Characterization of gamma-ray burst prompt emission spectra down to soft X-rays
Journal
Date Issued
2018
Author(s)
Abstract
Detection of prompt emission by Swift-XRT provides a unique tool to study how the prompt spectrum of gamma-ray bursts (GRBs) extends down to the soft X-ray band. This energy band is particularly important for prompt emission studies, since it is towards low energies that the observed spectral shape is in disagreement with the synchrotron predictions. Unfortunately, the number of cases where XRT started observing the GRB location during the prompt phase is very limited. In this work, we collect a sample of 34 GRBs and perform joint XRT+BAT spectral analysis of prompt radiation, extending a previous study focused on the 14 brightest cases. Fermi-GBM observations are included in the analysis when available (11 cases), allowing the characterization of prompt spectra from soft X-rays to MeV energies. In 62% of the spectra, the XRT data reveal a hardening of the spectrum, well described by introducing an additional, low-energy power-law segment (with index α1) into the empirical fitting function. The break energy below which the spectrum hardens has values between 3 keV and 22 keV. A second power-law (α2) describes the spectrum between the break energy and the peak energy. The mean values of the photon indices are <α1> = -0.51 (σ = 0.24) and <α2> = -1.56 (σ = 0.26). These are consistent, within one σ, with the synchrotron values in fast cooling regime. As a test, if we exclude XRT data from the fits we find typical results: the spectrum below the peak energy is described by a power law with <α> = -1.15. This shows the relevance of soft X-ray data in revealing prompt emission spectra consistent with synchrotron spectra. Finally, we do not find any correlation between the presence of the X-ray break energy and the flux, fluence, or duration of the prompt emission.
Volume
616
Start page
A138
Issn Identifier
0004-6361
Ads BibCode
2018A&A...616A.138O
Rights
open.access
File(s)![Thumbnail Image]()
Loading...
Name
aa32172-17.pdf
Description
Pdf editoriale
Size
5.94 MB
Format
Adobe PDF
Checksum (MD5)
3dad22e7ede0e81622d49d3b324d0ad7