2021
DOI: 10.1093/mnras/stab1773
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Singling out modified gravity parameters and data sets reveals a dichotomy between Planck and lensing

Abstract: An important route to testing General Relativity (GR) at cosmological scales is usually done by constraining modified gravity (MG) parameters added to the Einstein perturbed equations. Most studies have analyzed so far constraints on pairs of MG parameters, but here, we explore constraints on one parameter at a time while fixing the other at its GR value. This allows us to analyse various models while benefiting from a stronger constraining power from the data. We also explore which specific datasets are in te… Show more

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Cited by 3 publications
(2 citation statements)
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“…Refs. [122,132,133]. The distinction between our binned σ 8 (z) model and modified gravity parameterizations is largely one of interpretation rather than modeling specifics.…”
Section: F Binned σ8(z)mentioning
confidence: 99%
“…Refs. [122,132,133]. The distinction between our binned σ 8 (z) model and modified gravity parameterizations is largely one of interpretation rather than modeling specifics.…”
Section: F Binned σ8(z)mentioning
confidence: 99%
“…Studies evolved from the phenomenology of specific models, such as f (R) [21][22][23][24] and DGP [25,26], to the development of general frameworks [27][28][29][30][31][32][33][34] for studying broad classes of modified gravity theories, such as Horndeski [35,36] and beyond [37][38][39][40], along with the numerical tools for interpreting observations within these frameworks, such as EFTCAMB [41][42][43] and hi_class [44,45]. The essential difference between MGCAMB (and similar software, like MGCLASS [46] and ISiTGR [47][48][49]) and codes like EFTCAMB and hi_class is that the latter JCAP08(2023)038 are exact tools for testing scalar-tensor theories, albeit of most general type, while the former are purely phenomenological, helping constrain departures from GR that are more directly probed by large-scale structure surveys. In practice, one always has to choose a particular parameterization and such choices are often driven by intuition gained from scalar-tensor theories.…”
Section: Introductionmentioning
confidence: 99%