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Record W3112292050 · doi:10.3847/2041-8213/abec72

LOFAR Detection of 110–188 MHz Emission and Frequency-dependent Activity from FRB 20180916B

2021· article· en· W3112292050 on OpenAlexafffund
Ziggy Pleunis, Daniele Michilli, C. Bassa, J. W. T. Hessels, Arun Naidu, Bridget C. Andersen, Pragya Chawla, Emmanuel Fonseca, A. Gopinath, V. M. Kaspi, V. I. Kondratiev, Dongzi Li, Mohit Bhardwaj, P. J. Boyle, Charanjot Brar, Tomás Cassanelli, Yashwant Gupta, Alexander Josephy, R. Karuppusamy, A. Keimpema, Franz Kirsten, Calvin Leung, B. Marcote, Kiyoshi W. Masui, Ryan Mckinven, Bradley W. Meyers, Cherry Ng, Kenzie Nimmo, Z. Paragi, Mubdi Rahman, Paul Scholz, Kaitlyn Shin, Kendrick M. Smith, I. H. Stairs, Shriharsh P. Tendulkar

Bibliographic record

VenueThe Astrophysical Journal Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsPerimeter InstituteUniversity of TorontoMcGill University
FundersInstitut de Ciències del CosmosFonds de recherche du Québec – Nature et technologiesScience and Technology Facilities CouncilNational Research Council CanadaObservatoire de Paris, Université de Recherche Paris Sciences et LettresNational Defense Science and Engineering GraduateSmithsonian Astrophysical ObservatoryNatural Sciences and Engineering Research Council of CanadaFondation familiale TrottierBundesministerium für Bildung und ForschungInstitut Périmètre de physique théoriqueUniversity of British ColumbiaUniversité d'OrléansNational Radio Astronomy ObservatoryVetenskapsrådetMinisterio de Economía y CompetitividadMax-Planck-GesellschaftUniversity of TorontoDepartment of Atomic Energy, Government of IndiaNederlandse Organisatie voor Wetenschappelijk OnderzoekMinisterio de Ciencia e InnovaciónCentre National de la Recherche ScientifiqueIndustry CanadaMcGill UniversityAssociated UniversitiesU.S. Department of DefenseMcGill Space InstituteMinisterium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-WestfalenTata Institute of Fundamental ResearchCanadian Institute for Advanced ResearchNational Science FoundationScience Foundation IrelandPrecursory Research for Embryonic Science and TechnologyGovernment of Canada
KeywordsLOFARPhysicsFast radio burstAstrophysicsFaraday effectPolarization (electrochemistry)Spectral lineComputational physicsRadio telescopeAstronomyMagnetic fieldChemistry

Abstract

fetched live from OpenAlex

Abstract The object FRB 20180916B is a well-studied repeating fast radio burst source. Its proximity (∼150 Mpc), along with detailed studies of the bursts, has revealed many clues about its nature, including a 16.3 day periodicity in its activity. Here we report on the detection of 18 bursts using LOFAR at 110–188 MHz, by far the lowest-frequency detections of any FRB to date. Some bursts are seen down to the lowest observed frequency of 110 MHz, suggesting that their spectra extend even lower. These observations provide an order-of-magnitude stronger constraint on the optical depth due to free–free absorption in the source’s local environment. The absence of circular polarization and nearly flat polarization angle curves are consistent with burst properties seen at 300–1700 MHz. Compared with higher frequencies, the larger burst widths (∼40–160 ms at 150 MHz) and lower linear polarization fractions are likely due to scattering. We find ∼2–3 rad m −2 variations in the Faraday rotation measure that may be correlated with the activity cycle of the source. We compare the LOFAR burst arrival times to those of 38 previously published and 22 newly detected bursts from the uGMRT (200–450 MHz) and CHIME/FRB (400–800 MHz). Simultaneous observations show five CHIME/FRB bursts when no emission is detected by LOFAR. We find that the burst activity is systematically delayed toward lower frequencies by about 3 days from 600 to 150 MHz. We discuss these results in the context of a model in which FRB 20180916B is an interacting binary system featuring a neutron star and high-mass stellar companion.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.275
Teacher spread0.266 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations179
Published2021
Admission routes2
Has abstractyes

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