Nested Sampling for physical scientists

Greg  Ashton; Noam Bernstein; Johannes  Buchner; Xi Chen; Gábor Csányi; Farhan Feroz; Andrew Fowlie; Matthew Griffiths; Michael Habeck; Will Handley; Edward Higson; Michael Hobson; Anthony Lasenby; David B. Parkinson; Livia B.  Pártay; Matthew Pitkin; Doris Schneider; Leah South; Joshua Speagle; John Veitch; Philipp Wacker; David  Wales; David Yallup

doi:10.1038/s43586-022-00121-x

Nested Sampling for physical scientists

Greg Ashton, Noam Bernstein, Johannes Buchner, Xi Chen, Gábor Csányi, Farhan Feroz, Andrew Fowlie, Matthew Griffiths, Michael Habeck, Will Handley, Edward Higson, Michael Hobson, Anthony Lasenby, David B. Parkinson, Livia B. Pártay, Matthew Pitkin, Doris Schneider, Leah South, Joshua Speagle, John VeitchPhilipp Wacker, David Wales, David Yallup

University of Cambridge

Research output: Contribution to journal › Article › peer-review

90 Citations (SciVal)

199 Downloads (Pure)

Abstract

This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior. Different ways of applying nested sampling are outlined, with detailed examples from three scientific fields: cosmology, gravitational-wave astronomy and materials science. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.

Original language	English
Article number	39
Journal	Nature Reviews Methods Primers
Volume	2
Issue number	1
DOIs	https://doi.org/10.1038/s43586-022-00121-x
Publication status	Published - 26 May 2022

Bibliographical note

Funding Information:
The authors thank J. Skilling for his wonderful algorithm. The success of nested sampling may be that simple beats clever; but the beauty of nested sampling is that it is both simple and clever. They thank K. Barbary for discussions. A.F. was supported by a National Natural Science Foundation of China (NSFC) Research Fund for International Young Scientists (grant 11950410509). L.B.P. acknowledges support from the Engineering and Physical Sciences Research Council (EPSRC) through an Early Career Fellowship (EP/T000163/1). M. Habeck acknowledges support from the Carl Zeiss Foundation. N.B. was funded by the US Naval Research Laboratory’s base 6.1 research program, and CPU time from the US Department of Defence (DoD) High Performance Computing Modernization Program Office (HPCMPO) at the Air Force Research Laboratory (AFRL) and Army Research Laboratory (ARL) DoD Supercomputing Research Centers (DSRCs). M.P. acknowledges support from the Science and Technology Facilities Council (STFC) (ST/V001213/1 and ST/V005707/1). W.H. was supported by a Royal Society University Research Fellowship.

Publisher Copyright:
© 2022, Springer Nature Limited.

ASJC Scopus subject areas

General Medicine
General Biochemistry,Genetics and Molecular Biology

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2205.15570.pdfAccepted author manuscript, 9.07 MB

https://arxiv.org/pdf/2205.15570.pdf

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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., ... Yallup, D. (2022). Nested Sampling for physical scientists. Nature Reviews Methods Primers, 2(1), Article 39 . https://doi.org/10.1038/s43586-022-00121-x

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, DB, Pártay, LB, 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

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note = "Funding Information: The authors thank J. Skilling for his wonderful algorithm. The success of nested sampling may be that simple beats clever; but the beauty of nested sampling is that it is both simple and clever. They thank K. Barbary for discussions. A.F. was supported by a National Natural Science Foundation of China (NSFC) Research Fund for International Young Scientists (grant 11950410509). L.B.P. acknowledges support from the Engineering and Physical Sciences Research Council (EPSRC) through an Early Career Fellowship (EP/T000163/1). M. Habeck acknowledges support from the Carl Zeiss Foundation. N.B. was funded by the US Naval Research Laboratory{\textquoteright}s base 6.1 research program, and CPU time from the US Department of Defence (DoD) High Performance Computing Modernization Program Office (HPCMPO) at the Air Force Research Laboratory (AFRL) and Army Research Laboratory (ARL) DoD Supercomputing Research Centers (DSRCs). M.P. acknowledges support from the Science and Technology Facilities Council (STFC) (ST/V001213/1 and ST/V005707/1). W.H. was supported by a Royal Society University Research Fellowship. Publisher Copyright: {\textcopyright} 2022, Springer Nature Limited.",

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AU - Griffiths, Matthew

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Nested Sampling for physical scientists

Abstract

Bibliographical note

ASJC Scopus subject areas

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