Inferring dark matter subhalo properties from simulated subhalo-stream encounters

Kavli Affiliate: Alexander P. Ji

| First 5 Authors: Tariq Hilmi, Denis Erkal, Sergey E. Koposov, Ting S. Li, Sophia Lilleengen

| Summary:

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.

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