Searching for dark matter sources in Fermi-LAT’s unIDs with Machine Learning

Discussion timeslot (ZOOM-Meeting): 16. July 2021 - 18:00
ZOOM-Meeting URL: https://icrc2021.desy.de/pf_access_abstracts
Corresponding Session: https://icrc2021-venue.desy.de/channel/Presenter-Forum-1-Evening-All-Categories/48
Abstract:
'Around one third of the point-like sources in the Fermi-LAT catalogs remain as unidentified sources (UniDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source identified at other wavelengths, or to a well-known source type emitting only in gamma rays (such as certain pulsars). If the dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma rays by WIMPs annihilation. We propose a new search methodology that uses Machine Learning classification algorithms calibrated to a mixed sample of both experimental (known astrophysical objects) and theoretical (expected DM) data. With our methodology, we can correctly classify a promisingly high percent of astrophysical sources, opening a window to robustly search for DM source association among Fermi-LAT unIDs.'

Authors: Viviana Gammaldi
Co-Authors: Javier Coronado-Blázquez | Miguel A. Sánchez-Conde | Bryan Zaldivar
Indico-ID: 121
Proceeding URL: https://pos.sissa.it/395/493