首页|Findings from National Autonomous University of Mexico (UNAM) Broaden Understanding of Machine Learning (Machine-learning Enhanced Photometric Analysis of the Extremely Bright Grb 210822a)
Findings from National Autonomous University of Mexico (UNAM) Broaden Understanding of Machine Learning (Machine-learning Enhanced Photometric Analysis of the Extremely Bright Grb 210822a)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Oxford Univ Press
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news originating from Mexico City, Mexico, by NewsRx correspondents, research stated, “We present analytical and numer- ical 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.” Funders for this research include Universidad Nacional Autonoma de Mexico, DGTIC UNAM on the supercomputer Miztli, Programa de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica (PAPIIT),UK Swift Science Data Centre at the University of Leicester, Consejo Nacional de Ciencia y Tecnologia (CONACyT). Our news journalists obtained a quote from the research from the National Autonomous University of Mexico (UNAM), “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 = 80 000 s that we interpreted as evidence of a jet break, which constrains the opening angle to be about theta(j) = (3-5) degrees. Finally, we apply a machine-learning technique to model the multiwavelength light curve of GRB 210822A using the AFTERGLOWPY LIBRARY.”
Mexico CityMexicoNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningNational Autonomous University of Mexico (UNAM)
NETL
NSTL
Oxford Univ Press
