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Record W7162020669 · doi:10.82308/14113

Characterizing the fast radio burst population with the CHIME telescope

2022· dissertation· en· W7162020669 on OpenAlexaboutno aff
Pragya Chawla

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
Fundersnot available
KeywordsTelescopeFast radio burstRadio telescopeSkyPopulationPipeline (software)Intergalactic travelCOSMIC cancer databaseField (mathematics)

Abstract

fetched live from OpenAlex

Fast radio bursts (FRBs) are millisecond-duration radio transients of unknown origin. As these bursts are detectable at cosmological distances, they can be used to study the ionized plasma in the intergalactic medium. In order to harness the potential of FRBs as cosmological probes, it is important to develop a detailed understanding of the FRB population. This thesis aims to further our current understanding of two distinct aspects of the population, namely, source environments and activity levels, using the results of the CHIME/FRB project.The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a transit telescope operating in the frequency range of 400-800 MHz. The CHIME/FRB project searches for FRBs in real time over the instantaneous field of view of CHIME (~250 sq. deg.). As the telescope observes the full northern sky every day, the FRB detection pipeline can both discover new sources and monitor the ones which are known to repeat. The first CHIME/FRB catalog consists of 474 non-repeating sources and 61 bursts from 18 repeating sources. These bursts are well suited for population studies as they have been detected with a uniform selection function. We present algorithms to determine the on-sky exposure and sensitivity variations for the CHIME/FRB system. Using these algorithms, we generate full-sky maps of the total exposure during periods of nominal sensitivity. The estimated exposure can be used to characterize activity levels for known FRB sources. We demonstrate this using a study which uses the exposure information to validate the discovery of a periodic modulation in the activity of the repeating FRB source, FRB 20180916B. We then present a multi-band observation campaign of FRB 20180916B with the CHIME/FRB system, the Green Bank telescope (GBT) and the Low Frequency Array (LOFAR). We report on the detection of seven bursts in the frequency range of 300-400 MHz with the GBT. Knowing that the circumburst environment is optically thin to free-free absorption at 300 MHz, we find evidence against the association of a hyper-compact H II region or a young supernova remnant with the source. We also characterize the frequency dependence of burst activity and place constraints on the scattering properties of the source environment.Finally, we report on a Monte-Carlo based population synthesis study of two propagation effects, namely, dispersion and scattering, in the first CHIME/FRB catalog. We simulate intrinsic properties and propagation effects for a variety of FRB population models and compare the simulated distributions of dispersion measures and scattering timescales with the corresponding distributions from the CHIME/FRB catalog. Our simulations confirm the results of previous studies which suggested that the interstellar medium of the host galaxy alone cannot explain the observed scattering timescales of FRBs. We conclude that either FRBs inhabit environments with more extreme scattering properties than those inferred for Galactic pulsars, or that the circumgalactic media of intervening galaxies is a source of intense scattering

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.300
Teacher spread0.292 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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