Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 2010 | Published
Journal Article Open

Markov chain beam randomization: a study of the impact of PLANCK beam measurement errors on cosmological parameter estimation


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, called 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. We show that MCBR properly accounts for and provides the marginalized errors of the parameters. The method can be generalized and used to propagate any systematic uncertainties for which a set of templates is available. We apply the method to the Planck satellite, and consider future experiments. Beam measurement errors should have a small effect on cosmological parameters as long as the beam fitting is performed after removal of 1/f noise.

Additional Information

© ESO 2010. Received 31 July; Accepted 13 January 2010. G.R. is grateful to Jeffrey Jewell and Lloyd Knox for insightful discussions. L.P. acknowledges support by ASI contract I/016/07/0 "COFIS". K.M.H. receives support from NASA via JPL subcontract 1363745. We gratefully acknowledge support by the NASA Science Mission Directorate via the US Planck Project. The research described in this paper was partially carried out at the Jet propulsion Laboratory, California Institute of Technology, under a contract with NASA.

Attached Files

Published - Rocha2010p9838Astron_Astrophys.pdf


Files (632.2 kB)
Name Size Download all
632.2 kB Preview Download

Additional details

August 21, 2023
October 20, 2023