Group-finding with photometric redshifts: The Photo-z Probability Peaks algorithm

TL;DR

The paper introduces the Photo-z Probability Peaks (P3) algorithm, a new method for detecting small galaxy groups using photometric redshift data by identifying peaks in local galaxy overdensity, improving accuracy over previous methods.

Contribution

The P3 algorithm leverages redshift information to reduce background contamination and accurately detect low-richness galaxy groups, validated on simulations and real survey data.

Findings

Achieves 84% purity at S/N of 3 with sigma_z=0.05

Detects approximately 295 groups per square degree

Improves purity to 97% with sigma_z=0.02

Abstract

We present a galaxy group-finding algorithm, the Photo-z Probability Peaks (P3) algorithm, optimized for locating small galaxy groups using photometric redshift data by searching for peaks in the signal-to-noise of the local overdensity of galaxies in a three-dimensional grid. This method is an improvement over similar two-dimensional matched-filter methods in reducing background contamination through the use of redshift information, allowing it to accurately detect groups at lower richness. We present the results of tests of our algorithm on galaxy catalogues from the Millennium Simulation. Using a minimum S/N of 3 for detected groups, a group aperture size of 0.25 Mpc/h, and assuming photometric redshift accuracy of sigma_z = 0.05 it attains a purity of 84% and detects ~295 groups/deg.^2 with an average group richness of 8.6 members. Assuming photometric redshift accuracy of sigma_z = 0.02, it attains a purity of 97% and detects ~143 groups/deg.^2 with an average group richness of 12.5 members. We also test our algorithm on data available for the COSMOS field and the presently-available fields from the CFHTLS-Wide survey, presenting preliminary results of this analysis.