Dwarf spheroidal $J$-factor likelihoods for generalized NFW profiles

TL;DR

This paper develops a new statistical method to estimate the J-factors of dwarf spheroidal galaxies, improving the robustness of dark matter indirect detection analyses by providing profile likelihoods instead of Bayesian estimates.

Contribution

The paper introduces a scheme to derive profile likelihoods for J-factors with multiple free parameters, validated on simulations, and applied to gamma-ray data for improved dark matter constraints.

Findings

Validated the method on Gaia Challenge simulations.

Provided maximum likelihood estimates for ten dwarf spheroidals.

Derived new upper limits on dark matter annihilation cross-section.

Abstract

Indirect detection strategies of particle Dark Matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical background. To robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data -- which are generally frequentist -- rely on estimating the abundance of DM by calculating the so-called $\textit{J-factor}$. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using Jeans equation, commonly by means of Bayesian techniques which entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for $J$-factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for coverage and bias. We present the profile likelihood function and maximum likelihood estimates for the $J$-factor of ten dSphs . As an illustration, we apply these profiles likelihood to recently published analyses of gamma-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as $\textit{classical dwarfs}$. The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.