Extracting the Gamma Ray Signal from Dark Matter Annihilation in the Galactic Center Region

TL;DR

GLAST's Galactic Center gamma-ray search aims to identify dark matter annihilation signals by exploiting both spectral signatures and angular morphology to separate them from bright astrophysical backgrounds. The authors model point-like and diffuse backgrounds, compute the DM-induced flux using the J-factor of chosen halo profiles, and forecast 95% CL constraints on the DM mass $m_X$ and annihilation cross section $\langle\sigma v\rangle$ for NFW and Moore halos. They find that, in many scenarios, a DM signal can be identified and key parameters such as the inner halo slope $\gamma$ and, to a lesser extent, the DM mass can be constrained, with limitations arising from background assumptions and PSF accuracy. A post-submission note reports that PSF updates modestly degrade sensitivity, but the approach remains a viable path for indirect DM detection with GLAST.

Abstract

The GLAST satellite mission will study the gamma ray sky with considerably greater exposure than its predecessor EGRET. In addition, it will be capable of measuring the arrival directions of gamma rays with much greater precision. These features each significantly enhance GLAST's potential for identifying gamma rays produced in the annihilations of dark matter particles. The combined use of spectral and angular information, however, is essential if the full sensitivity of GLAST to dark matter is to be exploited. In this paper, we discuss the separation of dark matter annihilation products from astrophysical backgrounds, focusing on the Galactic Center region, and perform a forecast for such an analysis. We consider both point-like and diffuse astrophysical backgrounds and model them using a point-spread-function for GLAST. While the results of our study depend on the specific characteristics of the dark matter signal and astrophysical backgrounds, we find that in many scenarios it is possible to successfully identify dark matter annihilation radiation, even in the presence of significant astrophysical backgrounds.

Figures (5)

• Figure 1: A simulated sky map of the gamma ray backgrounds present in the region of the Galactic Center, after two years of observation by GLAST. Each point denotes one gamma ray detected. In the top and bottom frames, photons with energy above 3 and 10 GeV are shown, respectively.
• Figure 2: The gamma ray spectrum per annihilation for a 100 GeV (top) and 500 GeV (bottom) WIMP. Each curve denotes the result for a different dominant annihilation mode.
• Figure 3: The projected exclusion limits at 95% confidence level from GLAST (after ten years) on the WIMP annihilation cross section, as a function of the WIMP mass. The region above the dotted line is already excluded by EGRET dingus. The dashed and solid lines show the projections for GLAST for an assumed isotropic diffuse background and the limit case where the astrophysical background has exactly the same angular distribution of the DM signal, respectively. In the upper and lower frames, the NFW and Moore et al. halo profiles have been adopted, respectively. Also shown are points representing a random scan of supersymmetric models.
• Figure 4: The ability of GLAST to measure the annihilation cross section and mass of dark matter after ten years of observation. Here, we have used a benchmark scenario with $m_X=100$ GeV, $\langle\sigma v\rangle = 3 \times 10^{-26}$ cm$^3$/s and an NFW halo profile. The inner and outer contours in each frame represent the 2 and 3$\,\sigma$ regions, respectively. In the top frame, the halo profile shape was treated as if it is known in advance. In the lower frame, we marginalize over the inner slope of the profile.
• Figure 5: The ability of GLAST to measure the inner slope of the halo profile and the mass of dark matter particle (marginalizing over the annihilation cross section) after ten years of observation. Here, we have used a benchmark scenario with $m_X=100$ GeV, $\langle\sigma v\rangle = 3 \times 10^{-26}$ cm$^3$/s and an NFW halo profile. The inner and outer contours represent the 2 and 3$\,\sigma$ regions, respectively.