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MGLENS: Modified gravity weak lensing simulations for emulation-based cosmological inference

Harnois-Déraps, Joachim; Hernandez-Aguayo, Cesar; Cuesta-Lazaro, Carolina; Arnold, Christian; Li, Baojiu; Davies, Christopher T; Cai, Yan-Chuan

MGLENS: Modified gravity weak lensing simulations for emulation-based cosmological inference Thumbnail


Authors

Joachim Harnois-Déraps

Carolina Cuesta-Lazaro

Christian Arnold

Christopher T Davies

Yan-Chuan Cai



Abstract

We present MGLENS, a large series of modified gravity lensing simulations tailored for cosmic shear data analyses and forecasts in which cosmological and modified gravity parameters are varied simultaneously. Based on the FORGE and BRIDGE N-body simulation suites presented in companion papers, we construct 100 × 5000 deg2 of mock Stage-IV lensing data from two 4D Latin hypercubes that sample cosmological and gravitational parameters in f(R) and nDGP gravity, respectively. These are then used to validate our inference analysis pipeline based on the lensing power spectrum, exploiting our implementation of these modified gravity models within the COSMOSIS cosmological inference package. Sampling this new likelihood, we find that cosmic shear can achieve 95 per cent CL constraints on the modified gravity parameters of log10[fR0 ] < −4.77 and log10[H0rc] > 0.09, after marginalizing over intrinsic alignments of galaxies and including scales up to  = 5000. We also investigate the impact of photometric uncertainty, scale cuts, and covariance matrices. We finally explore the consequences of analysing MGLENS data with the wrong gravity model, and report catastrophic biases for a number of possible scenarios. The Stage-IV MGLENS simulations,
the FORGE and BRIDGE emulators and the COSMOSIS interface modules will be made publicly available upon journal acceptance.

Citation

Harnois-Déraps, J., Hernandez-Aguayo, C., Cuesta-Lazaro, C., Arnold, C., Li, B., Davies, C. T., & Cai, Y. (2023). MGLENS: Modified gravity weak lensing simulations for emulation-based cosmological inference. Monthly Notices of the Royal Astronomical Society, 525(4), 6336–6358. https://doi.org/10.1093/mnras/stad2700

Journal Article Type Article
Acceptance Date Sep 5, 2023
Online Publication Date Sep 7, 2023
Publication Date 2023-11
Deposit Date Jan 30, 2024
Publicly Available Date Jan 30, 2024
Journal Monthly Notices of the Royal Astronomical Society
Print ISSN 0035-8711
Publisher Royal Astronomical Society
Peer Reviewed Peer Reviewed
Volume 525
Issue 4
Pages 6336–6358
DOI https://doi.org/10.1093/mnras/stad2700
Public URL https://durham-repository.worktribe.com/output/2187362

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