Bayesian component separation: The Planck experience

Understand

Bayesian component separation techniques have played a central role in the data reduction process of Planck.

• The most important strength of this approach is its global nature, in which a parametric and physical model is fitted to the data.
• Such physical modeling allows the user to constrain very general data models, and jointly probe cosmological, astrophysical and instrumental parameters.
• This approach also supports statistically robust goodness-of-fit tests in terms of data-minus-model residual maps, which are essential for identifying residual systematic effects in the data.