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Cold dark matter (CDM) constitutes most of the matter in the Universe. The interplay between dark and luminous matter in dense cosmic environments like galaxy clusters is studied theoretically using cosmological simulations. Observed gravitational lensing is used to test and characterize the properties of substructures - the small-scale distribution of dark matter - in clusters. An apt metric, the probability of strong lensing events produced by dark matter substructure, is devised and computed for 11 galaxy clusters. We report that observed cluster substructures are more efficient lenses than predicted by CDM simulations, by more than an order of magnitude. We suggest that hitherto undiagnosed systematic issues with simulations or incorrect assumptions about the properties of dark matter could explain our results.
Recently, Meneghetti et al. reported an excess of small-scale gravitational lenses in galaxy clusters, compared to simulations of standard cold dark matter (CDM). We propose a self-interacting dark matter (SIDM) scenario, where a population of subhal
We present a systematic search for wide-separation (Einstein radius >1.5), galaxy-scale strong lenses in the 30 000 sq.deg of the Pan-STARRS 3pi survey on the Northern sky. With long time delays of a few days to weeks, such systems are particularly w
We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neura
We perform a semi-automated search for strong gravitational lensing systems in the 9,000 deg$^2$ Dark Energy Camera Legacy Survey (DECaLS), part of the DESI Legacy Imaging Surveys (Dey et al.). The combination of the depth and breadth of these survey
We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to fi