arXiv subjects

Thomas C. Abbott

Publications and source records attributed to Thomas C. Abbott.

9 recordsLinked to original sources

arXiv2026

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

The local environments of repeating fast radio bursts (FRBs) provide critical clues to their progenitors. While some active repeaters (e.g., FRB~20121102A, FRB~20190520B) are embedded in compact persistent radio sources (PRS), others appear to reside in cleaner environments. We present a high-resolution, multi-frequency (4$-$26 GHz) continuum study of the hyperactive repeater FRB 20220912A using the Karl G. Jansky Very Large Array (VLA). We report the discovery of a previously unknown radio source distinct from the compact PRSs seen in other FRBs, spatially coincident with the FRB position and offset by $\approx 300$~mas ($\approx 450$~pc) from the host galaxy's center. The absence of continuum emission in archival milliarcsecond-resolution VLBI observations indicates that the source is resolved out, ruling out a hyper-compact ($< 1$~pc) central-engine-powered origin. We constrain the physical diameter of the emitting region between 75~pc and 190~pc. We further demonstrate that the source is characterized by a steep non-thermal spectral index ($α\approx -0.73$) and a remarkably high star-formation rate surface density $Σ_{\text{SFR}} \gtrsim 13~M_{\odot}~\text{yr}^{-1}~\text{kpc}^{-2}$. We argue that this emission is best explained as a compact star-forming region within the host galaxy. This association with a site of ongoing star formation provides strong observational support for the hypothesis that young magnetars, formed after the deaths of massive stars, are the progenitors of at least some repeating FRBs.

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arXiv2026

Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB

We present 30 newly discovered repeating fast radio burst (FRB) sources from the second catalog of bursts detected by the FRB backend on the Canadian Hydrogen Intensity Mapping Experiment (CHIME/FRB). These repeaters have extragalactic dispersion measures (DMs) spanning $99.4-1446.0\ \text{pc cm}^{-3}$ and burst rates between $10^{-5.7}$ and $10^{-0.5}$ hr$^{-1}$ scaled to a fluence threshold of 5 Jy ms. We report evidence of monotonic, linear DM variations in four repeaters on years-long timescales. The newly discovered sources bring CHIME/FRB's total number of observed repeating FRBs to 80, 79 of which were discovered by CHIME/FRB, between 2018 July 25 and 2023 September 15. In the full CHIME/FRB sample, only 2.4$\pm 0.4\%$ of sources have been observed to repeat, and we do not find evidence for significant evolution of this value over the duration of the experiment. We find no substantial evidence for bimodal populations of one-off and repeating FRBs in their burst rate distributions; the distribution of upper limits on repeat rates implied from observations of as-yet one-offs is entirely contained within the observed range of repeater burst rates and the distributions do not appear inconsistent. Similarly, using the population analysis framework of C. W. James (2023), we find that our observations of repeating and yet-one-off FRBs are equally well fit assuming a power-law distribution of repeat rates with 50$-$100% of the population repeating.

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arXiv2026

Radio Monitoring Campaign of Active Repeater FRB 20220912A with CHIME

FRB 20220912A is a highly active repeating fast radio burst (FRB) source, discovered by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) using its real-time FRB detection system (CHIME/FRB). Here, we present results from a radio monitoring campaign of FRB 20220912A using CHIME, including ~200 hours of data collected by CHIME/Pulsar, spanning 1.5 years following the source's discovery. We present an analysis of a sample of 828 CHIME-detected bursts from FRB 20220912A, in the 400-800 MHz radio frequency band. The source remains highly active for ~10 weeks and has a bimodal wait-time distribution with peaks at $160^{+120}_{-70}$ ms and $306^{+14}_{-13}$ s. Assuming a radio efficiency factor of $10^{-4}$ and a beaming angle of 0.1, we estimate the total emitted energy from the source over the entire observing campaign to be $2 \times 10^{43}$ ergs. We report a 2.3$σ$ detection of a linear increase in the DM of $1.4 \pm 0.6$ pc cm$^{-3}$ yr$^{-1}$, with no significant trend in rotation measure (with a 3$σ$ upper limit of 13.4 rad m$^{-2}$ yr$^{-1}$). We contrast our findings with other active repeaters, which exhibit different DM and RM evolution to indicate that FRB 20220912A may reside in a unique local environment.

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arXiv2025

FRB 20250316A: A Brilliant and Nearby One-Off Fast Radio Burst Localized to 13 parsec Precision

Precise localizations of a small number of repeating fast radio bursts (FRBs) using very long baseline interferometry (VLBI) have enabled multiwavelength follow-up observations revealing diverse local environments. However, the 2--3\% of FRB sources that are observed to repeat may not be representative of the full population. Here we use the VLBI capabilities of the full CHIME Outriggers array for the first time to localize a nearby (40 Mpc), bright (kJy), and apparently one-off FRB source, FRB 20250316A, to its environment on 13-pc scales. We use optical and radio observations to place deep constraints on associated transient emission and the properties of its local environment. We place a $5σ$ upper limit of $L_{\mathrm{9.9~\mathrm{GHz}}} < 2.1\times10^{25}~\mathrm{erg~s^{-1}~Hz^{-1}}$ on spatially coincident radio emission, a factor of 100 lower than any known compact persistent radio source associated with an FRB. Our KCWI observations allow us to characterize the gas density, metallicity, nature of gas ionization, dust extinction and star-formation rate through emission line fluxes. We leverage the exceptional brightness and proximity of this source to place deep constraints on the repetition of FRB 20250316A, and find it is inconsistent with all well-studied repeaters given the non-detection of bursts at lower spectral energies. We explore the implications of a measured offset of 190$\pm20$ pc from the center of the nearest star-formation region, in the context of progenitor channels. FRB 20250316A marks the beginning of an era of routine localizations for one-off FRBs on tens of mas-scales, enabling large-scale studies of their local environments.

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arXiv2024

frb-voe: A Real-time Virtual Observatory Event Alert Service for Fast Radio Bursts

We present frb-voe, a publicly available software package that enables radio observatories to broadcast fast radio burst (FRB) alerts to subscribers through low-latency virtual observatory events (VOEvents). We describe a use-case of frb-voe by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) Collaboration, which has broadcast thousands of FRB alerts to subscribers worldwide. Using this service, observers have daily opportunities to conduct rapid multi-wavelength follow-up observations of new FRB sources. Alerts are distributed as machine-readable reports and as emails containing FRB metadata, and are available to the public within approximately 13 seconds of detection. A sortable database and a downloadable JSON file containing FRB metadata from all broadcast alerts can be found on the CHIME/FRB public webpage. The frb-voe service also provides users with the ability to retrieve FRB names from the Transient Name Server (TNS) through the frb-voe client user interface (CLI). The frb-voe service can act as a foundation on which any observatory that detects FRBs can build its own VOEvent broadcasting service to contribute to the coordinated multi-wavelength follow-up of astrophysical transients.

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arXiv2024

Contemporaneous X-ray Observations of 30 Bright Radio Bursts from the Prolific Fast Radio Burst Source FRB 20220912A

We present an extensive contemporaneous X-ray and radio campaign performed on the repeating fast radio burst (FRB) source FRB 20220912A for eight weeks immediately following the source's detection by CHIME/FRB. This includes X-ray data from XMM-Newton, NICER, and Swift, and radio detections of FRB 20220912A from CHIME/Pulsar and Effelsberg. We detect no significant X-ray emission at the time of 30 radio bursts with upper limits on $0.5-10.0$ keV X-ray fluence of $(1.5-14.5)\times 10^{-10}$ erg cm$^{-2}$ (99.7% credible interval, unabsorbed) on a timescale of 100 ms. Translated into a fluence ratio $η_{\text{ x/r}} = F_{\text{X-ray}}/F_{\text{radio}}$, this corresponds to $η_{\text{ x/r}} < 7\times10^{6}$. For persistent emission from the location of FRB 20220912A, we derive a 99.7% $0.5-10.0$ keV isotropic flux limit of $8.8\times 10^{-15}$ erg cm$^{-2}$ s$^{-1}$ (unabsorbed) or an isotropic luminosity limit of 1.4$\times10^{41}$ erg s$^{-1}$ at a distance of 362.4 Mpc. We derive a hierarchical extension to the standard Bayesian treatment of low-count and background-contaminated X-ray data, which allows the robust combination of multiple observations. This methodology allows us to place the best (lowest) 99.7% credible interval upper limit on an FRB $η_{\text{ x/r}}$ to date, $η_{\text{ x/r}} < 2\times10^6$, assuming that all thirty detected radio bursts are associated with X-ray bursts with the same fluence ratio. If we instead adopt an X-ray spectrum similar to the X-ray burst observed contemporaneously with FRB-like emission from Galactic magnetar SGR 1935+2154 detected on 2020 April 28, we derive a 99.7% credible interval upper limit on $η_{\text{ x/r}}$ of $8\times10^5$, which is only 3 times the observed value of $η_{\text{ x/r}}$ for SGR 1935+2154.

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arXiv2023

Comprehensive Bayesian analysis of FRB-like bursts from SGR 1935+2154 observed by CHIME/FRB

The bright millisecond-duration radio burst from the Galactic magnetar SGR 1935+2154 in 2020 April was a landmark event, demonstrating that at least some fast radio burst (FRB) sources could be magnetars. The two-component burst was temporally coincident with peaks observed within a contemporaneous short X-ray burst envelope, marking the first instance where FRB-like bursts were observed to coincide with X-ray counterparts. In this study, we detail five new radio burst detections from SGR 1935+2154, observed by the CHIME/FRB instrument between October 2020 and December 2022. We develop a fast and efficient Bayesian inference pipeline that incorporates state-of-the-art Markov chain Monte Carlo techniques and use it to model the intensity data of these bursts under a flexible burst model. We revisit the 2020 April burst and corroborate that both the radio sub-components lead the corresponding peaks in their high-energy counterparts. For a burst observed in 2022 October, we find that our estimated radio pulse arrival time is contemporaneous with a short X-ray burst detected by GECAM and HEBS, and Konus-Wind and is consistent with the arrival time of a radio burst detected by GBT. We present flux and fluence estimates for all five bursts, employing an improved estimator for bursts detected in the side-lobes. We also present upper limits on radio emission for X-ray emission sources which were within CHIME/FRB's field-of-view at trigger time. Finally, we present our exposure and sensitivity analysis and estimate the Poisson rate for FRB-like events from SGR 1935+2154 to be $0.005^{+0.082}_{-0.004}$ events/day above a fluence of $10~\mathrm{kJy~ms}$ during the interval from 28 August 2018 to 1 December 2022, although we note this was measured during a time of great X-ray activity from the source.

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arXiv2023

Explaining the GWSkyNet-Multi machine learning classifier predictions for gravitational-wave events

GWSkyNet-Multi is a machine learning model developed for classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes, a merger involving a neutron star, or a non-astrophysical glitch. This facilitates time sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary black hole mergers and mergers involving neutron stars. We leverage these findings to show that events misclassified by GWSkyNet-Multi in LVK's third observing run have distinct sky area, coherence factor, and distance values that influence the predictions and explain these misclassifications. The results help identify the model's limitations and inform potential avenues for further optimization.

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arXiv2021

GWSkyNet-Multi: A Machine Learning Multi-Class Classifier for LIGO-Virgo Public Alerts

Compact object mergers which produce both detectable gravitational waves and electromagnetic emission can provide valuable insights into the neutron star equation of state, the tension in the Hubble constant, and the origin of the r-process elements. However, electromagnetic follow-up of gravitational wave sources is complicated by false positive detections, sources which do not emit light, and the transient nature of the associated electromagnetic emission. GWSkyNet-Multi is a machine learning model that attempts to resolve these issues by providing real-time predictions of the source of a gravitational wave detection. The model uses information from Open Public Alerts (OPAs) released by LIGO-Virgo within minutes of a gravitational wave detection. GWSkyNet was first introduced in Cabero et al. (2020) as a binary classifier and uses the OPA skymaps to classify sources as either astrophysical or as glitches. In this paper, we introduce GWSkyNet-Multi, a new version of GWSkyNet which further distinguishes sources as binary black hole mergers, mergers involving a neutron star, or non-astrophysical glitches in the detectors. GWSkyNet-Multi is a sequence of three one-versus-all classifiers trained using a class-balanced and physically-motivated source mass distribution. Training on this data set, we obtain test set accuracies of 94% for BBH-versus-all, 94% for NS-versus-all, and 95% for glitch-versus-all. We obtain an overall accuracy of 93% using a hierarchical classification scheme. Furthermore, we correctly identify 36 of the 40 gravitational wave detections from the first half of LIGO-Virgo's third observing run (O3a) and present predictions for O3b sources. We also briefly discuss the interpretability of our models. As gravitational wave detections increase in number and frequency, GWSkyNet-Multi will be a powerful tool for prioritizing successful electromagnetic follow-up.

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