Misinterpreting modified gravity as dark energy: A quantitative study

Yuewei Wen, Eva Nesbit, Dragan Huterer, Scott Watson

Research output: Contribution to journalArticlepeer-review

Abstract

Standard cosmological data analyses typically constrain simple phenomenological dark-energy parameters, for example the present-day value of the equation of state parameter, w 0, and its variation with scale factor, w a. However, results from such an analysis cannot easily indicate the presence of modified gravity. Even if general relativity does not hold, experimental data could still be fit sufficiently well by a phenomenological w 0 w aCDM, unmodified-gravity model. Hence, it would be very useful to know if there are generic signatures of modified gravity in standard analyses. Here we present, for the first time to our knowledge, a quantitative mapping showing how modified gravity models look when (mis)interpreted within the standard unmodified-gravity analysis. Scanning through a broad space of modified-gravity (Horndeski) models, and assuming a near-future survey consisting of CMB, BAO, and SNIa observations, we report values of the best-fit set of cosmological parameters including (w 0, w a) that would be inferred if modified gravity were at work. We find that modified gravity models that can masquerade as standard gravity lead to very specific biases in standard-parameter spaces. We also comment on implications for measurements of the amplitude of mass fluctuations described by the parameter S 8.

Original languageEnglish (US)
Article number042
JournalJournal of Cosmology and Astroparticle Physics
Volume2022
Issue number3
DOIs
StatePublished - Mar 1 2022

Keywords

  • dark energy theory
  • Machine learning
  • modified gravity

ASJC Scopus subject areas

  • Astronomy and Astrophysics

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