Optical Cluster-Finding with An Adaptive Matched-Filter Technique: Algorithm and Comparison with Simulations

TL;DR

This paper introduces an adaptive matched-filter algorithm for galaxy cluster detection in wide-field surveys, demonstrating high completeness and purity, accurate redshift estimation, and a reliable mass-richness relation in simulated SDSS data.

Contribution

The paper presents a novel adaptive matched-filter technique capable of identifying galaxy clusters across various survey data types with high efficiency and accuracy.

Findings

Detected clusters are ~85% complete and over 90% pure for masses above 1.0×10^{14} h^{-1} M_solar.

Estimated cluster redshifts have small errors, typically less than 0.01.

Cluster richness correlates roughly linearly with virial mass, recovering the luminosity-mass relation.

Abstract

We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with spectroscopic coverage, multicolor photometric redshifts, no redshift information at all, and any combination of these within one survey. It works with high efficiency in multi-band imaging surveys where photometric redshifts can be estimated with well-understood error distributions. Tests of the algorithm on realistic mock SDSS catalogs suggest that the detected sample is ~85% complete and over 90% pure for clusters with masses above 1.0*10^{14} h^{-1} M_solar and redshifts up to z=0.45. The errors of estimated cluster redshifts from maximum likelihood method are shown to be small (typically less that 0.01) over the whole redshift range with photometric redshift errors typical of those found in the Sloan survey. Inside the spherical radius corresponding to a galaxy overdensity of Delta=200, we find the derived cluster richness Lambda_{200} a roughly linear indicator of its virial mass M_{200}, which well recovers the relation between total luminosity and cluster mass of the input simulation.