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Bayesian component separation: The Planck experience

Published online by Cambridge University Press:  08 May 2018

Ingunn Kathrine Wehus Open the ORCID record for Ingunn Kathrine Wehus [Opens in a new window]  and
Hans Kristian Eriksen
Ingunn Kathrine Wehus
Affiliation:
Institute of Theoretical Astrophysics, University of Oslo, Postboks 1029 Blindern, 0315 Oslo, Norway email: i.k.wehus@astro.uio.no
Hans Kristian Eriksen
Affiliation:
Institute of Theoretical Astrophysics, University of Oslo, Postboks 1029 Blindern, 0315 Oslo, Norway email: i.k.wehus@astro.uio.no
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Abstract

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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. The main challenges are high code complexity and computational cost. Whether or not these costs are justified for a given experiment depends on its final uncertainty budget. We therefore predict that the importance of Bayesian component separation techniques is likely to increase with time for intensity mapping experiments, similar to what has happened in the CMB field, as observational techniques mature, and their overall sensitivity improves.

Keywords

Cosmology: cosmic microwave backgroundGalaxy: generalMethods: data analysis
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S333: Peering towards Cosmic Dawn , October 2017 , pp. 274 - 279
Copyright
Copyright © International Astronomical Union 2018 

References

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