Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering

TL;DR

The paper introduces 'cluster-lensing', an open-source Python package that models galaxy cluster properties, including miscentering effects, to improve weak lensing analysis accuracy.

Contribution

It provides a comprehensive, easy-to-use Python toolkit for modeling galaxy clusters with miscentering effects, enhancing weak lensing studies.

Findings

Includes models for NFW profiles with miscentering

Calculates surface mass density and shear profiles

Facilitates accurate mass estimates in weak lensing

Abstract

We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $\Sigma(R)$ and differential surface mass density $\Delta\Sigma(R)$ profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo (Ford 2016). Full documentation, source code, and installation instructions are available at http://jesford.github.io/cluster-lensing/.