2019MNRAS.482.1824S

We present EasyCritics, an algorithm to detect strongly lensing groups and clusters in wide-field surveys without relying on a direct recognition of arcs. EasyCritics assumes that light traces mass in order to predict the most likely locations of critical curves from the observed fluxes of luminous red early-type galaxies in the line of sight. The positions, redshifts, and fluxes of these galaxies constrain the idealized gravitational lensing potential as a function of source redshift up to five free parameters, which are calibrated on few known lenses. From the lensing potential, EasyCritics derives the critical curves for a given, representative source redshift. The code is highly parallelized, uses fast Fourier methods and, optionally, GPU acceleration in order to process large data sets efficiently. The search of a 1 deg² field of view requires less than 1 min on a modern quad-core CPU, when using a pixel resolution of 0.25 arcsec px^–1. In this first part of a paper series on EasyCritics, we describe the main underlying concepts and present a first demonstration on data from the Canada-France-Hawaii-Telescope Lensing Survey. We show that EasyCritics is able to identify known group- and cluster-scale lenses, including a cluster with two giant arc candidates that were previously missed by automated arc detectors.