Testing strong lensing subhalo detection with a cosmological simulation
  Strong gravitational lensing offers a compelling test of the cold dark matter
paradigm, as it allows for subhaloes with masses of $\sim10^{9}$ M$_\odot$ and
below to be detected. We test commonly-used techniques for detecting dark
matter subhaloes superposed in images of strongly lensed galaxies. For the lens
we take a simulated galaxy in a $\sim10^{13}$ M$_\odot$ halo grown in a
high-resolution cosmological hydrodynamics simulation, which we view from two
different directions. To remove particle noise, we represent the projected
galaxy mass distribution by a series of analytic Gaussian profiles which
precisely capture the features of the projected galaxy. We first model the lens
mass as a broken power-law density profile (the parameterization of which
includes a core ensuring the results are unaffected by a numerical central core
in the simulated galaxy) and then search for small haloes. Of the two
projections, one has a regular elliptical shape, while the other has distinct
deviations from an elliptical shape. For the former, the broken power-law model
gives no false positives and correctly recovers the mass of the superposed
small halo, but for the latter we do find false positives and the inferred halo
mass is overestimated by a factor of $\sim4-5$. We then replace the broken
power-law model by a more complex model in which the lens mass is decomposed
into separate stellar and dark matter components. In this case, we show that we
can precisely capture the complex projected structures of the simulated galaxy
and correctly infer the input parameters of the superposed small halo. By
improving the lens galaxy mass model, we argue this enables more robust subhalo
inference that can detect lower mass dark matter subhaloes, strengthening the
technique's ability to test alternative models of dark matter which do not form
dark matter subhaloes below a cut-off mass.
