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Title:
Constraining cosmological dark matter annihilation with gamma ray observations
Authors:
Dodelson, Scott; Belikov, Alexander V.; Hooper, Dan; Serpico, Pasquale
Affiliation:
AA(Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, Illinois 60510-0500, USA; Department of Astronomy and Astrophysics, The University of Chicago, Chicago, Illinois 60637-1433, USA; Kavli Institute for Cosmological Physics, Chicago, Illinois 60637-1433, USA), AB(Department of Physics, The University of Chicago, Chicago, Illinois 60637-1433, USA), AC(Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, Illinois 60510-0500, USA; Department of Astronomy and Astrophysics, The University of Chicago, Chicago, Illinois 60637-1433, USA), AD(Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, Illinois 60510-0500, USA; Physics Department, Theory Division, CERN, CH-1211 Geneva 23, Switzerland)
Publication:
Physical Review D, vol. 80, Issue 8, id. 083504 (PhRvD Homepage)
Publication Date:
10/2009
Origin:
APS
PACS Keywords:
Dark matter, gamma-ray
DOI:
10.1103/PhysRevD.80.083504
Bibliographic Code:
2009PhRvD..80h3504D

Abstract

Annihilation of cosmologically distributed dark matter is predicted to produce a potentially observable flux of high energy photons. This signal is predicted to be virtually uniform on the sky but, in order to be identified, must be extracted from various galactic and extragalactic backgrounds. We consider three techniques for extracting this signal from the backgrounds: spectral discrimination, angular discrimination, and distribution discrimination. We analyze the first two of these with the Fisher matrix formalism to obtain projections for constraints from the Fermi satellite. The third technique exploits the fact that the number of photons from extragalactic blazars is drawn from a distribution which is far from Poisson. Using a toy model, we show that knowledge of this distribution enhances one’s ability to extract the dark matter signal, while ignorance of it can lead to the introduction of a large systematic error.
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