Matter power spectrum emulator for f(R) modified gravity cosmologies

Nesar Ramachandra, Georgios Valogiannis, Mustapha Ishak, and Katrin Heitmann (LSST Dark Energy Science Collaboration)
Phys. Rev. D 103, 123525 – Published 10 June 2021

Abstract

Testing a subset of viable cosmological models beyond general relativity, with implications for cosmic acceleration and the dark energy associated with it, is within the reach of Rubin Observatory Legacy Survey of Space and Time (LSST) and a part of its endeavor. Deviations from GRw(z)CDM models can manifest in the growth rate of structure and lensing, as well as in screening effects on nonlinear scales. We explore the constraining power of small-scale deviations predicted by the f(R) Hu-Sawicki modified gravity candidate, by emulating this model with COLA (comoving Lagrangian acceleration) simulations. We present the experimental design, data generation, and interpolation schemes in cosmological parameters and across redshifts for the emulation of the boost in the power spectra due to modified gravity effects. Three preliminary applications of the emulator highlight the sensitivity to cosmological parameters, Fisher forecasting and Markov chain Monte Carlo inference for a fiducial cosmology. This emulator will play an important role for future cosmological analysis handling the formidable amount of data expected from Rubin Observatory LSST.

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  • Received 5 October 2020
  • Accepted 5 May 2021

DOI:https://doi.org/10.1103/PhysRevD.103.123525

© 2021 American Physical Society

Physics Subject Headings (PhySH)

Gravitation, Cosmology & Astrophysics

Authors & Affiliations

Nesar Ramachandra1, Georgios Valogiannis2,3,*, Mustapha Ishak4, and Katrin Heitmann1 (LSST Dark Energy Science Collaboration)

  • 1High Energy Physics Division, Argonne National Laboratory, Lemont, Illinois 60439, USA
  • 2Department of Astronomy, Cornell University, Ithaca, New York 14853, USA
  • 3Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA
  • 4Physics Department, The University of Texas at Dallas, Richardson, Texas 75080, USA

  • *gvalogiannis@g.harvard.edu

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Issue

Vol. 103, Iss. 12 — 15 June 2021

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