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Record W4383199524 · doi:10.1093/mnras/stad2009

High frequency study of FRB 20180916B using the 100-m Effelsberg radio telescope

2023· article· en· W4383199524 on OpenAlexaboutno aff
Suryarao Bethapudi, L. G. Spitler, Robert Main, Dongzi Li, Robert Wharton

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsnot available
FundersMax-Planck-GesellschaftCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsPhysicsRadio telescopeTelescopeAstronomyRadio spectrumAstrophysicsRadio frequencyRadio astronomyTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT FRB 20180916B is a repeating fast radio burst (FRB) with an activity period of 16.33 d. In previous observations ranging from ∼150−1400 MHz, the activity window was found to be frequency dependent, with lower frequency bursts occurring later. In this work, we present the highest frequency detections of bursts from this FRB, using the 100-m Effelsberg radio telescope at 4−8 GHz. We present the results from two observing campaigns. We performed the first campaign over an entire activity period which resulted in no detections. The second campaign was done in an active window at 4−8 GHz which we predicted from our modelling of chromaticity, resulting in eight burst detections. The bursts were detected in a window of 1.35 d, 3.6 d preceding the activity peak seen by Canadian hydrogen intensity mapping experiment, suggesting the chromaticity extends to higher frequency. The detected bursts have narrower temporal widths and larger spectral widths compared to lower frequencies. All of them have flat polarization position angle sweeps and high polarization fractions. The bursts also exhibit diffractive scintillation due to the Milky Way, following a f3.90 ± 0.05 scaling, and vary significantly over time. We find that burst rate across frequency scales as f−2.6 ± 0.2. Lastly, we examine implications of the frequency dependency on the source models.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.834

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 science0.0010.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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 designObservational
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

Citations28
Published2023
Admission routes1
Has abstractyes

Explore more

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