Testing modified gravity scenarios with direct peculiar velocities

Abstract

The theoretical basis of dark energy remains unknown and could signify a need to modify the laws of gravity on cosmological scales. In this study we investigate how the clustering and motions of galaxies can be used as probes of modified gravity theories, using galaxy and direct peculiar velocity auto- and cross-correlation functions. We measure and fit these correlation functions in simulations of $\Lambda$CDM, DGP, and $f(R)$ cosmologies and, by extracting the characteristic parameters of each model, we show that these theories can be distinguished from General Relativity using these measurements. We present forecasts showing that with sufficiently large data samples, this analysis technique is a competitive probe that can help place limits on allowed deviations from GR. For example, a peculiar velocity survey reaching to $z=0.5$ with $20\%$ distance accuracy would constrain model parameters to 3-$\sigma$ confidence limits ${\log }_{10}|f_{R0}|<-6.45$ for $f(R)$ gravity and $r_c>2.88c/H_0$ for nDGP, assuming a fiducial GR model.

14 pages, 12 figures, 3 tables, accepted for publication in MNRAS

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Cited by in corpus (5)

• Growth-rate measurement with type-Ia supernovae using ZTF survey simulations
• Constraining modified gravity scenarios with the 6dFGS and SDSS galaxy peculiar velocity datasets
• Bayesian deep learning for cosmic volumes with modified gravity
• Consistencies and inconsistencies in redshift-independent distances
• Prospects for measuring the Doppler magnification dipole with LSST and DESI