Volume 627, July 2019
|Number of page(s)||14|
|Section||Numerical methods and codes|
|Published online||05 July 2019|
Multi-resolution Bayesian CMB component separation through Wiener filtering with a pseudo-inverse preconditioner⋆
Institute of Theoretical Astrophysics, University of Oslo, PO Box 1029 Blindern, 0315 Oslo, Norway
2 Department of Mathematics, University of Oslo, PO Box 1080 Blindern, 0316 Oslo, Norway
Accepted: 7 May 2019
We present a Bayesian model for multi-resolution component separation for cosmic microwave background (CMB) applications based on Wiener filtering and/or computation of constrained realizations, extending a previously developed framework. We also develop an efficient solver for the corresponding linear system for the associated signal amplitudes. The core of this new solver is an efficient preconditioner based on the pseudo-inverse of the coefficient matrix of the linear system. In the full sky coverage case, the method gives an increased speed of the preconditioner, and it is easier to implement in terms of practical computer code. In the case where a mask is applied and prior-driven constrained realization is sought within the mask, this is the first time full convergence has been achieved at the full resolution of the Planck data set.
Key words: methods: statistical / cosmic background radiation
The prototype benchmark code is available at https://github.com/dagss/cmbcr
© ESO 2019
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