2002 doi

  47. [55]

    E., Strader , J., & Ho , L

    Greene , J. E., Strader , J., & Ho , L. C. 2020, , 58, 257, 10.1146/annurev-astro-032620-021835

    2020 doi

  48. [56]

    J., Evans , D

    Hardcastle , M. J., Evans , D. A., & Croston , J. H. 2007, MNRAS, 376, L58, 10.1111/j.1745-3933.2007.00287.x

    2007

  49. [57]

    K., Dhillon , V

    Hardy , L. K., Dhillon , V. S., Spitler , L. G., et al. 2017, , 472, 2800, 10.1093/mnras/stx2153

    2017 doi

  50. [58]

    R., Millman , K

    Harris , C. R., Millman , K. J., van der Walt , S. J., et al. 2020, , 585, 357, 10.1038/s41586-020-2649-2

    2020 doi

  51. [59]

    Heckman , T. M. 1980, A&A, 87, 152

    1980

  52. [60]

    Hessels , J. W. T., Michilli , D., Seyler , Z., & et al. 2019, ApJ, 876, L23, 10.3847/2041-8213/ab1976

    2019 doi

  53. [61]

    M., Bhardwaj , M., Gordon , A

    Hewitt , D. M., Bhardwaj , M., Gordon , A. C., et al. 2024 a , , 977, L4, 10.3847/2041-8213/ad8ce1

    2024 doi

  54. [62]

    M., Bhandari , S., Marcote , B., et al

    Hewitt , D. M., Bhandari , S., Marcote , B., et al. 2024 b , , 529, 1814, 10.1093/mnras/stae632

    2024 doi

  55. [63]

    H., Michilli , D., Spitler , L

    Hilmarsson , G. H., Michilli , D., Spitler , L. G., et al. 2021, , 908, L10, 10.3847/2041-8213/abdec0

    2021 doi

  56. [64]

    Ho , L. C. 2002, , 564, 120, 10.1086/324399

    2002 doi

  57. [65]

    C., Filippenko , A

    Ho , L. C., Filippenko , A. V., & Sargent , W. L. W. 2003, , 583, 159, 10.1086/345354

    2003 doi

  58. [66]

    Hunter , J. D. 2007, Computing in Science and Engineering, 9, 90, 10.1109/MCSE.2007.55

    2007 doi

  59. [67]

    M., & Mahmud, I

    Hussain, M. M., & Mahmud, I. 2019, Journal of Open Source Software, 4, 1556, 10.21105/joss.01556

    2019 doi

  60. [68]

    L., Drout , M

    Ibik , A. L., Drout , M. R., Gaensler , B. M., et al. 2024, , 961, 99, 10.3847/1538-4357/ad0893

    2024 doi

  61. [69]

    2017, Bd-J/Prospector: Initial Release , v0.1, Zenodo, Zenodo, 10.5281/zenodo.1116491

    Johnson , B., & Leja , J. 2017, Bd-J/Prospector: Initial Release , v0.1, Zenodo, Zenodo, 10.5281/zenodo.1116491

    2017 doi

  62. [70]

    D., Leja , J., Conroy , C., & Speagle , J

    Johnson , B. D., Leja , J., Conroy , C., & Speagle , J. S. 2021, , 254, 22, 10.3847/1538-4365/abef67

    2021 doi

  63. [71]

    D., Leja , J

    Johnson , B. D., Leja , J. L., Conroy , C., & Speagle , J. S. 2019, Prospector: Stellar population inference from spectra and SEDs , Astrophysics Source Code Library. 1905.025

    2019

  64. [72]

    2011, , 412, 2641, 10.1111/j.1365-2966.2010.18105.x

    Jones , S., McHardy , I., Moss , D., et al. 2011, , 412, 2641, 10.1111/j.1365-2966.2010.18105.x

    2011

  65. [73]

    2019, , 882, L18, 10.3847/2041-8213/ab2c00

    Josephy , A., Chawla , P., Fonseca , E., et al. 2019, , 882, L18, 10.3847/2041-8213/ab2c00

    2019 doi

  66. [74]

    Kale , R., & Ishwara-Chandra , C. H. 2021, Experimental Astronomy, 51, 95, 10.1007/s10686-020-09677-6

    2021 doi

  67. [75]

    2017, , 839, L3, 10.3847/2041-8213/aa68e1

    Kashiyama , K., & Murase , K. 2017, , 839, L3, 10.3847/2041-8213/aa68e1

    2017 doi

  68. [76]

    2022, , 602, 585, 10.1038/s41586-021-04354-w

    Kirsten , F., Marcote , B., Nimmo , K., et al. 2022, , 602, 585, 10.1038/s41586-021-04354-w

    2022 doi

  69. [77]

    2013, , 775, L16, 10.1088/2041-8205/775/1/L16

    Kriek , M., & Conroy , C. 2013, , 775, L16, 10.1088/2041-8205/775/1/L16

    2013 doi

  70. [78]

    2017, , 468, 2726, 10.1093/mnras/stx665

    Kumar , P., Lu , W., & Bhattacharya , M. 2017, , 468, 2726, 10.1093/mnras/stx665

    2017 doi

  71. [79]

    E., Andersen , B

    Lanman , A. E., Andersen , B. C., Chawla , P., et al. 2022, , 927, 59, 10.3847/1538-4357/ac4bc7

    2022 doi

  72. [80]

    D., Conroy , C., van Dokkum , P

    Leja , J., Johnson , B. D., Conroy , C., van Dokkum , P. G., & Byler , N. 2017, , 837, 170, 10.3847/1538-4357/aa5ffe

    2017 doi

  73. [81]

    2020, , 896, 71, 10.3847/1538-4357/ab8db8

    Li , Q.-C., Yang , Y.-P., & Dai , Z.-G. 2020, , 896, 71, 10.3847/1538-4357/ab8db8

    2020 doi

  74. [82]

    2025, arXiv e-prints, arXiv:2506.01238, 10.48550/arXiv.2506.01238

    Liu , W., Bhardwaj , M., & Margalit , B. 2025, arXiv e-prints, arXiv:2506.01238, 10.48550/arXiv.2506.01238

    2025 doi arXiv

  75. [83]

    R., Bailes , M., McLaughlin , M

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

    2007 doi

  76. [84]

    2014, , 442, L9, 10.1093/mnrasl/slu046

    Lyubarsky , Y. 2014, , 442, L9, 10.1093/mnrasl/slu046

    2014 doi

  77. [85]

    V., & Giannios , D

    Lyutikov , M., Barkov , M. V., & Giannios , D. 2020, , 893, L39, 10.3847/2041-8213/ab87a4

    2020 doi

  78. [86]

    A., Ansoldi , S., et al

    MAGIC Collaboration , Acciari , V. A., Ansoldi , S., et al. 2018, , 481, 2479, 10.1093/mnras/sty2422

    2018 doi

  79. [87]

    S., et al

    Marcote , B., Nimmo , K., Salafia , O. S., et al. 2019, , 876, L14, 10.3847/2041-8213/ab1aad

    2019 doi

  80. [88]

    Marcote , B., Paragi , Z., Hessels , J. W. T., et al. 2017, , 834, L8, 10.3847/2041-8213/834/2/L8

    2017 doi

  81. [89]

    Marcote , B., Nimmo , K., Hessels , J. W. T., et al. 2020, , 577, 190, 10.1038/s41586-019-1866-z

    2020 doi

  82. [90]

    Margalit , B., Berger , E., & Metzger , B. D. 2019, , 886, 110, 10.3847/1538-4357/ab4c31

    2019 doi

  83. [91]

    Margalit , B., & Metzger , B. D. 2018, , 868, L4, 10.3847/2041-8213/aaedad

    2018 doi

  84. [92]

    D., Berger , E., et al

    Margalit , B., Metzger , B. D., Berger , E., et al. 2018, , 481, 2407, 10.1093/mnras/sty2417

    2018 doi

  85. [93]

    2022, The Astronomer's Telegram, 15679, 1

    McKinven , R., & CHIME/FRB Collaboration . 2022, The Astronomer's Telegram, 15679, 1

    2022

  86. [94]

    P., Waters , B., Schiebel , D., Young , W., & Golap , K

    McMullin , J. P., Waters , B., Schiebel , D., Young , W., & Golap , K. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw , F. Hill , & D. J. Bell , 127

    2007

  87. [95]

    D., Berger , E., & Margalit , B

    Metzger , B. D., Berger , E., & Margalit , B. 2017, , 841, 14, 10.3847/1538-4357/aa633d

    2017 doi

  88. [96]

    2023, , 950, 134, 10.3847/1538-4357/accf89

    Michilli , D., Bhardwaj , M., Brar , C., et al. 2023, , 950, 134, 10.3847/1538-4357/accf89

    2023 doi

  89. [97]

    E., Latimer , L

    Molina , M., Reines , A. E., Latimer , L. J., Baldassare , V., & Salehirad , S. 2021, , 922, 155, 10.3847/1538-4357/ac1ffa

    2021 doi

  90. [98]

    2020, , 498, 3863, 10.1093/mnras/staa2637

    Mondal , S., Bera , A., Chandra , P., & Das , B. 2020, , 498, 3863, 10.1093/mnras/staa2637

    2020 doi

  91. [99]

    V., Zhang , S., et al

    Mori , K., Gotthelf , E. V., Zhang , S., et al. 2013, , 770, L23, 10.1088/2041-8205/770/2/L23

    2013 doi

  92. [100]

    2016, , 461, 1498, 10.1093/mnras/stw1328

    Murase , K., Kashiyama , K., & M \'e sz \'a ros , P. 2016, , 461, 1498, 10.1093/mnras/stw1328

    2016 doi

  93. [101]

    M., Falcke , H., Wilson , A

    Nagar , N. M., Falcke , H., Wilson , A. S., & Ho , L. C. 2000, , 542, 186, 10.1086/309524

    2000 doi

  94. [102]

    Narayan , R., & McClintock , J. E. 1998, New Astronomy Reviews, 42, 1, 10.1016/S1387-6473(98)00002-X

    1998 doi

  95. [103]

    2021, Universe, 7, 76, 10.3390/universe7030076

    Nicastro , L., Guidorzi , C., Palazzi , E., et al. 2021, Universe, 7, 76, 10.3390/universe7030076

    2021 doi

  96. [104]

    M., Hessels , J

    Nimmo , K., Hewitt , D. M., Hessels , J. W. T., et al. 2022, , 927, L3, 10.3847/2041-8213/ac540f

    2022 doi

  97. [105]

    H., Aggarwal , K., Li , D., et al

    Niu , C. H., Aggarwal , K., Li , D., et al. 2022, , 606, 873, 10.1038/s41586-022-04755-5

    2022 doi

  98. [106]

    2018, , 475, 5109, 10.1093/mnras/sty004

    Oppermann , N., Yu , H.-R., & Pen , U.-L. 2018, , 475, 5109, 10.1093/mnras/sty004

    2018 doi

  99. [107]

    A., & Butler , B

    Perley , R. A., & Butler , B. J. 2017, , 230, 7, 10.3847/1538-4365/aa6df9

    2017 doi

  100. [108]

    Petroff , E., Hessels , J. W. T., & Lorimer , D. R. 2022, , 30, 2, 10.1007/s00159-022-00139-w

    2022 doi

  101. [109]

    2022, , 511, 6033, 10.1093/mnras/stac500

    Plavin , A., Paragi , Z., Marcote , B., et al. 2022, , 511, 6033, 10.1093/mnras/stac500

    2022 doi

  102. [110]

    M., Mickaliger , M

    Rajwade , K. M., Mickaliger , M. B., Stappers , B. W., et al. 2020, , 495, 3551, 10.1093/mnras/staa1237

    2020 doi

  103. [111]

    2023, , 949, L3, 10.3847/2041-8213/acc4b6

    Ravi , V., Catha , M., Chen , G., et al. 2023, , 949, L3, 10.3847/2041-8213/acc4b6

    2023 doi

  104. [112]

    Reines , A. E. 2022, Nature Astronomy, 6, 26, 10.1038/s41550-021-01556-0

    2022 doi

  105. [113]

    E., Condon , J

    Reines , A. E., Condon , J. J., Darling , J., & Greene , J. E. 2020, , 888, 36, 10.3847/1538-4357/ab4999

    2020 doi

  106. [114]

    Resmi , L., Vink , J., & Ishwara-Chandra , C. H. 2021, , 655, A102, 10.1051/0004-6361/202039771

    2021 doi

  107. [115]

    W., et al

    Rhodes , L., Caleb , M., Stappers , B. W., et al. 2023, , 525, 3626, 10.1093/mnras/stad2438

    2023 doi

  108. [116]

    Rickett , B. J. 1990, , 28, 561, 10.1146/annurev.aa.28.090190.003021

    1990

  109. [117]

    K., Tremou , E., Stewart , A

    Sarbadhicary , S. K., Tremou , E., Stewart , A. J., et al. 2021, , 923, 31, 10.3847/1538-4357/ac2239

    2021 doi

  110. [118]

    F., & Finkbeiner , D

    Schlafly , E. F., & Finkbeiner , D. P. 2011, , 737, 103, 10.1088/0004-637X/737/2/103

    2011 doi

  111. [119]

    Scholz , P., Bogdanov , S., Hessels , J. W. T., et al. 2017, , 846, 80, 10.3847/1538-4357/aa8456

    2017 doi

  112. [120]

    Sen, P. K. 1968, Journal of the American Statistical Association, 63, 1379, 10.1080/01621459.1968.10480934

    1968

  113. [121]

    2025, , 979, L21, 10.3847/2041-8213/ad9ddc

    Shah , V., Shin , K., Leung , C., et al. 2025, , 979, L21, 10.3847/2041-8213/ad9ddc

    2025 doi

  114. [122]

    2024, , 635, 61, 10.1038/s41586-024-08074-9

    Sharma , K., Ravi , V., Connor , L., et al. 2024, , 635, 61, 10.1038/s41586-024-08074-9

    2024 doi

  115. [123]

    2025, arXiv e-prints, arXiv:2505.13297, 10.48550/arXiv.2505.13297

    Shin , K., Curtin , A., Fine , M., et al. 2025, arXiv e-prints, arXiv:2505.13297, 10.48550/arXiv.2505.13297

    2025 doi arXiv

  116. [124]

    P., Nimmo , K., Hessels , J

    Snelders , M. P., Nimmo , K., Hessels , J. W. T., et al. 2023, Nature Astronomy, 7, 1486, 10.1038/s41550-023-02101-x

    2023 doi

  117. [125]

    Speagle , J. S. 2020, , 493, 3132, 10.1093/mnras/staa278

    2020 doi

  118. [126]

    G., Scholz , P., Hessels , J

    Spitler , L. G., Scholz , P., Hessels , J. W. T., et al. 2016, , 531, 202, 10.1038/nature17168

    2016 doi

  119. [127]

    Sridhar , N., & Metzger , B. D. 2022, , 937, 5, 10.3847/1538-4357/ac8a4a

    2022 doi

  120. [128]

    D., Beniamini , P., et al

    Sridhar , N., Metzger , B. D., Beniamini , P., et al. 2021, , 917, 13, 10.3847/1538-4357/ac0140

    2021 doi

  121. [129]

    A., Kriek , M., Price , S

    Suess , K. A., Kriek , M., Price , S. H., & Barro , G. 2021, , 915, 87, 10.3847/1538-4357/abf1e4

    2021 doi

  122. [130]

    A., Leja , J., Johnson , B

    Suess , K. A., Leja , J., Johnson , B. D., et al. 2022, , 935, 146, 10.3847/1538-4357/ac82b0

    2022 doi

  123. [131]

    P., Bassa , C

    Tendulkar , S. P., Bassa , C. G., Cordes , J. M., et al. 2017, , 834, L7, 10.3847/2041-8213/834/2/L7

    2017 doi

  124. [132]

    Terashima , Y., & Wilson , A. S. 2003, , 583, 145, 10.1086/345339

    2003 doi

  125. [133]

    1950, Proceedings of the Royal Netherlands Academy of Sciences, Series A, 53, 386

    Theil, H. 1950, Proceedings of the Royal Netherlands Academy of Sciences, Series A, 53, 386

    1950

  126. [134]

    Ulvestad , J. S. 2009, , 138, 1529, 10.1088/0004-6256/138/5/1529

    2009 doi

  127. [135]

    E., Batejat , F., et al

    Varenius , E., Conway , J. E., Batejat , F., et al. 2019, , 623, A173, 10.1051/0004-6361/201730631

    2019 doi

  128. [136]

    L., Romero , G

    Vieyro , F. L., Romero , G. E., Bosch-Ramon , V., Marcote , B., & del Valle , M. V. 2017, , 602, A64, 10.1051/0004-6361/201730556

    2017 doi

  129. [137]

    E., et al

    Virtanen , P., Gommers , R., Oliphant , T. E., et al. 2020, Nature Methods, 17, 261, 10.1038/s41592-019-0686-2

    2020 doi

  130. [138]

    Walker , M. A. 1998, , 294, 307, 10.1046/j.1365-8711.1998.01238.x10.1111/j.1365-8711.1998.01238.x

    1998

  131. [139]

    2020, , 892, 135, 10.3847/1538-4357/ab7dbf

    Wang , J.-S., & Lai , D. 2020, , 892, 135, 10.3847/1538-4357/ab7dbf

    2020 doi

  132. [140]

    C., Zhong , Y., & Luo , B

    Wang , Y., Wang , T., Ho , L. C., Zhong , Y., & Luo , B. 2024, arXiv e-prints, arXiv:2402.17991, 10.48550/arXiv.2402.17991

    2024 doi arXiv

  133. [141]

    W., Panagia , N., Sramek , R

    Weiler , K. W., Panagia , N., Sramek , R. A., et al. 1989, , 336, 421, 10.1086/167021

    1989 doi

  134. [142]

    2023, Universe, 9, 330, 10.3390/universe9070330

    Xu , J., Feng , Y., Li , D., et al. 2023, Universe, 9, 330, 10.3390/universe9070330

    2023 doi

  135. [143]

    Y., Feng , Y., Tsai , C.-W., et al

    Yang , A. Y., Feng , Y., Tsai , C.-W., et al. 2024, , 976, 165, 10.3847/1538-4357/ad7d02

    2024 doi

  136. [144]

    2019, , 885, 149, 10.3847/1538-4357/ab48dd

    Yang , Y.-H., & Dai , Z.-G. 2019, , 885, 149, 10.3847/1538-4357/ab48dd

    2019 doi

  137. [145]

    2017, , 836, L32, 10.3847/2041-8213/aa5ded

    Zhang , B. 2017, , 836, L32, 10.3847/2041-8213/aa5ded

    2017 doi

  138. [146]

    2024, Annual Review of Nuclear and Particle Science, 74, 89, 10.1146/annurev-nucl-102020-124444

    ---. 2024, Annual Review of Nuclear and Particle Science, 74, 89, 10.1146/annurev-nucl-102020-124444

    2024 doi

  139. [147]

    2025, The Astronomer's Telegram, 17156, 1

    Zhang , J., Wang , P., Zhang , Y., et al. 2025, The Astronomer's Telegram, 17156, 1

    2025

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.