Issue |
EPJ Web Conf.
Volume 209, 2019
RICAP18, 7th Roma International Conference on Astroparticle Physics
|
|
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Article Number | 01027 | |
Number of page(s) | 5 | |
DOI | https://doi.org/10.1051/epjconf/201920901027 | |
Published online | 13 May 2019 |
https://doi.org/10.1051/epjconf/201920901027
Temporal studies on GRB light curves for neutrino flux predictions in multi-collision zone models
1 Dipartimento di Fisica, Università La Sapienza, P.le Aldo Moro 2, 00185 Roma, Italy
2 INFN - Sezione di Roma, P.le Aldo Moro 2, 00185 Roma, Italy
a e-mail: Angela.Zegarelli@roma1.infn.it
Published online: 13 May 2019
For the analysis here presented, the most luminous GRB detected by Konus-WIND until now was selected, namely GRB 110918A. Through the NeuCosmA code, simulating multi-zone collisions during the GRB prompt emission, a synthetic light curve representative of the observed one has been obtained, in order to study how characteristic parameters of the inner engine activity influence the light curve. This is achieved by varying the input parameters values in the simulation. In agreement with other previous studies, the inner engine is found to be more variable than the observed light curve. Furthermore, the Empirical Mode Decomposition method is applied and its stability is analyzed. Finally, the first multi-collision neutrino flux estimate for a real GRB is presented. Assuming the flux evaluated through the simulation reproducing the GRB gamma-ray light curve and taking into account the data taking conditions and the detector response during the GRB episode, the number of expected signal in the ANTARES neutrino telescope from GRB 110918A was calculated to be µs=6.1×10-4, which is found to be a factor 20 lower than previous estimations with one-zone models.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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