Constraining galaxy properties with complete samples of lenses

TL;DR

Upcoming large-scale, high-resolution imaging surveys will enable complete samples of strong gravitational lenses, allowing precise constraints on galaxy mass profiles and stellar initial mass functions without additional dynamical data.

Contribution

This paper demonstrates that complete lens samples from future surveys can break degeneracies in galaxy property measurements, providing high-precision constraints on dark matter and stellar mass.

Findings

A Euclid-like survey can detect about 2.5 lenses per square degree.

A 50 deg$^2$ survey can constrain the dark matter slope to within 3.5%.

Stellar mass ratio can be determined with 10% uncertainty.

Abstract

The statistics of Einstein radii for a sample of strong lenses can provide valuable constraints on the underlying mass distribution. The correct interpretation, however, relies critically on the modelling of the selection of the sample, which has proven to be a limiting factor. This may change thanks to upcoming uniform high-resolution imaging surveys that cover a large fraction of the sky, because they can provide complete lens samples, with well understood selection criteria. To explore how the observed distribution of Einstein radii depends on the galaxy properties, we simulated a realistic complete sample of strong lenses, predicting a number density of lenses of about 2.5 deg$^{-2}$ for a \Euclid-like setup. Such data can break the degeneracy between the stellar initial mass function (IMF) and the inner slope of the density profile of dark matter, without having to rely on additional information from stellar dynamics. We found that a survey covering only 50 deg$^2$ can already provide tight constraints: assuming that the cosmology is known, the dark matter slope is recovered with an uncertainty of $3.5\%$, while the uncertainty in the ratio between the true stellar mass and that inferred from stellar population modelling was found to be $10\%$. These findings highlight the potential of this method when applied to samples of lenses with well-understood selection functions.