Novel techniques and prospects for the indirect detection of dark matter

Abstract

The microphysics of dark matter remains elusive nearly a century after its discovery. However,a promising window into the unknown is opened at the intersection of cosmology, particle physics, and astrophysics. The indirect detection of dark matter through its annihilation products is sensitive to the dark matter mass, annihilation cross section, and coupling properties to the standard model. Notably, secondary gamma rays are expected from annihilating thermal relic WIMPs that may be observable with current gamma-ray observatories. Here, we discuss the underpinnings of indirect detection and methods to enhance its discriminative power. We begin by testing the consistency of dark matter velocity distributions obtained from dark matter-only numerical simulations with analytic predictions, using the publicly available Via Lactea 2 dataset as an example. Next, we assess the ability of future MeV-range observatories to constrain the hadronic final states produced by light quark-coupling dark matter annihilation or decay. The unique spectral features of resulting π0 and η decays provide statistical resolving power and insight into the dark matter to quark current coupling. We then consider constraints on p-wave dark matter in a density spike surrounding the supermassive black hole at the center of M87. Due to the large velocity dispersion of dark matter particles in the spike, it is possible to place tight constraints on p-wave annihilation with Fermi-LAT and MAGIC data. By applying Approximate Bayesian Computation to a mock analysis of the diffuse gamma-ray background, we show that parameter constraints can be tightened beyond those possible in exact likelihood analysis. In our model of isotropic backgrounds and dark matter annihilation in galactic subhalos, this method allows for the inclusion of energy information in posterior estimates, whereas the corresponding likelihood is computationally intractable. Finally, we develop a method for analyzing the Fermi Galactic Center gamma-ray excess that relies on simulation-based inference with neural posterior models to jointly analyze photon directional and spectral information. We demonstrate the ability to significantly differentiate between the millisecond pulsar and annihilating dark matter hypotheses.