The Detection and Statistics of Giant Arcs Behind CLASH Clusters

Abstract

We developed an algorithm to find and characterize gravitationally lensed galaxies (arcs) to perform a comparison of the observed and simulated arc abundance. Observations are from the Cluster Lensing And Supernova survey with Hubble (CLASH). Simulated CLASH images are created using the MOKA package and also clusters selected from the high resolution, hydrodynamical simulations, MUSIC, over the same mass and redshift range as the CLASH sample. The algorithm' s arc elongation accuracy, completeness and false positive rate are determined and used to compute an estimate of the true arc abundance. We derive a lensing efficiency of $4\pm 1$ arcs (with length $\ge 6"$ and length-to-width ratio $\ge 7$) per cluster for the X-ray selected CLASH sample, $4\pm 1$ arcs per cluster for the MOKA simulated sample and $3\pm 1$ arcs per cluster for the MUSIC simulated sample. The observed and simulated arc statistics are in full agreement. We measure the photometric redshifts of all detected arcs and find a median redshift $z_s=1.9$ with 33% of the detected arcs having $z_s>3$. We find that the arc abundance does not depend strongly on the source redshift distribution but is sensitive to the mass distribution of the dark matter halos (e.g. the $c-M$ relation). Our results show that consistency between the observed and simulated distributions of lensed arc sizes and axial ratios can be achieved by using cluster-lensing simulations that are carefully matched to the selection criteria used in the observations.

54 pages, 23 figures, accepted for publication in the Astrophysical Journal

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• The science of short exposures: Hubble SNAPshot observations of massive galaxy clusters
• PICS: Simulations of Strong Gravitational Lensing in Galaxy Clusters
• Crowded Field Galaxy Photometry: Precision Colors in the CLASH Clusters
• RELICS: A Strong Lens Model for SPT-CLJ0615-5746, a z=0.972 Cluster
• The Strongest Cluster Lenses: An Analysis of the Relation Between Strong Gravitational Lensing Strength and the Physical Properties of Galaxy Clusters
• Automated Lensing Learner: Automated Strong Lensing Identification with a Computer Vision Technique
• EasyCritics I: Efficient detection of strongly-lensing galaxy groups and clusters in wide-field surveys
• Cosmology through arc statistics I: sensitivity to ${\Omega }_m$ and ${\sigma }_8$
• The importance of secondary halos for strong lensing in massive galaxy clusters across redshift
• The DES Bright Arcs Survey: Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey 5,000 Sq. Deg. Footprint
• Detection of Strongly Lensed Arcs in Galaxy Clusters with Transformers
• MIFAL: fully automated Multiple-Image Finder ALgorithm for strong-lens modelling -- proof of concept
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• Strong Lensing In The Inner Halo Of Galaxy Clusters
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