Nonlinear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

dc.creatorHamann, Jan
dc.creatorHannestad, Steen
dc.creatorMelchiorri, Alessandro
dc.creatorWong, Yvonne Y. Y.
dc.date2008-04-11
dc.date2008-09-08
dc.date.accessioned2026-07-07T11:49:46Z
dc.date.available2026-07-07T11:49:46Z
dc.descriptionWe explore and compare the performances of two nonlinear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-LCDM cosmologies. The first model is the well known Q model, first applied in the analysis of 2dFGRS data. The second, the P model, is inspired by the halo model, in which nonlinear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while both models perform equally well in providing adequate correction for a range of galaxy clustering data in standard LCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalisation, a technique sometimes used in the marginalisation of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended nonlinear correction model also because of its physical transparency.
dc.description21 pages, 8 figures, uses iopart.cls; v2: 22 pages, matches published version
dc.identifierhttps://arxiv.org/abs/0804.1789
dc.identifierhttp://arxiv.org/abs/0804.1789
dc.identifierJCAP0807:017,2008
dc.identifierdoi:10.1088/1475-7516/2008/07/017
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/203351
dc.subjectAstrophysics
dc.titleNonlinear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation
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