Multidetector multicomponent spectral matching and applications for cosmic microwave background data analysis

By Jacques Delabrouille, J. Cardoso, G. Patanchon. 2002

161 citations recorded by the source corpus.

We present a new method for analysing multidetector maps containing several astrophysical components. Our method, based on matching the data to a model in the spectral domain, permits us to estimate jointly the spatial power spectra of the components and of the noise, as well as their mixing coefficients. It is of particular relevance for analysis of millimetre-wave maps of cosmic microwave background (CMB) anisotropies.

Subfields: Astronomy and Astrophysics, Oceanography, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f77740cf8ec9d6e3e964d84e9370410bec369d83

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Citations in the corpus

A full sky, low foreground, high resolution CMB map from WMAP (2008, methodology): “In this paper, contrarily to other approaches which rely heavily on the structure of the data as described by a model, for instance a noisy linear mixture of independent components (Delabrouille et al. 2003), we assume as little as possible about the foregrounds and the noise.”
Component separation methods for the PLANCK mission (2008, methodology): “– Spectral matching independent component analysis (SMICA; Delabrouille et al. 2003; Cardoso et al. 2008).”
PICO: Probe of Inflation and Cosmic Origins (2019, methodology): “12Non-parametric techniques rely on the fact that CMB emission is uncorrelated with the foregrounds and thus a correlations analysis within a given spatial/frequency data-cube can be used to separate the two sources of emission [130, 227–230].”