Markov Chain Beam Randomization: a study of the impact of PLANCK beam measurement errors on cosmological parameter estimation

Understand

We introduce a new method to propagate uncertainties in the beam shapes used to measure the cosmic microwave background to cosmological parameters determined from those measurements.

• The method, which we call Markov Chain Beam Randomization, MCBR, randomly samples from a set of templates or functions that describe the beam uncertainties.
• The method is much faster than direct numerical integration over systematic `nuisance' parameters, and is not restricted to simple, idealized cases as is analytic marginalization.
• It does not assume the data are normally distributed, and does not require Gaussian priors on the specific systematic uncertainties.