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Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations

Price, MA; McEwen, JD; Cai, X; Kitching, TD; (2019) Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations. Monthly Notices of the Royal Astronomical Society , 489 (3) pp. 3236-3250. 10.1093/mnras/stz2373. Green open access

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Abstract

Weak lensing convergence maps – upon which higher order statistics can be calculated – can be recovered from observations of the shear field by solving the lensing inverse problem. For typical surveys this inverse problem is ill-posed (often seriously) leading to substantial uncertainty on the recovered convergence maps. In this paper we propose novel methods for quantifying the Bayesian uncertainty in the location of recovered features and the uncertainty in the cumulative peak statistic – the peak count as a function of signal-to-noise ratio (SNR). We adopt the sparse hierarchical Bayesian mass-mapping framework developed in previous work, which provides robust reconstructions and principled statistical interpretation of reconstructed convergence maps without the need to assume or impose Gaussianity. We demonstrate our uncertainty quantification techniques on both Bolshoi N-body (cluster scale) and Buzzard V-1.6 (large-scale structure) N-body simulations. For the first time, this methodology allows one to recover approximate Bayesian upper and lower limits on the cumulative peak statistic at well-defined confidence levels.

Type: Article
Title: Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/mnras/stz2373
Publisher version: http://doi.org/10.1093/mnras/stz2373
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: gravitational lensing: weak, methods: statistical, techniques: image processing, cosmological parameters, dark matter
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.ucl.ac.uk/id/eprint/10082846
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