Multi-resolution Bayesian CMB component separation through Wiener-filtering with a pseudo-inverse preconditioner

Understand

We present a Bayesian model for multi-resolution CMB component separation 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 a speed-up of 2--3x in compute time compared to a simple diagonal preconditioner, and it is easier to implement in terms of practical computer code.