Power spectrum tomography of dark matter annihilation with local galaxy distribution

TL;DR

This paper estimates the sensitivity of gamma-ray and galaxy catalog cross-correlation methods to dark matter annihilation signals, showing that tomographic approaches and halo substructure boosts significantly improve detection prospects for various dark matter masses.

Contribution

It provides updated theoretical sensitivity estimates for dark matter annihilation detection using gamma-ray and galaxy data, incorporating tomographic slicing and substructure effects.

Findings

Tomographic slicing improves sensitivity by a factor of a few to several.

Halo substructures can enhance detection sensitivity, probing canonical cross sections up to 700 GeV.

Modest substructure boosts still allow probing cross sections larger than the canonical value for certain mass ranges.

Abstract

Cross-correlating the gamma-ray background with local galaxy catalogs potentially gives stringent constraints on dark matter annihilation. We provide updated theoretical estimates of sensitivities to the annihilation cross section from gamma-ray data with Fermi telescope and 2MASS galaxy catalogs, by elaborating the galaxy power spectrum and astrophysical backgrounds, and adopting the Markov-Chain Monte Carlo simulations. In particular, we show that taking tomographic approach by dividing the galaxy catalogs into more than one redshift slice will improve the sensitivity by a factor of a few to several. If dark matter halos contain lots of bright substructures, yielding a large annihilation boost (e.g., a factor of $\sim$100 for galaxy-size halos), then one may be able to probe the canonical annihilation cross section for thermal production mechanism up to masses of $\sim$700 GeV. Even with modest substructure boost (e.g., a factor of $\sim$10 for galaxy-size halos), on the other hand, the sensitivities could still reach a factor of three larger than the canonical cross section for dark matter masses of tens to a few hundreds of GeV.