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Abstract / Description of output
Modified Growth with CAMB (MGCAMB) is a patch for the Einstein-Boltzmann solver CAMB for cosmological tests of gravity. Until now, MGCAMB was limited to scales well-described by linear perturbation theory. In this work, we extend the framework with a phenomenological model that can capture nonlinear corrections in a broad range of modified gravity theories. The extension employs the publicly available halo model reaction code ReACT, developed for modeling the nonlinear corrections to cosmological observables in extensions of the ΛCDM model. The nonlinear extension makes it possible to use a wider range of data from large scale structure surveys, without applying a linear scale cut. We demonstrate that, with the 3×2pt Dark Energy Survey data, we achieve a stronger constraint on the linear phenomenological functions µ and Σ, after marginalzing over the additional
nonlinear parameter p1, compared to the case without the nonlinear extension and using a linear cut. The new version of MGCAMB is now forked with CAMB on GitHub allowing for compatibility with future upgrades.
nonlinear parameter p1, compared to the case without the nonlinear extension and using a linear cut. The new version of MGCAMB is now forked with CAMB on GitHub allowing for compatibility with future upgrades.
Original language | English |
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Article number | 003 |
Pages (from-to) | 1-17 |
Number of pages | 17 |
Journal | Journal of Cosmology and Astroparticle Physics (JCAP) |
Volume | 2024 |
Issue number | 11 |
DOIs | |
Publication status | Published - 7 Nov 2024 |
Keywords / Materials (for Non-textual outputs)
- Cosmological perturbation theory in GR and beyond
- Statistical sampling techniques
- cosmological parameters from LSS
- weak gravitational lensing
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Dive into the research topics of 'Extending MGCAMB tests of gravity to nonlinear scales'. Together they form a unique fingerprint.Projects
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Novel Non-linear Techniques for Cosmic Large Scale Structure
Engineering and Physical Sciences Research Council
1/04/22 → 31/01/26
Project: Research