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Cluster abundance in chameleon f(R) gravity I : toward an accurate halo mass function prediction.

Cataneo, Matteo and Rapetti, David and Lombriser, Lucas and Li, Baojiu (2016) 'Cluster abundance in chameleon f(R) gravity I : toward an accurate halo mass function prediction.', Journal of cosmology and astroparticle physics., 2016 (12). 024.

Abstract

We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1088/1475-7516/2016/12/024
Publisher statement:This is an author-created, un-copyedited version of an article published in Journal of Cosmology and Astroparticle Physics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/1475-7516/2016/12/024
Date accepted:05 December 2016
Date deposited:07 December 2016
Date of first online publication:13 December 2016
Date first made open access:13 December 2017

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