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Record W7161980520 · doi:10.82308/39651

Automated radio follow-up for fast radio bursts with an application to a hyperactive repeating source, FRB 20220912A

2025· dissertation· en· W7161980520 on OpenAlexaboutno aff
Thomas Abbott

Bibliographic record

VenueOpen MIND · 2025
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
Fundersnot available
KeywordsFast radio burstObservatoryEvent (particle physics)Universal Software Radio PeripheralRadio broadcastingBroadcasting (networking)Software

Abstract

fetched live from OpenAlex

Fast radio bursts (FRBs) are brief (µs – ms), energetic astrophysical events originating from extra-galactic sources with unknown physical origins. Constraining the progenitor of FRBs can better our understanding of stellar evolution and rates of core collapse supernova. Many progenitor models predict rapid multi-wavelength or multi-messenger counterparts, thus coordinated real-time follow-up is crucial to constraining these models. frb-voe is 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). This thesis describes 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. 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. This thesis also describes an example follow-up of FRB 20220912A. This FRB is a highly active repeating FRB source, discovered by the CHIME radio telescope using the real-time FRB detection system and subsequently localized by the Deep Synoptic Array-110 (DSA-110) through VOEvents. Radio follow-up revealed the source displays interesting properties, such as “microshots”, a drifting time-variable central emitting frequency, and indications of variations of its dispersion measure (DM). We present results from a long-term radio follow-upcampaign of FRB 20220912A using over 200 hours of data collected by the CHIME Pulsar backend, spanning the 2 years following the source’s discovery. The CHIME/Pulsar backend uses a digitally-formed tracking beam to observe the source for 21 minutes daily at 41 us time resolution between 400-800 MHz. This study finds 828 bursts from the source, which test the energetics of some FRB progenitor models, and we show strong evidence for a variation in the source’s DM. We discuss the implications of the newly discovered DM variation and implications of the energetics regarding the physical origins of the source

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.373
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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