Features in the Primordial Spectrum from WMAP: A Wavelet Analysis

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dc.creatorShafieloo, Arman
dc.creatorSouradeep, Tarun
dc.creatorManimaran, P.
dc.creatorPanigrahi, Prasanta K.
dc.creatorRangarajan, Raghavan
dc.date2006-11-11
dc.date2007-06-12
dc.date.accessioned2026-07-07T11:00:10Z
dc.date.available2026-07-07T11:00:10Z
dc.descriptionPrecise measurements of the anisotropies in the cosmic microwave background enable us to do an accurate study on the form of the primordial power spectrum for a given set of cosmological parameters. In a previous paper (Shafieloo and Souradeep 2004), we implemented an improved (error sensitive) Richardson-Lucy deconvolution algorithm on the measured angular power spectrum from the first year of WMAP data to determine the primordial power spectrum assuming a concordance cosmological model. This recovered spectrum has a likelihood far better than a scale invariant, or, `best fit' scale free spectra (Δln L = 25 w.r.t. Harrison Zeldovich, and, Δln L = 11 w.r.t. power law with n_s=0.95). In this paper we use Discrete Wavelet Transform (DWT) to decompose the local features of the recovered spectrum individually to study their effect and significance on the recovered angular power spectrum and hence the likelihood. We show that besides the infra-red cut off at the horizon scale, the associated features of the primordial power spectrum around the horizon have a significant effect on improving the likelihood. The strong features are localised at the horizon scale.
dc.description8 pages, 4 figures, uses Revtex4, matches version accepted to Phys. Rev. D, main results and conclusions unchanged, references added
dc.identifierhttps://arxiv.org/abs/astro-ph/0611352
dc.identifierhttp://arxiv.org/abs/astro-ph/0611352
dc.identifierPhys.Rev.D75:123502,2007
dc.identifierdoi:10.1103/PhysRevD.75.123502
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/187627
dc.subjectAstrophysics
dc.subjectGeneral Relativity and Quantum Cosmology
dc.subjectHigh Energy Physics - Theory
dc.titleFeatures in the Primordial Spectrum from WMAP: A Wavelet Analysis
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