A model-independent analysis of the Fermi Large Area Telescope gamma-ray data from the Milky Way dwarf galaxies and halo to constrain dark matter scenarios [electronic resource].
- Published
- Washington, D.C. : United States. Dept. of Energy, 2012.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy - Physical Description
- pages 26-39 : digital, PDF file
- Additional Creators
- SLAC National Accelerator Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access
- Free-to-read Unrestricted online access
- Summary
- Here, we implemented a novel technique to perform the collective spectral analysis of sets of multiple gamma-ray point sources using the data collected by the Large Area Telescope onboard the Fermi satellite. The energy spectra of the sources are reconstructed starting from the photon counts and without assuming any spectral model for both the sources and the background. In case of faint sources, upper limits on their fluxes are evaluated with a Bayesian approach. Our analysis technique is very useful when several sources with similar spectral features are studied, such as sources of gamma rays from annihilation of dark matter particles. We also present the results obtained by applying this analysis to a sample of dwarf spheroidal galaxies and to the Milky Way dark matter halo. The analysis of dwarf spheroidal galaxies yields upper limits on the product of the dark matter pair annihilation cross section and the relative velocity of annihilating particles that are well below those predicted by the canonical thermal relic scenario in a mass range from a few GeV to a few tens of GeV for some annihilation channels.
- Report Numbers
- E 1.99:1356669
- Subject(s)
- Other Subject(s)
- Note
- Published through SciTech Connect.
07/22/2012.
": S0927650512001417"
Astroparticle Physics 37 C ISSN 0927-6505 AM
M. N. Mazziotta; F. Loparco; F. de Palma; N. Giglietto. - Funding Information
- AC02-76SF00515
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