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Mapping Spatially Varying Additive Biases in Cosmic Shear Data

Kitching, TD; Deshpande, AC; Taylor, PL; (2021) Mapping Spatially Varying Additive Biases in Cosmic Shear Data. The Open Journal of Astrophysics , 4 (1) 10.21105/astro.2110.01275. Green open access

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Abstract

In this paper we address the challenge of extracting maps of spatially varying unknown additive biases from cosmic shear data. This is done by exploiting the isotropy of the cosmic shear field, and the anisotropy of a typical additive bias field, using an autocorrelation discrepancy map; which identifies significant non-Gaussian components of the map. We test this approach using simulations and find that the autocorrelation discrepancy map produces spatially varying features that are indicative of the additive bias field both in amplitude and spatial variation. We then apply this to the Dark Energy Survey Year 1 data, and find evidence for spatially varying additive biases of at most 0.002 on large-scales. The method can be used to empirically inform modelling of the spatially varying additive bias field in any cosmological parameter inference, and can act as a validation test for cosmic shear surveys.

Type: Article
Title: Mapping Spatially Varying Additive Biases in Cosmic Shear Data
Open access status: An open access version is available from UCL Discovery
DOI: 10.21105/astro.2110.01275
Publisher version: https://doi.org/10.21105/astro.2110.01275
Language: English
Additional information: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10141388
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