Bayesian hierarchical modelling of weak lensing - the golden goal

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Title: Bayesian hierarchical modelling of weak lensing - the golden goal
Author(s): Heavens, A
Alsing, J
Jaffe, A
Hoffmann, T
Kiessling, A
Wandelt, B
Item Type: Conference Paper
Abstract: To accomplish correct Bayesian inference from weak lensing shear data requires a complete statistical description of the data. The natural framework to do this is a Bayesian Hierarchical Model, which divides the chain of reasoning into component steps. Starting with a catalogue of shear estimates in tomographic bins, we build a model that allows us to sample simultaneously from the the underlying tomographic shear fields and the relevant power spectra (E-mode, B-mode, and E-B, for auto- and cross-power spectra). The procedure deals easily with masked data and intrinsic alignments. Using Gibbs sampling and messenger fields, we show with simulated data that the large (over 67000-)dimensional parameter space can be efficiently sampled and the full joint posterior probability density function for the parameters can feasibly be obtained. The method correctly recovers the underlying shear fields and all of the power spectra, including at levels well below the shot noise.
Publication Date: 1-Dec-2017
Date of Acceptance: 12-Jul-2015
ISBN: 978-981-3226-59-3
Publisher: World Scientific
Start Page: 3005
End Page: 3010
Journal / Book Title: Proceedings of the MG14 Meeting on General Relativity
Copyright Statement: © The Editors. This is an Open Access proceedings volume published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.
Sponsor/Funder: Imperial College Trust
Funder's Grant Number: NA
Conference Name: MG14 Meeting on General Relativity
Keywords: astro-ph.CO
Publication Status: Published
Start Date: 2015-07-12
Finish Date: 2015-07-18
Conference Place: Rome, Italy
Appears in Collections:Physics
Faculty of Natural Sciences

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