Machine-Learning Enhanced Photometric Analysis of the Extremely Bright GRB 210822A

Abstract

We present analytical and numerical models of the bright long GRB 210822A at z=1.736. The intrinsic extreme brightness exhibited in the optical, which is very similar to other bright GRBs (e.g., GRBs 080319B, 130427A, 160625A 190114C, and 221009A), makes GRB 210822A an ideal case for studying the evolution of this particular kind of GRB. We use optical data from the RATIR instrument starting at T+315.9 s, with publicly available optical data from other ground-based observatories, as well as Swift/UVOT, and X-ray data from the Swift/XRT instrument. The temporal profiles and spectral properties during the late stages align consistently with the conventional forward shock model, complemented by a reverse shock element that dominates optical emissions during the initial phases (T<300 s). Furthermore, we observe a break at T=80000s that we interpreted as evidence of a jet break, which constrains the opening angle to be about θj=(3-5) degrees. Finally, we apply a machine-learning technique to model the multi-wavelength light curve of GRB 210822A using the AFTERGLOWPY library. We estimate the angle of sight θobs=(6.4 0.1) × 10-1 degrees, the energy E0=(7.9 1.6)× 1053 ergs, the electron index p=2.54 0.10, the thermal energy fraction in electrons εe=(4.63 0.91) × 10-5 and in the magnetic field εB= (8.66 1.01) × 10-6, the efficiency = 0.89 0.01, and the density of the surrounding medium n0 = 0.85 0.01 cm-3.

0

Turn this paper into a lesson

ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…