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http://hdl.handle.net/20.500.12386/31067
Titolo: | A Python approach for GRB afterglow analysis: sAGa (Software for AfterGlow Analysis) | Autori: | MARONGIU, MARCO GUIDORZI, CRISTIANO |
Data pubblicazione: | 2021 | Serie: | INAF Technical Reports - Rapporti Tecnici INAF | Report: | 99 | Abstract: | This technical note describes a fully self-consistent code in Python – called sAGa (Software for AfterGlow Analysis) – to cope with the complex landscape of GRB afterglows. sAGa adds up to other pre-existing broadband fitting tools in the literature and provides an independent check, emphasising the broadband study of GRB afterglows over the last two decades. This code aims to model GRB afterglow data within a self-consistent physically grounded picture. Built adopting a Bayesian approach, all the data set, from radio to gamma-rays, is modelled. By-products are plots of spectra and light-curves, and computation of the break frequencies and normalisations as a function of the shock microphysical parameters, such as the power-law index of the electron energy distribution, the fractions of the blastwave energy delivered to relativistic electrons and magnetic fields, and other parameters such as the kinetic energy of the explosion and the density of the circumburst medium (CBM). Dust extinction of optical along the sightline and scintillation in radio frequencies are also accounted for. sAGa has been successfully tested on the broadband data of the afterglows of GRB120521C, GRB090423, and GRB050904. Our results are consistent with those reported in the literature within 2 sigma. Moreover, the values of the power-law index of the electron energy distribution obtained from sAGa analysis are compatible with the inferences based on the lines of reasoning based on the observation of the optical/X-ray spectra. | URI: | http://hdl.handle.net/20.500.12386/31067 http://dx.doi.org/10.20371/INAF/TechRep/99 |
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È visualizzato nelle collezioni: | 4.01 Rapporti tecnici INAF |
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