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Fast Luminous Extragalactic Transients in the VLA Sky Survey: Implications for the rates of Accretion-Induced Collapse Events, Fast Blue Optical Transients and Gamma Ray Burst Afterglows

T0 review · 4 major / 7 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read The paper finds six luminous radio transients that appear in only the middle of three VLASS epochs, classifies them through host galaxies and radio energetics, and converts the sample into upper limits on the volumetric rates of…

desk verdict Genuinely useful VLASS fast-transient sample and host-galaxy work, but the headline rate limits rest on an unstable luminosity-function extrapolation and need reworking before they can be trusted. read the letter →

arxiv 2506.04522 v1 pith:AK72VZAO submitted 2025-06-05 astro-ph.HE

Kritti Sharma , Vikram Ravi , Dillon Z. Dong , Gregg Hallinan , Casey Law , Delina Levine , Jean J. Somalwar , Jessie Miller
show 2 more authors
Nikita Kosogorov Steven T. Myers
This is my paper
classification astro-ph.HE
keywords radiotransientsVLASSaccretion-inducedcollapsefastblueopticalgamma-rayburstsvolumetricratespulsarwindnebulaesynchrotronemission
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper argues that a blind radio survey can measure how rare fast, luminous stellar explosions are, even when no single event can be firmly identified. Using the three epochs of the VLA Sky Survey, the authors find six transients in the nearby universe that are visible in the middle epoch but absent from the first and third, and they classify them probabilistically using host-galaxy stellar populations, host-normalized offsets, and synchrotron energetics. From that sample they set upper limits: accretion-induced collapse of white dwarfs occurs in at most roughly 1.1% (dense circumstellar medium) or 0.2% (pulsar wind nebula) of the local Type Ia supernova rate, radio-bright LFBOTs in at most 0.02% of the core-collapse supernova rate, and beaming-corrected long and short gamma-ray burst rates below about 11 and 81 $Gpc^{-3}$ $yr^{-1}$. The payoff is that radio surveys can constrain transient populations that are faint, dusty, or off-axis and thus missed by optical and high-energy searches.

What carries the argument

The search design is the key instrument: a transient must appear in VLASS epoch 2.1 but be absent in both epoch 1.1 and epoch 3.1, selecting events with characteristic timescales of about three years or less. The rate analysis converts each detection into a volumetric rate through a power-law luminosity function dN/dL proportional to L^$\alpha$ with $\alpha$ about -1.32, an effective sky fraction f_eff of about 0.41, a maximum detectable luminosity distance per source, and an assumed visibility timescale tau per transient class. The classification machinery is a probabilistic host comparison: chance-coincidence probabilities from archival imaging, host stellar masses, star formation rates, and host-normalized offsets are compared with the distributions of Type Ia supernovae, core-collapse supernovae, long and short GRBs, LFBOTs, and ULX sources, supplemented by shock energetics under the Chevalier/Ho synchrotron model and the Piro and Kulkarni pulsar wind nebula model.

What would settle it

Observe one securely classified accretion-induced-collapse event, such as a millisecond-magnetar pulsar wind nebula, within the VLASS search volume at z below about 0.3 and above the survey's luminosity threshold: that single event would already exceed the claimed 0.2%-of-Type-Ia ceiling. Alternatively, directly measure any class's true visibility time from repeated radio monitoring and rescale the quoted limits by the ratio of measured to assumed times.

Watch

Extended reading notes

Core claim

Searching the first halves of the three VLASS epochs for sources detected at >7 $\sigma$ in epoch 2.1 but undetected at 3 $\sigma$ in epochs 1.1 and 3.1, with host galaxies at z<=0.3, yields six luminous radio transients, one of which is the previously known SN 2019xhb. The chance-coincidence probability of host association is below 0.001 for all six. Using a fitted luminosity function dN/dL proportional to $L^{-1}$.32 and class-specific visibility timescales, the paper derives upper limits: AIC events with dense CSM interaction at no more than 1.10% of the Type Ia supernova rate, AIC events producing PWNe at no more than 0.20%, radio-bright AT2018cow-like LFBOTs at no more than 0.02% of the core-collapse supernova rate, and beaming-corrected local rates for long and short GRBs of 11.46 and 80.88 $Gpc^{-3}$ $yr^{-1}$, respectively. The central claim is that none of these exotic classes is common enough to have produced more than a handful of the detected events, and the survey's non-detections therefore sharpen the rate ceilings.

Load-bearing premise

All quoted rate ceilings assume each transient class stays radio-bright for a specific visibility time (6 months for AIC-PWN, 2 years for AIC-CSM, 1.5 years for LFBOTs, 10 months for GRBs) and that the beaming corrections from afterglow simulations are correct; if those assumed times or viewing angles are wrong, the ceilings move by the same factor.

Editorial extensions

If this is right

  • Accretion-induced collapse of white dwarfs must be rare: at most about 1.1% of the Type Ia supernova rate for dense-CSM events and about 0.2% for pulsar-wind-nebula events, matching theoretical expectations below 1%.
  • Radio-bright AT2018cow-like LFBOTs occur in under 0.02% of core-collapse supernovae, so either optically selected LFBOTs are usually radio-faint or LFBOTs are rarer than earlier optical estimates suggested.
  • Beaming-corrected local rates for long and short GRBs sit below about 11.5 and 81 Gpc^-3 yr^-1, with the short-GRB ceiling consistent with gravitational-wave constraints.
  • The VLASS search geometry is sensitive to off-axis GRBs, with median detectable viewing angles near 0.4 and 0.3 radians, so the non-detections constrain jet opening angles and emission geometry.
  • Host-galaxy properties and offsets are decisive for radio-only transients: they allow provisional classification and rate estimation even when no multi-wavelength counterpart is detected.

Reading between the lines

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

  • If the assumed visibility timescales are ever replaced with measured lightcurve durations, the same search becomes a direct rate measurement rather than an upper limit; a factor-of-two error in any assumed tau would shift every quoted rate by that same factor.
  • The paper's reported absence of X-ray and gamma-ray counterparts for the unclassified transients hints that many fast luminous radio events may be off-axis or heavily absorbed; a future campaign that catches one in the act could distinguish beamed from isotropic scenarios.
  • A deeper radio survey with similar cadence should recover a clean sample of these events, and comparing their host-offset distribution with Type Ia supernovae would test whether the AIC candidates truly trace Type Ia environments.
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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. The paper presents a systematic search for fast (≲3 yr) luminous radio transients in the first half of three VLASS epochs, requiring a >7σ detection in E2.1 and non-detections in E1.1 and E3.1, restricted to z≤0.3. Six sources pass the selection; for each, the authors obtain optical host spectroscopy, measure host stellar-population properties, compute host-association probabilities (P_cc<0.001), and fit radio synchrotron models. They then use probabilistic host-galaxy and energetics comparisons to classify the sources as possible AIC events with dense CSM or PWN emission, LFBOTs, and long/short GRB afterglows, and derive volumetric rate upper limits for each class using a power-law luminosity function, assumed visibility timescales from unpublished lightcurve simulations, and beaming corrections from afterglow simulations. The headline constraints are that AIC rates are ≲1.10% and ≲0.20% of the Type Ia SN rate, radio-bright LFBOTs are ≲0.02% of the CC SN rate, and beaming-corrected long- and short-GRB rates are ≲11.46 and ≲80.88 Gpc^-3 yr^-1.

Significance. If the rate constraints are robust, this is a valuable first radio-selected census of fast extragalactic transients: it places the first direct limits on the rates of AIC events with PWN or dense-CSM radio emission and on radio-bright LFBOTs, and it constrains off-axis GRB rates from an unbiased VLASS search rather than from targeted follow-up. The paper's strengths include a clean search definition, strong host associations, real Keck/LRIS spectroscopy for five hosts, careful stellar-population modeling with Prospector, and an explicit treatment of false-alarm statistics. However, the central rate claims are conditional on several layers of model input: a luminosity-function slope fit to 1–5 sources and extrapolated to luminosities below the observed range, visibility timescales taken from simulations reported only in 'Sharma et al. (in prep)', beaming fractions from the same simulation suite, and probabilistic classifications whose overlap is not fully propagated. The discovery sample and host-galaxy analysis are likely to stand, but the rate limits need substantial revision or reframing before they can be taken as the paper's primary quantitative result.

major comments (4)
  1. [§2.4 and §5] The quoted 'upper limits' are not Poisson counting limits: they are integrals of a fitted power-law luminosity function dN/dL ∝ L^α, extrapolated down to L_min ≈ 5×10^27 erg s^-1 Hz^-1. The combined fit gives α = −1.32^{+0.25}_{−0.28}, and the class-specific fits used in §5.1 and §5.4 are even less constrained (e.g., α = −1.57^{+1.12}_{−1.10} for AIC/PWN, whose 68% range extends above −1). For α > −1, the integral ∫_{L_min}^∞ L^α dL diverges, so the finite reported bounds require an upper truncation or a prior that is not described. Because the integrated rate is extremely sensitive to α and to L_min, the headline fractions (1.10%, 0.20%, 0.02%) are model-dependent extrapolations rather than guaranteed observational upper limits. Please report the exact integration limits and the class-specific fits for every rate, and provide a sensitivity test to L_min and to the presence of a low-luminosity break.
  2. [§2.1, §2.4, and §5] Every class-specific rate limit scales linearly with an assumed visibility timescale τ (6 months for AIC/PWN, 2 yr for AIC/CSM, 1.5 yr for LFBOTs, 10 months for GRBs), and the GRB beaming corrections use median detectable viewing angles of 0.41 and 0.34 rad from the same simulation suite. These inputs are summarized only in §2.1 and are attributed to 'Sharma et al. (in prep)', with no simulation outputs, no distribution of τ, and no sensitivity test. A factor-of-two error in τ or in the beaming fraction changes every quoted limit by the same factor. Please either include the simulation details and the implied τ distributions in this paper, or present the rates as explicitly conditional on these unpublished inputs.
  3. [§5.1–§5.4] The candidate membership underlying each rate is not consistently defined, and the same host-galaxy comparisons are used both to classify sources and to set the rates. §5.1 identifies three AIC/PWN candidates and fits α to those sources, whereas §5.4 and the conclusion refer to 'four potential LFBOT candidates' even though the reported probabilities are p<0.001 for three of the five transients and only p=0.024 and p=0.041 for the other two; the text never states which sources enter the LFBOT luminosity-function fit. The AIC-CSM limit in §5.1 is instead derived after excluding all sources, using an assumed maximum luminosity of 10^28 erg s^-1 Hz^-1, rather than the §2.4 procedure. For each rate, please specify exactly which sources are included, how the probability thresholds were chosen, and whether the quoted bound is a frequentist upper limit, a Bayesian posterior interval, or a posterior predictive interval.
  4. [Abstract and §5] The notation '≲ 1.10^{+2.60}_{−0.90}%' is internally ambiguous: a genuine upper limit is a single number with an associated confidence level, while the asymmetric errors suggest a posterior distribution of the inferred rate. The same issue affects all five headline constraints. Please state the confidence level of each upper limit explicitly and separate the posterior median/credible interval from the upper bound, so that a reader can tell whether the quoted values are 95% limits or best-fit rates with error bars.
minor comments (7)
  1. [Abstract vs. §2.2 and §6] The abstract says the search reports 'five such transients', while §2.2 and §6 report six sources in the sample; please clarify whether the abstract excludes the known SN 2019xhb and make the count consistent throughout.
  2. [§2.4] The text says the expected rate 'in a differential luminosity bindLatL' is approximated by the displayed expression, but the expression appears to be a volume per transient multiplied by t_span/τ, not a differential luminosity-function density; please define the estimator precisely and show how the power-law luminosity function is combined with it.
  3. [§5.1] The AIC-CSM rate is quoted as '339.211^{+780.02}_{−280.6} Gpc^-3 yr^-1', which carries excessive significant figures; please round to a physically meaningful precision.
  4. [§5.2] The text says the long-GRB beaming correction is f_b ≈ 10, but 1/(1−cos 0.41 rad) ≈ 12, and the ratio of the corrected to uncorrected long-GRB rate is 11.46/0.95 ≈ 12; please make the stated correction factor and the rates consistent.
  5. [§5.1, §5.2, and §5.3] The statement that a probability p<0.001 rules out membership 'with more than 6σ confidence' is not correct: p<0.001 corresponds to roughly 3.3σ, and 6σ would require p<2×10^-9; please quote the actual probabilities or use a correct significance conversion.
  6. [Figure 2 and §2.4] The red data points in Figure 2 are described as observed number densities, but the text does not state how the 1–5 sources are binned in luminosity or how the plotted error bars combine Poisson and measurement uncertainties; please add this information to the caption or text.
  7. [§2.2 and §2.1] The detection pipeline is attributed to 'Dong et al. (in prep)' and the lightcurve simulations to 'Sharma et al. (in prep)'; if these works are not yet public, please state their availability or include enough detail for the search and rate inputs to be reproduced.

Circularity Check

2 steps flagged · score 5.0 of 10

The volumetric-rate upper limits reduce to a luminosity-function fit performed on the same sample, and the beaming and visibility corrections are taken from an unpublished same-author simulation paper.

  1. fitted input called prediction [§2.4 (rate equation) and §5.4 (LFBOT rate)]
    "we calculate the upper limit on the rate of AT2018cow-like events with luminosities ≳2×10^28 erg s−1 Hz−1 as R_FBOTs ≲59.92^{+972.18}_{−34.14} (τ/1.5 yr)−1 Gpc−3 yr−1, where the constrained power-law index of the luminosity function is α=−1.29^{+0.38}_{−0.43}."

    The rate is obtained by integrating the power-law luminosity function whose index α and normalization were fitted to the same candidate detections that define the rate. The resulting 'upper limit' is therefore the best-fit integral of the input sample under the assumed functional form, not an independent Poisson bound. The same construction is used for the all-source rate in §2.4 (α=−1.32 fit to the six detections) and for the AIC/PWN limit in §5.1 (α=−1.57 fit to three candidates). The quoted uncertainty is the fit uncertainty propagated through the same data, so the limit is forced by the fit rather than by an external benchmark.

  2. self citation load bearing [§2.1 and §5.2 (beaming correction for long GRBs)]
    "The details of the lightcurve simulations will be discussed in Sharma et al. (in prep). Here we summarize the key insights from that analysis. ... For VLASS, the median observing angle is ⟨θ_obs⟩=0.41 radians (see §2.1), thus implying a correction factor of f_b≈10."

    The headline beaming-corrected GRB rates are obtained by multiplying the observed rate by f_b≈10, where f_b is set by the median detectable viewing angle from afterglow simulations cited only as 'Sharma et al. (in prep)'—an unpublished paper by the same authors. No simulation output or sensitivity test is given, so the central rate constraint rests on a self-citation whose content is not independently verifiable. The visibility timescales τ that linearly rescale every rate limit are likewise drawn from those simulations, making the quoted limits depend on the authors' own modeling at each step.

full rationale

The discovery of the six transients and the direct observed rates are genuine and could be checked against the VLASS data. However, the paper's central quantitative claims—the volumetric-rate upper limits—are not independent of the model inputs. The luminosity-function slope α is fitted to the same sample whose rate is then computed by integrating that function, so the 'upper limits' reduce to the fitted model's own integral rather than to Poisson counting statistics. In addition, the beaming corrections and visibility timescales that enter every rate limit are taken from 'Sharma et al. (in prep)', a same-author unpublished work with no provided simulation output; this is load-bearing self-citation. The 68% ranges for α even extend above −1 (e.g., −1.57+1.12 = −0.45), where the integral ∫ L^α dL diverges, so the finite quoted bounds require an undocumented truncation or prior. These issues make the rate constraints model-dependent extrapolations, though the paper does compare some results to independent literature values (e.g., Pescalli 2016; LIGO/Virgo), which is why the score is 5 rather than higher.

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

The central claim rests on a small set of fitted parameters and literature-based modeling assumptions. No new particles or forces are introduced. The main burden is that visibility timescales, beaming angles, and the luminosity function shape are taken from unpublished simulations or fitted to the same five sources, so the rate limits inherit those assumptions.

free parameters (8)
  • Luminosity function power-law index alpha = -1.32 (+0.25, -0.28)
    Fit to the detected transients in Section 2.4; used to integrate the volumetric rate down to L_min.
  • Visibility timescale tau (total sample) = 1 yr
    Assumed in R = 39.68 (tau/1 yr)^-1 Gpc^-3 yr^-1 (Section 2.4).
  • Visibility timescale tau (AIC-PWN) = 6 months
    Used for R_AIC,PWNe rate; based on median expected timescale from simulations (Section 5.1).
  • Visibility timescale tau (AIC-CSM) = 2 yr
    Used for R_AIC,CSM rate; based on typical visibility period (Section 5.1).
  • Visibility timescale tau (LFBOT) = 1.5 yr
    Used for R_FBOTs rate (Section 5.4).
  • Visibility timescale tau (GRBs) = 10 months
    Used for long- and short-duration GRB rates (Sections 5.2, 5.3).
  • Median detectable viewing angle for long GRBs = 0.41 rad
    From afterglow simulations (Section 2.1); used for beaming correction f_b ~ 10 in Section 5.2.
  • Median detectable viewing angle for short GRBs = 0.34 rad
    From afterglow simulations (Section 2.1); used for beaming correction in Section 5.3.
assumptions (8)
  • domain assumption Single power-law luminosity function dN/dL proportional to L^alpha with fitted alpha, valid down to L_min.
    Assumed in Section 2.4 for rate integration; not derived from physical principles.
  • ad hoc to paper Assumed visibility timescales come from lightcurve simulations.
    The simulations are in Sharma et al. (in prep) and are not included in this paper.
  • domain assumption AIC host galaxy environments and offsets mirror those of Type Ia SNe.
    Stated in Section 5.1; used to compute AIC candidate probabilities.
  • domain assumption Optical host completeness within 10 arcsec and r < 23.5 mag at z <= 0.3.
    Used in Section 2.2 to remove 107 candidates; asserted rather than demonstrated.
  • domain assumption Synchrotron self-absorbed shock model (Chevalier 1998; Ho et al. 2019) with chosen energy partition fractions.
    Used in Section 4.1 and Appendix A to derive shock radii, energies, and velocities.
  • domain assumption Piro and Kulkarni (2013) pulsar wind nebula spin-down model.
    Used in Section 4.2 and Appendix B to link magnetar parameters to radio luminosity.
  • domain assumption GRB afterglow simulations (van Eerten et al. 2012) with observed parameter distributions.
    Used in Section 2.1 to estimate detectable observing angles and beaming corrections.
  • domain assumption Local Type Ia SN rate of about 3e4 Gpc^-3 yr^-1 and CCSN rate of about 3e5 Gpc^-3 yr^-1.
    External normalizations from Li et al. (2011) and Dahlen et al. (2012), used in Section 5.

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Cite this review

Pith. "Pith review of Fast Luminous Extragalactic Transients in the VLA Sky Survey: Implications for the rates of Accretion-Induced Collapse Events, Fast Blue Optical Transients and Gamma Ray Burst Afterglows." pith.science (2026). https://pith.science/paper/AK72VZAO

@misc{pith2026250604522,
  author       = {Pith},
  title        = {Pith review of: Fast Luminous Extragalactic Transients in the VLA Sky Survey: Implications for the rates of Accretion-Induced Collapse Events, Fast Blue Optical Transients and Gamma Ray Burst Afterglows},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AK72VZAO}},
  note         = {Machine review of arXiv:2506.04522}
}
abstract

Radio wavelengths offer a unique window into high-energy astrophysical phenomena that may be obscured or too rapidly evolving to be captured at other wavelengths. Leveraging data from the Very Large Array Sky Survey, we perform a systematic search for fast, luminous transients with characteristic timescales $\lesssim 3$ years in the nearby universe ($z \leq 0.3$). We report the discovery of five such transients, and classify them based on their synchrotron emission energetics and host galaxy properties. From this sample, we derive observational constraints on the volumetric rates of certain corresponding transient classes. We limit the rates of accretion-induced collapse of white dwarfs with dense circumstellar medium interaction (and those producing pulsar wind nebulae) at $\lesssim 1.10_{-0.90}^{+2.60}$% ($\lesssim 0.20_{-0.10}^{+5.80}$%) of the local Type Ia supernova rate, respectively, broadly consistent with theoretical predictions. For AT2018cow-like radio-bright luminous fast blue optical transients, we estimate a rare occurrence rate of $\lesssim 0.02_{-0.01}^{+0.32}$% of the local core-collapse supernova rate. We constrain the local volumetric rates of long- and short-duration gamma-ray bursts (GRBs) to be $\lesssim 11.46_{-9.48}^{+26.28}$~Gpc$^{-3}$~yr$^{-1}$ and $\lesssim 80.88_{-66.90}^{+185.87}$~Gpc$^{-3}$~yr$^{-1}$, respectively. These estimates incorporate beaming corrections, with median detectable viewing angles derived from afterglow simulations of $\sim 0.4$ and $\sim 0.3$ radians for long- and short-duration GRBs. Our findings highlight the potential of radio surveys to uncover rare, energetic transients. We emphasize the critical role of coordinated multi-wavelength follow-up in fully characterizing these enigmatic events.

Figures

Figures reproduced from arXiv: 2506.04522 by the authors.

Figure 1
Figure 1. The reference (E1.1), discovery (E2.1) and late-time (E3.1) imaging of VLASS fast luminous transients at 3 GHz in quicklook imaging. The VLASS images are centered at the transient location (blue circle) and the corresponding optical images are centered on host galaxies. The physical scales are marked on the panels for reference [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 1
Figure 1. [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Luminosity function of VLASS fast luminous ra￾dio transients. The red data points represent the observed number densities of transients as a function of luminosity, with error bars indicating the total Poisson and measure￾ment uncertainties. The plot illustrates the luminosity func￾tion fitted with a power-law model dN/dL ∝ L α . The solid orange line denotes the median fit with power-law index α = −1.32+0.25 −0.28 … view at source ↗
Figures from the paper (7 more)
Figure 3
Figure 3. Figure 3: Optical spectra of VLASS transients host galaxies. For VTJ0918+1554, the archival SDSS spectrum provides a ∆λ/λ ∼ 2000 resolution. The spectra for the other five host galaxies were obtained using the Keck-I:LRIS (see [PITH_FULL_IMAGE:figures/full_fig_p007_3.png]
Figure 4
Figure 4. Figure 4: Determining the primary ionization mechanism within the host galaxies of our VLASS transients sample using the BPT empirical optical emission-line diagnostic diagrams (Baldwin et al. 1981). We include the maximum starburst line (solid; Kewley et al. 2001), the demarcat…
Figure 5
Figure 5. Figure 5: Comparison of VLASS host galaxies with background galaxy population. We use the COSMOS￾2015 (Laigle et al. 2016; Leja et al. 2020) and 3D-HST (Skel￾ton et al. 2014) galaxy catalogs at z ≤ 0.3 to represent the field galaxy population. For reference, the center of the st…
Figure 7
Figure 7. Figure 7: Constraints on the magnetar spin down-powered PWN model (Piro & Kulkarni 2013). The dashed and dot￾ted lines show the lines of constant initial surface dipole magnetic field B0 and spin-down timescale τ0, respectively. The color-map in the background shows the expected…
Figure 6
Figure 6. Figure 6: Constraints from the dense CSM interaction￾powered synchrotron radiation model (Ho et al. 2019). The constraints for our 6 VLASS transients in velocity-energy space (top panel) and peak luminosity-timescale space (bot￾tom panel) are shown in contrast to other classes o…
Figure 8
Figure 8. Figure 8: Constraints on the black hole accretion rates re￾quired to power black hole jet models for VLASS transients. The solid lines show the predicted jet power from a radio power-jet power relation (Cavagnolo et al. 2010) and the dot￾ted lines show the predicted jet power wi…
Figure 9
Figure 9. Figure 9: Comparison of the VLASS transient’s host galaxy properties and host normalized offsets with known transient classes. Since the redshift distribution of the comparison samples is very different from our sample, we correct the host galaxy properties of Fast Radio Bursts …

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Works this paper leans on

128 extracted references · 7 canonical work pages

  1. [1]

    D., Acernese, F., et al

    Abbott, R., Abbott, T. D., Acernese, F., et al. 2023, Physical Review X, 13, 011048, doi: 10.1103/PhysRevX.13.011048

    doi:10.1103/physrevx.13.011048 2023

  2. [2]

    Abbott, T. M. C., Abdalla, F. B., Allam, S., et al. 2018, ApJS, 239, 18, doi: 10.3847/1538-4365/aae9f0

    doi:10.3847/1538-4365/aae9f0 2018

  3. [3]

    B., Axelsson, M., et al

    Ajello, M., Atwood, W. B., Axelsson, M., et al. 2021, ApJS, 256, 12, doi: 10.3847/1538-4365/ac0ceb

    work page doi:10.3847/1538-4365/ac0ceb 2021

  4. [4]

    D., Allende Prieto, C., et al

    Alam, S., Albareti, F. D., Allende Prieto, C., et al. 2015, ApJS, 219, 12, doi: 10.1088/0067-0049/219/1/12 20Sharma et al

    doi:10.1088/0067-0049/219/1/12 2015

  5. [5]

    P., et al

    Balasubramanian, A., Corsi, A., Mooley, K. P., et al. 2021, ApJL, 914, L20, doi: 10.3847/2041-8213/abfd38

    doi:10.3847/2041-8213/abfd38 2021

  6. [6]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766

    doi:10.1086/130766 1981

  7. [7]

    2021, MNRAS, 500, 1633, doi: 10.1093/mnras/staa2587

    Beck, R., Szapudi, I., Flewelling, H., et al. 2021, MNRAS, 500, 1633, doi: 10.1093/mnras/staa2587

    doi:10.1093/mnras/staa2587 2021

  8. [8]

    C., Kulkarni, S

    Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2019, PASP, 131, 018002, doi: 10.1088/1538-3873/aaecbe

    doi:10.1088/1538-3873/aaecbe 2019

Show all 128 references
  1. [9]

    Y., et al

    Bhardwaj, M., Michilli, D., Kirichenko, A. Y., et al. 2023, arXiv e-prints, arXiv:2310.10018, doi: 10.48550/arXiv.2310.10018

    2023 doi arXiv

  2. [10]

    K., Berger, E., & Fong, W.-f

    Blanchard, P. K., Berger, E., & Fong, W.-f. 2016, ApJ, 817, 144, doi: 10.3847/0004-637X/817/2/144

    2016 doi

  3. [11]

    S., Kulkarni, S

    Bloom, J. S., Kulkarni, S. R., & Djorgovski, S. G. 2002, AJ, 123, 1111, doi: 10.1086/338893

    2002 doi

  4. [12]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682, doi: 10.1086/308692

    2000 doi

  5. [13]

    2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020 —

    Cappellari, M. 2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020 —. 2022, arXiv e-prints, arXiv:2208.14974. https://arxiv.org/abs/2208.14974

    2017 arXiv

  6. [14]

    L., & Rawlings, S

    Carilli, C. L., & Rawlings, S. 2004, NewAR, 48, 979, doi: 10.1016/j.newar.2004.09.001

    2004 doi

  7. [15]

    W., McNamara, B

    Cavagnolo, K. W., McNamara, B. R., Nulsen, P. E. J., et al. 2010, ApJ, 720, 1066, doi: 10.1088/0004-637X/720/2/1066

    2010 doi

  8. [16]

    C., Magnier, E

    Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560. https://arxiv.org/abs/1612.05560

    2016 arXiv

  9. [17]

    A., Chugai, N., Milisavljevic, D., & Fransson, C

    Chandra, P., Chevalier, R. A., Chugai, N., Milisavljevic, D., & Fransson, C. 2020, ApJ, 902, 55, doi: 10.3847/1538-4357/abb460

    2020 doi

  10. [18]

    Chandra, P., & Frail, D. A. 2012, ApJ, 746, 156, doi: 10.1088/0004-637X/746/2/156

    2012 doi

  11. [19]

    Chevalier, R. A. 1977, in Astrophysics and Space Science

    1977

  12. [20]

    66, Supernovae, ed

    Library, Vol. 66, Supernovae, ed. D. N. Schramm, 53, doi: 10.1007/978-94-010-1229-4 5

    doi

  13. [21]

    Chevalier, R. A. 1998, ApJ, 499, 810, doi: 10.1086/305676

    1998 doi

  14. [22]

    A., Coppejans, D

    Chrimes, A. A., Coppejans, D. L., Jonker, P. G., et al. 2024a, A&A, 691, A329, doi: 10.1051/0004-6361/202451172

    doi

  15. [23]

    A., Jonker, P

    Chrimes, A. A., Jonker, P. G., Levan, A. J., et al. 2024b, MNRAS, 527, L47, doi: 10.1093/mnrasl/slad145

    doi

  16. [24]

    L., Margutti, R., Terreran, G., et al

    Coppejans, D. L., Margutti, R., Terreran, G., et al. 2020, ApJL, 895, L23, doi: 10.3847/2041-8213/ab8cc7

    2020 doi

  17. [25]

    A., et al

    Corbel, S., Dubus, G., Tomsick, J. A., et al. 2012, MNRAS, 421, 2947, doi: 10.1111/j.1365-2966.2012.20517.x

    2012

  18. [26]

    O., Gal-Yam, A., et al

    Corsi, A., Ofek, E. O., Gal-Yam, A., et al. 2014, ApJ, 782, 42, doi: 10.1088/0004-637X/782/1/42

    2014 doi

  19. [27]

    P., Werner, M., Akeson, R., et al

    Crill, B. P., Werner, M., Akeson, R., et al. 2020, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 11443, Space Telescopes and Instrumentation 2020: Optical, Infrared, and Millimeter Wave, ed. M. Lystrup & M. D. Perrin, 114430I, doi: 10.111...

    2020 doi

  20. [28]

    M., Wright, E

    Cutri, R. M., Wright, E. L., Conrow, T., et al. 2021, VizieR Online Data Catalog, II/328

    2021

  21. [29]

    G., et al

    Dahlen, T., Strolger, L.-G., Riess, A. G., et al. 2012, ApJ, 757, 70, doi: 10.1088/0004-637X/757/1/70 Dall’Osso, S., & Stella, L. 2022, in Astrophysics and Space Science Library, Vol. 465, Astrophysics and Space Science Library, ed. S. Bhattacharyya, A. Papitto, & D. Bhattacha...

    2012 doi

  22. [30]

    J., Lang, D., et al

    Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168, doi: 10.3847/1538-3881/ab089d

    2019 doi

  23. [31]

    Dong, D. Z. 2023, Dissertation (ph.d.), California Institute of Technology, doi: 10.7907/xwy9-tc17

    2023 doi

  24. [32]

    Z., & Hallinan, G

    Dong, D. Z., & Hallinan, G. 2023, ApJ, 948, 119, doi: 10.3847/1538-4357/acc06c

    2023 doi

  25. [33]

    Z., Hallinan, G., Nakar, E., et al

    Dong, D. Z., Hallinan, G., Nakar, E., et al. 2021, Science, 373, 1125, doi: 10.1126/science.abg6037

    2021 doi

  26. [34]

    T., & Li, A

    Draine, B. T., & Li, A. 2007, ApJ, 657, 810, doi: 10.1086/511055

    2007 doi

  27. [35]

    P., Andrews, S

    Driver, S. P., Andrews, S. K., Davies, L. J., et al. 2016, ApJ, 827, 108, doi: 10.3847/0004-637X/827/2/108

    2016 doi

  28. [36]

    Duncan, K. J. 2022, MNRAS, 512, 3662, doi: 10.1093/mnras/stac608

    2022 doi

  29. [37]

    C., & Thompson, C

    Duncan, R. C., & Thompson, C. 1992, ApJL, 392, L9, doi: 10.1086/186413

    1992 doi

  30. [38]

    2017, ApJ, 849, 162, doi: 10.3847/1538-4357/aa90b9

    Eftekhari, T., & Berger, E. 2017, ApJ, 849, 162, doi: 10.3847/1538-4357/aa90b9

    2017 doi

  31. [39]

    Alexander, K. D. 2018, ApJ, 854, 86, doi: 10.3847/1538-4357/aaa8e0

    2018 doi

  32. [40]

    2015, SSRv, 191, 77, doi: 10.1007/s11214-015-0138-y

    Ferrario, L., Melatos, A., & Zrake, J. 2015, SSRv, 191, 77, doi: 10.1007/s11214-015-0138-y

    2015 doi

  33. [41]

    Fong, W., Berger, E., Margutti, R., & Zauderer, B. A. 2015, ApJ, 815, 102, doi: 10.1088/0004-637X/815/2/102

    2015 doi

  34. [42]

    E., Dong, Y., et al

    Fong, W.-f., Nugent, A. E., Dong, Y., et al. 2022, ApJ, 940, 56, doi: 10.3847/1538-4357/ac91d010.48550/arXiv.2206. 01763

    2022 doi

  35. [43]

    E., Pignata, G., et al

    Forster, F., Bauer, F. E., Pignata, G., et al. 2019, Transient Name Server Discovery Report, 2019-2663, 1 Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al...

    2019 doi

  36. [44]

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

    2005

  37. [45]

    D., Slane, P

    Gelfand, J. D., Slane, P. O., & Zhang, W. 2009, ApJ, 703, 2051, doi: 10.1088/0004-637X/703/2/2051

    2009 doi

  38. [46]

    A., & Wiersema, K

    Wynn, G. A., & Wiersema, K. 2015, MNRAS, 448, 629, doi: 10.1093/mnras/stu2752

    2015 doi

  39. [47]

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

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

    2023 doi

  40. [48]

    Green, D. A. 2019, Journal of Astrophysics and Astronomy, 40, 36, doi: 10.1007/s12036-019-9601-6

    2019 doi

  41. [49]

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

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

    2020 doi

  42. [50]

    2019, in Bulletin of the American Astronomical Society, Vol

    Hallinan, G., Ravi, V., Weinreb, S., et al. 2019, in Bulletin of the American Astronomical Society, Vol. 51, 255, doi: 10.48550/arXiv.1907.07648

    2019 doi arXiv

  43. [51]

    2020, The Astronomer’s Telegram, 14020, 1

    Hallinan, G., Mooley, K., Dong, D., et al. 2020, The Astronomer’s Telegram, 14020, 1

    2020

  44. [52]

    Ho, A. Y. Q., Phinney, E. S., Ravi, V., et al. 2019, ApJ, 871, 73, doi: 10.3847/1538-4357/aaf473

    2019 doi

  45. [53]

    Ho, A. Y. Q., Perley, D. A., Kulkarni, S. R., et al. 2020, ApJ, 895, 49, doi: 10.3847/1538-4357/ab8bcf

    2020 doi

  46. [54]

    Ho, A. Y. Q., Perley, D. A., Yao, Y., et al. 2022, ApJ, 938, 85, doi: 10.3847/1538-4357/ac8bd0

    2022 doi

  47. [55]

    Ho, A. Y. Q., Perley, D. A., Gal-Yam, A., et al. 2023, ApJ, 949, 120, doi: 10.3847/1538-4357/acc533 Ivezi´ c,ˇZ., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111, doi: 10.3847/1538-4357/ab042c

    2023 doi

  48. [56]

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

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

    2021 doi

  49. [57]

    M., & Beloborodov, A

    Kaspi, V. M., & Beloborodov, A. M. 2017, ARA&A, 55, 261, doi: 10.1146/annurev-astro-081915-023329

    2017 doi

  50. [58]

    M., Tremonti, C., et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x

    2003

  51. [59]

    L., & Kirshner, R

    Kelly, P. L., & Kirshner, R. P. 2012, ApJ, 759, 107, doi: 10.1088/0004-637X/759/2/107

    2012 doi

  52. [60]

    Kennicutt, Robert C., J., Tamblyn, P., & Congdon, C. E. 1994, ApJ, 435, 22, doi: 10.1086/174790

    1994 doi

  53. [61]

    J., Dopita, M

    Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, ApJ, 556, 121, doi: 10.1086/321545

    2001 doi

  54. [63]

    J., et al

    Kovlakas, K., Zezas, A., Andrews, J. J., et al. 2020, MNRAS, 498, 4790, doi: 10.1093/mnras/staa2481

    2020 doi

  55. [64]

    2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    2001

  56. [65]

    A., Chandler, C

    Lacy, M., Baum, S. A., Chandler, C. J., et al. 2020, PASP, 132, 035001, doi: 10.1088/1538-3873/ab63eb

    2020 doi

  57. [66]

    J., Ilbert, O., et al

    Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24, doi: 10.3847/0067-0049/224/2/24

    2016 doi

  58. [67]

    C., et al

    Lampeitl, H., Smith, M., Nichol, R. C., et al. 2010, ApJ, 722, 566, doi: 10.1088/0004-637X/722/1/56610.48550/ arXiv.1005.4687

    2010

  59. [68]

    M., & Prakash, M

    Lattimer, J. M., & Prakash, M. 2001, ApJ, 550, 426, doi: 10.1086/319702

    2001 doi

  60. [69]

    2018, ApJL, 866, L22, doi: 10.3847/2041-8213/aae5f3

    Sironi, L. 2018, ApJL, 866, L22, doi: 10.3847/2041-8213/aae5f3

    2018 doi

  61. [70]

    S., Johnson, B

    Leja, J., Speagle, J. S., Johnson, B. D., et al. 2020, ApJ, 893, 111, doi: 10.3847/1538-4357/ab7e27

    2020 doi

  62. [71]

    S., Ting, Y.-S., et al

    Leja, J., Speagle, J. S., Ting, Y.-S., et al. 2022, ApJ, 936, 165, doi: 10.3847/1538-4357/ac887d

    2022 doi

  63. [72]

    2011, MNRAS, 412, 1473, doi: 10.1111/j.1365-2966.2011.18162.x

    Li, W., Chornock, R., Leaman, J., et al. 2011, MNRAS, 412, 1473, doi: 10.1111/j.1365-2966.2011.18162.x

    2011

  64. [73]

    D., et al

    Lien, A., Sakamoto, T., Barthelmy, S. D., et al. 2016, ApJ, 829, 7, doi: 10.3847/0004-637X/829/1/7

    2016 doi

  65. [74]

    2015, ApJ, 804, 90, doi: 10.1088/0004-637X/804/2/90

    Lunnan, R., Chornock, R., Berger, E., et al. 2015, ApJ, 804, 90, doi: 10.1088/0004-637X/804/2/90

    2015 doi

  66. [75]

    2011, ApJ, 731, 53, doi: 10.1088/0004-637X/731/1/53

    Mainzer, A., Bauer, J., Grav, T., et al. 2011, ApJ, 731, 53, doi: 10.1088/0004-637X/731/1/53

    2011 doi

  67. [76]

    N., Hobbs, G

    Manchester, R. N., Hobbs, G. B., Teoh, A., & Hobbs, M. 2005, AJ, 129, 1993, doi: 10.1086/428488

    2005 doi

  68. [77]

    G., Fong, W.-f., Simha, S., et al

    Mannings, A. G., Fong, W.-f., Simha, S., et al. 2021, ApJ, 917, 75, doi: 10.3847/1538-4357/abff56

    2021 doi

  69. [78]

    J., Laher, R

    Masci, F. J., Laher, R. R., Rusholme, B., et al. 2023, arXiv e-prints, arXiv:2305.16279, doi: 10.48550/arXiv.2305.16279 M´ esz´ aros, P., & Rees, M. J. 1997, ApJ, 476, 232, doi: 10.1086/303625

    2023 doi arXiv

  70. [79]

    D., Margalit, B., Kasen, D., & Quataert, E

    Metzger, B. D., Margalit, B., Kasen, D., & Quataert, E. 2015a, MNRAS, 454, 3311, doi: 10.1093/mnras/stv2224

    doi

  71. [80]

    D., Piro, A

    Metzger, B. D., Piro, A. L., & Quataert, E. 2009, MNRAS, 396, 1659, doi: 10.1111/j.1365-2966.2009.14909.x

    2009

  72. [81]

    D., Williams, P

    Metzger, B. D., Williams, P. K. G., & Berger, E. 2015b, ApJ, 806, 224, doi: 10.1088/0004-637X/806/2/224

    doi

  73. [82]

    Moriya, T. J. 2016, ApJL, 830, L38, doi: 10.3847/2041-8205/830/2/L38

    2016 doi

  74. [83]

    J., Bennett, C., et al

    Mosby, G., Rauscher, B. J., Bennett, C., et al. 2020, Journal of Astronomical Telescopes, Instruments, and Systems, 6, 046001, doi: 10.1117/1.JATIS.6.4.046001

    2020 doi

  75. [84]

    2022, MNRAS, 511, 3795, doi: 10.1093/mnras/stac285

    Curd, B. 2022, MNRAS, 511, 3795, doi: 10.1093/mnras/stac285

    2022 doi

  76. [85]

    2008, ApJ, 685, 160, doi: 10.1086/590483 22Sharma et al

    Elitzur, M. 2008, ApJ, 685, 160, doi: 10.1086/590483 22Sharma et al

    2008 doi

  77. [86]

    2017, ApJ, 850, 55, doi: 10.3847/1538-4357/aa9334

    Nicholl, M., Guillochon, J., & Berger, E. 2017, ApJ, 850, 55, doi: 10.3847/1538-4357/aa9334

    2017 doi

  78. [87]

    E., Fong, W.-F., Dong, Y., et al

    Nugent, A. E., Fong, W.-F., Dong, Y., et al. 2022, ApJ, 940, 57, doi: 10.3847/1538-4357/ac91d1

    2022 doi

  79. [88]

    B., Cohen, J

    Oke, J. B., Cohen, J. G., Carr, M., et al. 1995, PASP, 107, 375, doi: 10.1086/133562

    1995 doi

  80. [89]

    A., & Kaspi, V

    Olausen, S. A., & Kaspi, V. M. 2014, ApJS, 212, 6, doi: 10.1088/0067-0049/212/1/6

    2014 doi

  81. [90]

    2005, arXiv e-prints, cs/0502072

    OMullane, W., Li, N., Nieto-Santisteban, M., et al. 2005, arXiv e-prints, cs/0502072. https://arxiv.org/abs/cs/0502072

    2005 arXiv

  82. [91]

    Pacholczyk, A. G. 1970, Radio astrophysics. Nonthermal processes in galactic and extragalactic sources

    1970

  83. [92]

    Perley, D. A. 2019, PASP, 131, 084503, doi: 10.1088/1538-3873/ab215d

    2019 doi

  84. [93]

    A., Mazzali, P

    Perley, D. A., Mazzali, P. A., Yan, L., et al. 2019, MNRAS, 484, 1031, doi: 10.1093/mnras/sty3420

    2019 doi

  85. [94]

    A., Ho, A

    Perley, D. A., Ho, A. Y. Q., Yao, Y., et al. 2021, MNRAS, 508, 5138, doi: 10.1093/mnras/stab2785

    2021 doi

  86. [95]

    2016, A&A, 587, A40, doi: 10.1051/0004-6361/201526760

    Pescalli, A., Ghirlanda, G., Salvaterra, R., et al. 2016, A&A, 587, A40, doi: 10.1051/0004-6361/201526760

    2016 doi

  87. [96]

    L., & Kulkarni, S

    Piro, A. L., & Kulkarni, S. R. 2013, ApJL, 762, L17, doi: 10.1088/2041-8205/762/2/L17 Planck Collaboration, Aghanim, N., Akrami, Y., et al. 2020, A&A, 641, A6, doi: 10.1051/0004-6361/201833910

    2013 doi

  88. [97]

    2018, MNRAS, 481, 894, doi: 10.1093/mnras/sty2309

    Pursiainen, M., Childress, M., Smith, M., et al. 2018, MNRAS, 481, 894, doi: 10.1093/mnras/sty2309

    2018 doi

  89. [98]

    V., Hurley, K., & Lichti, G

    Rau, A., Kienlin, A. V., Hurley, K., & Lichti, G. G. 2005, A&A, 438, 1175, doi: 10.1051/0004-6361:20053159

    2005 doi

  90. [99]

    2010, Science, 330, 944, doi: 10.1126/science.1196088

    Rea, N., Esposito, P., Turolla, R., et al. 2010, Science, 330, 944, doi: 10.1126/science.1196088

    2010 doi

  91. [100]

    P., & Chevalier, R

    Reynolds, S. P., & Chevalier, R. A. 1984, ApJ, 278, 630, doi: 10.1086/161831

    1984 doi

  92. [101]

    T., Metzger, B

    Rowlinson, A., O’Brien, P. T., Metzger, B. D., Tanvir, N. R., & Levan, A. J. 2013, MNRAS, 430, 1061, doi: 10.1093/mnras/sts683

    2013 doi

  93. [102]

    B., & Lightman, A

    Rybicki, G. B., & Lightman, A. P. 1979, Radiative processes in astrophysics S´ anchez-Bl´ azquez, P., Peletier, R. F., Jim´ enez-Vicente, J., et al. 2006, MNRAS, 371, 703, doi: 10.1111/j.1365-2966.2006.10699.x

    1979

  94. [103]

    O., Page, M

    Schady, P., Mason, K. O., Page, M. J., et al. 2007, MNRAS, 377, 273, doi: 10.1111/j.1365-2966.2007.11592.x

    2007

  95. [104]

    2021, ApJS, 255, 29, doi: 10.3847/1538-4365/abff5e

    Schulze, S., Yaron, O., Sollerman, J., et al. 2021, ApJS, 255, 29, doi: 10.3847/1538-4365/abff5e

    2021 doi

  96. [105]

    2014, PASJ, 66, 87, doi: 10.1093/pasj/psu063

    Serino, M., Sakamoto, T., Kawai, N., et al. 2014, PASJ, 66, 87, doi: 10.1093/pasj/psu063

    2014 doi

  97. [106]

    2024, Nature, 635, 61, doi: 10.1038/s41586-024-08074-9

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

    2024 doi

  98. [107]

    W., Young, D

    Shingles, L., Smith, K. W., Young, D. R., et al. 2021, Transient Name Server AstroNote, 7, 1

    2021

  99. [108]

    E., Whitaker, K

    Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ApJS, 214, 24, doi: 10.1088/0067-0049/214/2/24

    2014 doi

  100. [109]

    F., Cutri, R

    Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163, doi: 10.1086/498708

    2006 doi

  101. [110]

    Frail, D. A. 2006a, ApJ, 651, 1005, doi: 10.1086/507571

    doi

  102. [111]

    M., Kulkarni, S

    Soderberg, A. M., Kulkarni, S. R., Berger, E., et al. 2005, ApJ, 621, 908, doi: 10.1086/427649

    2005 doi

  103. [112]

    M., Kulkarni, S

    Soderberg, A. M., Kulkarni, S. R., Nakar, E., et al. 2006b, Nature, 442, 1014, doi: 10.1038/nature05087

    doi

  104. [113]

    M., Chakraborti, S., Pignata, G., et al

    Soderberg, A. M., Chakraborti, S., Pignata, G., et al. 2010, Nature, 463, 513, doi: 10.1038/nature08714

    2010 doi

  105. [114]

    J., Ravi, V., Dong, D

    Somalwar, J. J., Ravi, V., Dong, D. Z., et al. 2023, arXiv e-prints, arXiv:2310.03791, doi: 10.48550/arXiv.2310.03791

    2023 doi arXiv

  106. [115]

    Speagle, J. S. 2020, Monthly Notices of the Royal Astronomical Society, 493, 3132–3158, doi: 10.1093/mnras/staa278

    2020 doi

  107. [116]

    M., et al

    Tacchella, S., Conroy, C., Faber, S. M., et al. 2022, ApJ, 926, 134, doi: 10.3847/1538-4357/ac449b

    2022 doi

  108. [117]

    Tachibana, Y., & Miller, A. A. 2018, PASP, 130, 128001, doi: 10.1088/1538-3873/aae3d9

    2018 doi

  109. [118]

    Taggart, K., & Perley, D. A. 2021, MNRAS, 503, 3931, doi: 10.1093/mnras/stab174

    2021 doi

  110. [119]

    D., Giannios, D., & Kelley, L

    Tchekhovskoy, A., Metzger, B. D., Giannios, D., & Kelley, L. Z. 2014, MNRAS, 437, 2744, doi: 10.1093/mnras/stt2085

    2014 doi

  111. [120]

    Teboul, O., & Metzger, B. D. 2023, ApJL, 957, L9, doi: 10.3847/2041-8213/ad0037

    2023 doi

  112. [121]

    Thompson, C., & Duncan, R. C. 1993, ApJ, 408, 194, doi: 10.1086/172580

    1993 doi

  113. [122]

    L., Denneau, L., Heinze, A

    Tonry, J. L., Denneau, L., Heinze, A. N., et al. 2018, PASP, 130, 064505, doi: 10.1088/1538-3873/aabadf

    2018 doi

  114. [123]

    A., Burns, C

    Uddin, S. A., Burns, C. R., Phillips, M. M., et al. 2020, ApJ, 901, 143, doi: 10.3847/1538-4357/abafb7 van Eerten, H., van der Horst, A., & MacFadyen, A. 2012, ApJ, 749, 44, doi: 10.1088/0004-637X/749/1/44

    2020 doi

  115. [124]

    D., Salvaterra, R., Japelj, J., et al

    Vergani, S. D., Salvaterra, R., Japelj, J., et al. 2015, A&A, 581, A102, doi: 10.1051/0004-6361/20142501310.48550/ arXiv.1409.7064

    2015

  116. [125]

    N., Mannings, A

    Woodland, M. N., Mannings, A. G., Prochaska, J. X., et al. 2023, arXiv e-prints, arXiv:2312.01578, doi: 10.48550/arXiv.2312.01578

    2023 doi arXiv

  117. [126]

    L., Eisenhardt, P

    Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868, doi: 10.1088/0004-6256/140/6/1868

    2010 doi

  118. [127]

    T., Murase, K., & Zhang, B

    Yuan, C., Winter, W., Zhang, B. T., Murase, K., & Zhang, B. 2025, ApJ, 982, 196, doi: 10.3847/1538-4357/adbbde VLASS F ast Luminous Extragalactic Transients23

    2025 doi

  119. [128]

    1998, ApJ, 497, 168, doi: 10.1086/305455

    Yungelson, L., & Livio, M. 1998, ApJ, 497, 168, doi: 10.1086/305455

    1998 doi

  120. [129]

    2017, PASP, 129, 064101, doi: 10.1088/1538-3873/aa65ba

    Zou, H., Zhou, X., Fan, X., et al. 2017, PASP, 129, 064101, doi: 10.1088/1538-3873/aa65ba

    2017 doi

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Reviewed August 7, 2026 · model on record in the stance chip above.