Taming astrophysical bias in direct dark matter searches

TL;DR

This paper investigates how assumptions about dark matter distribution and galactic models affect the accuracy of dark matter property measurements in direct detection experiments, emphasizing the importance of accounting for astrophysical uncertainties.

Contribution

It demonstrates that systematic biases from incorrect distribution assumptions are manageable through marginalization and shows that velocity distribution can be reconstructed unbiasedly.

Findings

Bias from wrong distribution assumptions is about 1 sigma.

Bias from incorrect galactic models can be large but is mitigated by marginalization.

Velocity distribution can be reconstructed without bias.

Abstract

We explore systematic biases in the identification of dark matter in future direct detection experiments and compare the reconstructed dark matter properties when assuming a self-consistent dark matter distribution function and the standard Maxwellian velocity distribution. We find that the systematic bias on the dark matter mass and cross-section determination arising from wrong assumptions for its distribution function is of order ~1\sigma. A much larger systematic bias can arise if wrong assumptions are made on the underlying Milky Way mass model. However, in both cases the bias is substantially mitigated by marginalizing over galactic model parameters. We additionally show that the velocity distribution can be reconstructed in an unbiased manner for typical dark matter parameters. Our results highlight both the robustness of the dark matter mass and cross-section determination using the standard Maxwellian velocity distribution and the importance of accounting for astrophysical uncertainties in a statistically consistent fashion.