SKA Sensitivity to Potential Radio Emission from Dark Matter Annihilation in Ursa Major III

TL;DR

This paper evaluates SKA's ability to detect radio signals from dark matter annihilation in Ursa Major III, highlighting its potential to improve current constraints despite astrophysical uncertainties.

Contribution

It provides the first detailed analysis of SKA's sensitivity to dark matter signals in Ursa Major III, considering astrophysical uncertainties and comparing with existing constraints.

Findings

SKA can detect DM annihilation signals with cross sections as low as 10^{-30} cm^3/s.

Sensitivity depends on magnetic field, diffusion, and density profile uncertainties.

SKA has the potential to surpass current indirect detection limits.

Abstract

The recently discovered stellar system, Ursa Major III/UNIONS 1, may be the faintest and densest dwarf spheroidal satellite galaxy of the Milky Way. Owing to its close proximity and substantial dark matter (DM) component, Ursa Major III emerges as a highly promising target for DM indirect detection. It is known that electrons and positrons originating from DM annihilation can generate a broad radio spectrum through the processes of synchrotron radiation and inverse Compton scattering within galaxies. In this study, we investigate the potential of the Square Kilometre Array (SKA) in detecting radio signatures arising from DM annihilation in Ursa Major III over a 100 hour observation period. Our analysis indicates that the SKA has strong capabilities in detecting these signatures. For instance, the SKA sensitivity to the DM annihilation cross section is estimated to reach $\mathcal{O}(10^{-30})-\mathcal{O}(10^{-28})\; \rm cm^{3} s^{-1}$ in the DM mass range from several GeV to $\sim100$ GeV for the $e^+e^-$ and $\mu^+\mu^-$ annihilation channels. The precise results are significantly influenced by various astrophysical factors, such as the strength of magnetic field, the diffusion coefficient, and the DM density profile in the dwarf galaxy. We discuss the impact of the uncertainties associated with these factors, and find that the SKA sensitivities have the potential to surpass the current constraints, even when considering these uncertainties.