Residual noise covariance for Planck low-resolution data analysis

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dc.contributor University of Helsinki, Department of Physics en
dc.contributor University of Helsinki, Helsinki Institute of Physics en
dc.contributor University of Helsinki, Department of Physics en
dc.contributor University of Helsinki, Department of Physics en Keskitalo, R. A. J. Ashdown, M. Cabella, P. Kisner, T. Poutanen, T. Stompor, R. G. Bartlett, J. Borrill, J. Cantalupo, C. de Gasperis, G. de Rosa, A. de Troia, G. K. Eriksen, H. Finelli, F. M. Gorski, K. Gruppuso, A. Hivon, E. Jaffe, A. Keihänen, E. Kurki-Suonio, H. R. Lawrence, C. Natoli, P. Paci, F. Polenta, G. Rocha, G. 2010-12-20T16:05:00Z 2010-12-20T16:05:00Z 2010
dc.identifier.citation Keskitalo , R , A. J. Ashdown , M , Cabella , P , Kisner , T , Poutanen , T , Stompor , R , G. Bartlett , J , Borrill , J , Cantalupo , C , de Gasperis , G , de Rosa , A , de Troia , G , K. Eriksen , H , Finelli , F , M. Gorski , K , Gruppuso , A , Hivon , E , Jaffe , A , Keihänen , E , Kurki-Suonio , H , R. Lawrence , C , Natoli , P , Paci , F , Polenta , G & Rocha , G 2010 , ' Residual noise covariance for Planck low-resolution data analysis ' , Astronomy & Astrophysics , vol. 522 , pp. A94 . en
dc.identifier.issn 0004-6361
dc.identifier.other PURE: 10373324
dc.identifier.other PURE UUID: a491152d-24ed-4d1c-9b5a-42454e6bf8f0
dc.identifier.other ArXiv:
dc.identifier.other WOS: 000284153100100
dc.identifier.other Scopus: 78149306048
dc.identifier.other ORCID: /0000-0002-4618-3063/work/43223696
dc.identifier.other ORCID: /0000-0003-1804-7715/work/43224038
dc.description.abstract Aims: Develop and validate tools to estimate residual noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the sub-percent level at multipoles, ell > 2Nside, where Nside is the HEALPix resolution parameter. We show that sufficient characterization of the residual noise is unavoidable if one is to draw reliable contraints on large scale anisotropy. Conclusions: We have described how to compute the low-resolution maps, with a controlled sky signal level, and a reliable estimate of covariance of the residual noise. We have also presented a method to smooth the residual noise covariance matrices to describe the noise correlations in smoothed, bandwidth limited maps. en
dc.format.extent 29
dc.language.iso eng
dc.relation.ispartof Astronomy & Astrophysics
dc.rights en
dc.subject 115 Astronomy, Space science en
dc.subject astro-ph.CO en
dc.subject astro-ph.IM en
dc.subject 114 Physical sciences en
dc.title Residual noise covariance for Planck low-resolution data analysis en
dc.type Article
dc.description.version Peer reviewed
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion

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