Extreme value distribution for gamma-ray-burst prompt data -- How unexpected was the BOAT event?
Stefano Covino

TL;DR
This paper applies extreme value theory to gamma-ray burst data to assess the rarity of the exceptional GRB221009A event, finding it highly unlikely under standard models and suggesting it is an outlier.
Contribution
The study introduces a model-independent approach using generalized extreme value distribution to analyze the extremities of GRB data, highlighting the rarity of the BOAT event.
Findings
GRB data's extreme values are consistent with a single population.
GRB221009A's fluence and peak flux are statistically exceptional.
The probability of observing such an event is about once per millennium.
Abstract
Gamma-Ray Bursts (GRBs) are known to be unpredictable in time and position. A few (observationally) exceptional events have been observed, as GRB221009A that stands out for its fluence and peak flux, being orders of magnitude higher than what measured so far. Analyzing the observed fluence, peak flux or duration distributions typically requires one to assume some scenarios, and the consistency of the observed data with the predictions turns out to be an important model diagnostic. However, it is also of interest to model these distributions using general statistical properties that do not rely on specific model assumptions, allowing one to derive inferences only based on the consistency of the observed distributions with the hypothesis of one single population of events that generate them. We obtained fluences, peak fluxes and durations from the catalogues of GRBs observed by the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
