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Nested sampling for physical scientists

Authors :
Greg Ashton
Noam Bernstein
Johannes Buchner
Xi Chen
Gábor Csányi
Andrew Fowlie
Farhan Feroz
Matthew Griffiths
Will Handley
Michael Habeck
Edward Higson
Michael Hobson
Anthony Lasenby
David Parkinson
Livia B. Pártay
Matthew Pitkin
Doris Schneider
Joshua S. Speagle
Leah South
John Veitch
Philipp Wacker
David J. Wales
David Yallup
Ashton, G [0000-0001-7288-2231]
Bernstein, N [0000-0002-6532-1337]
Csányi, G [0000-0002-8180-2034]
Lasenby, A [0000-0002-8208-6332]
Pitkin, M [0000-0003-4548-526X]
Speagle, JS [0000-0003-2573-9832]
South, L [0000-0002-5646-2963]
Veitch, J [0000-0002-6508-0713]
Wales, DJ [0000-0002-3555-6645]
Apollo - University of Cambridge Repository
Source :
Ashton, G, Bernstein, N, Buchner, J, Chen, X, Csányi, G, Feroz, F, Fowlie, A, Griffiths, M, Habeck, M, Handley, W, Higson, E, Hobson, M, Lasenby, A, Parkinson, D B, Pártay, L B, Pitkin, M, Schneider, D, South, L, Speagle, J, Veitch, J, Wacker, P, Wales, D & Yallup, D 2022, ' Nested Sampling for physical scientists ', Nature Reviews Methods Primers, vol. 2, no. 1, 39 . https://doi.org/10.1038/s43586-022-00121-x
Publication Year :
2022
Publisher :
arXiv, 2022.

Abstract

We review Skilling's nested sampling (NS) algorithm for Bayesian inference and more broadly multi-dimensional integration. After recapitulating the principles of NS, we survey developments in implementing efficient NS algorithms in practice in high-dimensions, including methods for sampling from the so-called constrained prior. We outline the ways in which NS may be applied and describe the application of NS in three scientific fields in which the algorithm has proved to be useful: cosmology, gravitational-wave astronomy, and materials science. We close by making recommendations for best practice when using NS and by summarizing potential limitations and optimizations of NS.<br />Comment: 20 pages + supplementary information, 5 figures. preprint version; published version at https://www.nature.com/articles/s43586-022-00121-x

Details

ISSN :
26628449
Database :
OpenAIRE
Journal :
Ashton, G, Bernstein, N, Buchner, J, Chen, X, Csányi, G, Feroz, F, Fowlie, A, Griffiths, M, Habeck, M, Handley, W, Higson, E, Hobson, M, Lasenby, A, Parkinson, D B, Pártay, L B, Pitkin, M, Schneider, D, South, L, Speagle, J, Veitch, J, Wacker, P, Wales, D & Yallup, D 2022, ' Nested Sampling for physical scientists ', Nature Reviews Methods Primers, vol. 2, no. 1, 39 . https://doi.org/10.1038/s43586-022-00121-x
Accession number :
edsair.doi.dedup.....d0f6297e206b1e40bc7d17199f8ce0a6
Full Text :
https://doi.org/10.48550/arxiv.2205.15570