Constraining Dark Matter in Galactic Substructure

TL;DR

This paper evaluates the potential of gamma-ray signals from galactic subhalos to constrain dark matter properties, demonstrating that using the true photon count distribution improves estimation accuracy over traditional Poisson models.

Contribution

It derives the true photon count distribution from a detailed subhalo model and shows its advantage in dark matter parameter estimation compared to Poisson assumptions.

Findings

True PDF reduces error in dark matter property estimates by ~50%.

Combines gamma-ray distribution and counts PDF for improved detection prospects.

Provides a framework for analyzing gamma-ray data with realistic subhalo models.

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 Lambda-CDM-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 unbaised 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.