Fast Radio Burst Localization with very Long Baseline Interferometry
Bibliographic record
Abstract
This thesis covers the development of Very Long Baseline Interferometry (VLBI) localization techniques for Fast Radio Bursts (FRBs). FRBs were discovered only in the 2000s and have revolutionized the radio transient field due to their unknown and complex emission mechanisms, their brightness, and the potential use as probes of the Universe's cosmology. The aim of this thesis project is to enhance the localization potential of Canadian Hydrogen Intensity Mapping Experiment (CHIME) in order to identify galactic hosts, which are necessary to precisely measure redshifts of FRBs. The VLBI prototype station chosen, was the Algonquin Radio Observatory (ARO) 10-m telescope a decommissioned radio dish from the 1960s. During the first two years of PhD studies, a complete refurbishment of the system was done, which included an update on the analog signal chain and a new acquisition system. While upgrades were on their way, CHIME Fast Radio Burst Project (CHIME/FRB) detected its first FRB in 2018, and today more than thousand have been observed. The ARO 10-m telescope has proved to be robust and stable over the years, with scientific results since its functioning on 2019 until the completion of this thesis (February 15th, 2022). Observations of at least three bright radio bursts have been recorded and analyzed at the ARO 10-m telescope, which have paved the way for the upcoming CHIME/FRB Outriggers project. A VLBI study has been carried out with the ARO testbed, including a new fringe fitting correlator model and a new method to phase calibrate using pulsars, particularity developed for the 400--800 MHz low frequency bandpass. The upcoming CHIME/FRB Outriggers project will have multiple baselines across North America in order to localized thousands of FRBs in the next years, to 50 mas precision, which no other experiment has been able to accomplish. Therefore, these results will open a new era in transient astronomy and unlock the unknown matter content of the Universe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".