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• W2067709708 abstract "We revisit a recently introduced power spectrum estimation technique based on Gibbs sampling, with the goal of applying it to the high-resolution WMAP data. In order to facilitate this analysis, a number of sophistications have to be introduced, each of which is discussed in detail. We have implemented two independent versions of the algorithm to cross-check the computer codes and to verify that a particular solution to any given problem does not affect the scientific results. We then apply these programs to simulated data with known properties at intermediate (Nside = 128) and high (Nside = 512) resolutions, to study effects such as incomplete sky coverage and white versus correlated noise. From these simulations we also establish the Markov chain correlation length as a function of signal-to-noise ratio and give a few comments on the properties of the correlation matrices involved. Parallelization issues are also discussed, with emphasis on real-world limitations imposed by current supercomputer facilities. The scientific results from the analysis of the first-year WMAP data are presented in a companion letter." @default.
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• W2067709708 date "2004-12-01" @default.
• W2067709708 modified "2023-09-27" @default.
• W2067709708 title "Power Spectrum Estimation from High‐Resolution Maps by Gibbs Sampling" @default.
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• W2067709708 doi "https://doi.org/10.1086/425219" @default.
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