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arXiv · 1906.08030

How to avoid X'es around point sources in maximum likelihood CMB maps

Sigurd K. Naess
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Abstract

The maximum likelihood estimator for CMB map-making is optimal and unbiased as long as the data model is correct, but in practice it rarely is, with model errors including sub-pixel structure and instrumental problems like time-variable gain and pointing errors. In the presence of such errors, the solution is biased, with the local error in each pixel leaking outwards along the scanning pattern by a noise correlation length. The most important sources of such leakage are strong point sources, and for common scanning patterns the leakage manifests as an X around each such source. I discuss why this happens, and present several old and new methods for mitigating and/or eliminating this leakage, along with a small stand-alone TOD simulator and map-maker in Python that implements them.

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Sigurd K. Naess. 2019-11-24. How to avoid X'es around point sources in maximum likelihood CMB maps. https://doi.org/10.1088/1475-7516%2F2019%2F12%2F060

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