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Autores principales: Naess, Sigurd, Louis, Thibaut
Formato: Preprint
Publicado: 2022
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Acceso en línea:https://arxiv.org/abs/2210.02243
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author Naess, Sigurd
Louis, Thibaut
author_facet Naess, Sigurd
Louis, Thibaut
contents CMB mapmaking relies on a data model to solve for the sky map, and this process is vulnerable to bias if the data model cannot capture the full behavior of the signal. We demonstrate that this bias is not just limited to small-scale effects in high-contrast regions of the sky, but can manifest as $\mathcal{O}(1)$ power loss on large scales in the map under conditions and assumptions realistic for ground-based CMB telescopes. This bias is invisible to simulation-based tests that do not explicitly model them, making it easy to miss. We identify two different mechanisms that both cause suppression of long-wavelength modes: sub-pixel errors and detector gain calibration mismatch. We show that the specific case of subpixel bias can be eliminated using bilinear pointing matrices, but also provide simple methods for testing for the presence of large-scale model error bias in general.
format Preprint
id arxiv_https___arxiv_org_abs_2210_02243
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Large-scale power loss in ground-based CMB mapmaking
Naess, Sigurd
Louis, Thibaut
Instrumentation and Methods for Astrophysics
Cosmology and Nongalactic Astrophysics
CMB mapmaking relies on a data model to solve for the sky map, and this process is vulnerable to bias if the data model cannot capture the full behavior of the signal. We demonstrate that this bias is not just limited to small-scale effects in high-contrast regions of the sky, but can manifest as $\mathcal{O}(1)$ power loss on large scales in the map under conditions and assumptions realistic for ground-based CMB telescopes. This bias is invisible to simulation-based tests that do not explicitly model them, making it easy to miss. We identify two different mechanisms that both cause suppression of long-wavelength modes: sub-pixel errors and detector gain calibration mismatch. We show that the specific case of subpixel bias can be eliminated using bilinear pointing matrices, but also provide simple methods for testing for the presence of large-scale model error bias in general.
title Large-scale power loss in ground-based CMB mapmaking
topic Instrumentation and Methods for Astrophysics
Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2210.02243