Inferring dark matter subhalo properties from simulated subhalo-stream encounters

Abstract: In the cold dark matter paradigm, our Galaxy is predicted to contain >10000 dark matter subhaloes in the $10^5-10^8M_\odot$ range which should be completely devoid of stars. Stellar streams are sensitive to the presence of these subhaloes, which can create small-scale features in streams if they pass closely enough. Modelling these encounters can therefore, potentially recover the subhalo's properties. In this work, we demonstrate this for streams generated in numerical simulations, modelled on eccentric orbits in a realistic Milky Way potential, which includes the Large Magellanic Cloud and the subhalo itself. We focus on a mock model of the ATLAS-Aliqa Uma stream and inject a $10^7 M_\odot$ subhalo, creating a similar discontinuous morphology to current observations. We then explore how well subhalo properties are recovered using mock stream observations, consisting of no observational errors, as well as assuming realistic observational setups. These setups include present day style observations, and what will be possible with 4MOST and Gaia DR5 in the future. We show that we can recover all parameters describing the impact even with uncertainties matching existing data, including subhalo positions, velocities, mass and scale radius. Modelling the subhalo on an orbit instead of assuming an impulse approximation, we greatly reduce the degeneracy between subhalo mass and velocity seen in previous works. However, we find a slight bias in the subhalo mass (~0.1 dex). This demonstrates that we should be able to reliably extract the properties of subhaloes with stellar streams in the near future.