Forward analytical model for the optical selection bias on galaxy cluster lensing profiles

TL;DR

This paper develops a predictive analytical model to quantify how optical selection biases, mainly from line-of-sight projections, influence galaxy cluster lensing profiles and related observables.

Contribution

It introduces a scale-dependent parametrization of optical cluster bias and validates the model against simulations for DES Y3-like catalogs.

Findings

Model captures the impact of projection effects on the two-halo term.

Successfully reproduces bias in density profiles due to richness boosts.

Framework links line-of-sight structures to cosmology and survey parameters.

Abstract

Cluster catalogs selected by optical properties are subject to selection biases, primarily arising from unresolved systems along the line of sight. These biases affect key observables for cluster cosmology, such as the lensing signal and clustering statistics. In this work, we present a fully predictive forward analytical model to quantify the impact of optical-selection bias due to projection effects on cluster density profiles. This is achieved by introducing a scale-dependent parametrization of the optical cluster bias, whose small- and large-scale behaviour is set by the amplitude of projection effects, and by expressing the two-halo component of the density profile in terms of the contributions from off-axis halos along the line of sight. As a case study, we consider a DES Y3-like cluster catalog and validate our model against simulated samples. Our model successfully captures the dependence of the two-halo component on richness boosts induced by projections, as well as its evolution with richness and redshift. It also recovers the overall bias in the projected density profile relative to a randomly selected sample with the same mass distribution. The framework presented here provides a consistent methodology for modeling the impact of line-of-sight structures on the observed richness and density profiles of optically selected clusters, directly linking selection biases to the underlying cosmology and survey specifications.