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Fast full N-body simulations of generic modified gravity: conformal coupling models

Ruan, Cheng-Zong and Hernández-Aguayo, César and Li, Baojiu and Arnold, Christian and Baugh, Carlton M and Klypin, Anatoly and Prada, Francisco (2022) 'Fast full N-body simulations of generic modified gravity: conformal coupling models.', Journal of Cosmology and Astroparticle Physics, 2022 (5). p. 18.

Abstract

We present mg-glam, a code developed for the very fast production of full N-body cosmological simulations in modified gravity (MG) models. We describe the implementation, numerical tests and first results of a large suite of cosmological simulations for three classes of MG models with conformal coupling terms: the f(R) gravity, symmetron and coupled quintessence models. Derived from the parallel particle-mesh code glam, mg-glamincorporates an efficient multigrid relaxation technique to solve the characteristic nonlinear partial differential equations of these models. For f(R) gravity, we have included new variants to diversify the model behaviour, and we have tailored the relaxation algorithms to these to maintain high computational efficiency. In a companion paper, we describe versions of this code developed for derivative coupling MG models, including the Vainshtein- and K-mouflage-type models. mg-glam can model the prototypes for most MG models of interest, and is broad and versatile. The code is highly optimised, with a tremendous speedup of a factor of more than a hundred compared with earlier N-body codes, while still giving accurate predictions of the matter power spectrum and dark matter halo abundance. mg-glam is ideal for the generation of large numbers of MG simulations that can be used in the construction of mock galaxy catalogues and the production of accurate emulators for ongoing and future galaxy surveys.

Item Type:Article
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Available under License - Creative Commons Attribution 4.0.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1088/1475-7516/2022/05/018
Publisher statement:2022 The Author(s). Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Date accepted:16 March 2022
Date deposited:07 July 2022
Date of first online publication:11 May 2022
Date first made open access:07 July 2022

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