Price, MA;
McEwen, JD;
Pratley, L;
Kitching, TD;
(2021)
Sparse Bayesian mass-mapping with uncertainties: Full sky observations on the celestial sphere.
Monthly Notices of the Royal Astronomical Society
, 500
(4)
pp. 5436-5452.
10.1093/mnras/staa3563.
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Abstract
To date weak gravitational lensing surveys have typically been restricted to small fields of view, such that the flat-sky approximation has been sufficiently satisfied. However, with Stage IV surveys (e.g. LSST and Euclid) imminent, extending mass-mapping techniques to the sphere is a fundamental necessity. As such, we extend the sparse hierarchical Bayesian massmapping formalism presented in previous work to the spherical sky. For the first time, this allows us to construct maximum a posteriori spherical weak lensing dark-matter mass-maps, with principled Bayesian uncertainties, without imposing or assuming Gaussianty. We solve the spherical mass-mapping inverse problem in the analysis setting adopting a sparsity promoting Laplacetype wavelet prior, though this theoretical framework supports all log-concave posteriors. Our spherical mass-mapping formalism facilitates principled statistical interpretation of reconstructions. We apply our framework to convergence reconstruction on high resolution N-body simulations with pseudo-Euclid masking, polluted with a variety of realistic noise levels, and show a significant increase in reconstruction fidelity compared to standard approaches. Furthermore, we perform the largest joint reconstruction to date of the majority of publicly available shear observational data sets (combining DESY1, KiDS450, and CFHTLens) and find that our formalism recovers a convergence map with significantly enhanced small-scale detail. Within our Bayesian framework we validate, in a statistically rigorous manner, the community’s intuition regarding the need to smooth spherical Kaiser-Squires estimates to provide physically meaningful convergence maps. Such approaches cannot reveal the small-scale physical structures that we recover within our framework.
Type: | Article |
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Title: | Sparse Bayesian mass-mapping with uncertainties: Full sky observations on the celestial sphere |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1093/mnras/staa3563 |
Publisher version: | https://doi.org/10.1093/mnras/staa3563 |
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: data analysis – methods: statistical – techniques: image processing – largescale structure of Universe. |
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/10117068 |
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