The search for dark matter via strong lens inversions of galaxy clusters using genetic algorithms

Abstract

Gravitational lensing provides a direct means for measuring the masses of galaxies and galaxy clusters. Provided that enough constraints are available, one might even hope to obtain a handle on the precise distribution of the mass, which in turn may reveal information about the spatial distribution of the dark matter. We present an approach using genetic algorithms, allowing the user to ‘breed’ solutions which are compatible with available strong lensing data. The procedure allows various types of constraints to be used, including positional information, null-space information, and time-delay measurements. The method is non-parametric in the sense that it does not assume a particular shape of the mass distribution. This is accomplished by placing circularly symmetric basis functions – projected Plummer spheres – on a dynamic grid in the lens plane. Using simulations, we show that our procedure is able construct a mass distribution and source positions that are compatible with a given set of observations. We discuss the degeneracies that are inherent to lens inversion (and hence any lens inversion technique) and that limit the potential of strong lensing to yield precise estimates of the dark-matter distribution. We show how these degeneracies cause most of the differences between inversions of the same lensing cluster by different authors, using the famous cluster Cl 0024+1654 as a working example.