Mass Modeling and Kinematics of Galaxy Clusters in Modified Gravity

TL;DR

This study investigates the chameleon screening mechanism in galaxy clusters by analyzing various mass models and using Bayesian methods to constrain parameters, showing minimal bias from model assumptions and low risk of false gravity modification detections.

Contribution

It extends previous work by considering multiple mass density profiles and demonstrates that assumptions about the mass model minimally affect constraints on modified gravity parameters.

Findings

Biases from incorrect mass model assumptions are minimal.

Spurious detection of modified gravity evidence is unlikely.

Constraints on chameleon parameters are robust across models.

Abstract

The chameleon screening mechanism has been constrained many a time using dynamic and kinematic galaxy cluster observables. Current constraints are, however, insensitive to different mass components within galaxy clusters and have been mainly focused on a single mass density profile, the Navarro-Frenk-While mass density model. In this work, we extend the study of the Chameleon screening mechanism in galaxy clusters by considering a series of mass density models, namely: generalized-Navarro-Frenk-While, b-Navarro-Frenk-While, Burket, Isothermal and Einasto. The coupling strength ($\beta$) and asymptotic value of the chameleon field ($\phi_\infty$) are constrained by using kinematics analyses of simulated galaxy clusters, generated both assuming General Relativity and a strong chameleon scenario. By implementing a Bayesian analysis we comprehensively show that the biases introduced due to an incorrect assumption of the mass model are minimal. Similarly, we also demonstrate that a spurious detection of evidence for modifications to gravity is highly unlikely when utilizing the kinematics of galaxy clusters.