Identifying Dark Matter Subhalos with Fermi
Nestor Mirabal, NASA/GSFC (USA)
Roberto A. Lineros, IFIC CSIC/UVEG
The all-sky coverage and unprecedented sensitivity of the Large Area Telescope (LAT) onboard NASAʼs Fermi satellite is producing the most detailed inventory of the gamma-ray universe from about 20 MeV to more than 300 GeV. This remarkable dataset provides an unprecedented opportunity to understand the demographics of gamma-ray point sources and could help us achieve a major breakthrough in physics beyond the Standard Model. I will describe the great promise of machine-learning algorithms in identifying potential dark matter signals in the Fermi catalog.