paper

MG-MAMPOSSt: A code to test modifications of gravity with the dynamics of galaxy clusters

arXiv:2011.15089 · doi:10.1093/mnras/stab1727

Abstract

We present an upgraded version of \textsc{MG-MAMPOSSt}, an extension of the \textsc{MAMPOSSt} algorithm that performs Bayesian fits of models of mass and velocity anisotropy profiles to the distribution of tracers in projected phase space, to handle modified gravity models and constrain their parameters. The new version implements two distinct types of gravity modifications, namely general chameleon and Vainshtein screening, and is further equipped with a Monte-Carlo-Markov-Chain module for an efficient parameter space exploration. The program is complemented by the \textsc{ClusterGEN} code, capable of producing mock galaxy clusters under the assumption of spherical symmetry, dynamical equilibrium, and Gaussian local velocity distribution functions as in \textsc{MAMPOSSt}. We demonstrate the potential of the method by analysing a set of synthetic, isolated spherically-symmetric dark matter haloes, focusing on the statistical degeneracies between model parameters. Assuming the availability of additional lensing-like information, we forecast the constraints on the modified gravity parameters for the two models presented, as expected from joint lensing+internal kinematics analyses, in view of upcoming galaxy cluster surveys. In Vainshtein screening, we forecast the weak lensing effect through the estimation of the full convergence-shear profile. For chameleon screening, we constrain the allowed region in the space of the two free parameters of the model, further focusing on the subclass to obtain realistic bounds on the background field . Our analysis demonstrates the complementarity of internal kinematics and lensing probes for constraining modified gravity theories, and how the bounds on Vainshtein-screened theories improve through the combination of the two probes.

arXiv comment19 pages, 13 figures, accepted for publication on MNRAS. For v3 : an error in the acknowledgements of v2 has been corrected. A significant extension about lensing in Vainshtein screening has been added compared to v1

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