Constraining dark matter in galactic substructure

Eric J. Baxter, Scott Dodelson, Savvas M. Koushiappas, and Louis E. Strigari
Phys. Rev. D 82, 123511 – Published 6 December 2010

Abstract

Detecting the dark matter annihilation signal from Galactic substructure, or subhalos, is an important challenge for high-energy gamma-ray experiments. In this paper we discuss detection prospects by combining two different aspects of the gamma-ray signal: the angular distribution and the photon counts probability distribution function (PDF). The true PDF from subhalos has been shown recently (by Lee et al.) to deviate from Poisson; we extend this analysis and derive the signal PDF from a detailed ΛCDM-based model for the properties of subhalos. We combine our PDF with a model for Galactic and extra-Galactic diffuse gamma-ray emission to obtain an estimator and projected error on dark matter particle properties (mass and annihilation cross section) using the Fermi gamma-ray space telescope. We compare the estimator obtained from the true PDF to that obtained from the simpler Poisson analysis. We find that, although both estimators are unbiased in the presence of backgrounds, the error on dark matter properties derived from the true PDF is 50% smaller than when utilizing the Poisson-based analysis.

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  • Received 31 July 2010

DOI:https://doi.org/10.1103/PhysRevD.82.123511

© 2010 The American Physical Society

Authors & Affiliations

Eric J. Baxter1, Scott Dodelson1,2,3, Savvas M. Koushiappas4, and Louis E. Strigari5

  • 1Department of Astronomy & Astrophysics, The University of Chicago, Chicago, Illinois 60637, USA
  • 2Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
  • 3Kavli Institute for Cosmological Physics, Chicago, Illinois 60637, USA
  • 4Department of Physics, Brown University, Providence, Rhode Island 02912, USA
  • 5Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305, USA

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Issue

Vol. 82, Iss. 12 — 15 December 2010

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