Implications of the Gaia Sausage for Dark Matter Nuclear Interactions

TL;DR

This paper explores how the Gaia-Sausage stellar substructure influences dark matter velocity distributions and impacts direct detection experiments, highlighting challenges for light dark matter and potential sensitivity improvements for heavier masses.

Contribution

It introduces the impact of Gaia-derived dark matter velocity distributions on direct detection data interpretation and model reconstruction, emphasizing the importance of combining experiments and thresholds.

Findings

Gaia distribution complicates light DM detection (~10 GeV).

Combining different target experiments can mitigate challenges.

Heavy DM detection (>30 GeV) may see sensitivity improvements.

Abstract

The advent of the Gaia era has led to potentially revolutionary understanding of dark matter (DM) dynamics in our galaxy, which has important consequences for direct detection (DD) experiments. In this paper, we study how the empirical DM velocity distribution inferred from Gaia-Sausage, a dominant substructure in the solar neighborhood, affects the interpretation of DD data. We survey different classes of operators in the non-relativistic effective field theory that could arise from several relativistic benchmark models and emphasize that the Gaia velocity distribution could modify both the total number of events as well as the shape of the differential recoil spectra, the two primary observables in DD experiments. Employing the euclideanized signal method, we investigate the effects of the Gaia distribution on reconstructing DM model parameters and identifying the correct DM model given a positive signal at future DD experiments. We find that for light DM with mass ~10 GeV, the Gaia distribution poses an additional challenge for characterizing DM interactions with ordinary matter, which may be addressed by combining complementary DD experiments with different targets and lowering the detection threshold. Meanwhile, for heavy DM with mass above ~30 GeV, depending on the type of DM model, there could be a (moderate) improvement in the sensitivity at future DD experiments.