polychord: next-generation nested sampling

By Will Handley, M. Hobson, Anthony N. Lasenby. 2015

396 citations recorded by the source corpus.

PolyChord is a novel nested sampling algorithm tailored for high-dimensional parameter spaces. This paper coincides with the release of PolyChord v1.3, and provides an extensive account of the algorithm. PolyChord utilises slice sampling at each iteration to sample within the hard likelihood constraint of nested sampling. It can identify and evolve separate modes of a posterior semi-independently, and is parallelised using openMPI. It is capable of exploiting a hierarchy of parameter speeds such as those present in CosmoMC and CAMB, and is now in use in the CosmoChord and ModeChord codes. PolyChord is available for download at: this http URL

Subfields: Astronomy and Astrophysics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/6dec3e400c37ae3e4be434484c5f3cca4aebb0a0

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Citations in the corpus

The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations with Lyα Forests (2020, methodology): “This analysis assumed flat priors for all nuisance parameters and used the nested sampler Polychord (Handley et al. 2015a, 2015b).”
Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue (2020, background): “In addition to the changes described below, Bilby now also supports the kombine (Farr & Farr 2015), ptmcmc (Ellis & van Haasteren 2017), PolyChord (Handley et al. 2015a,b), and UltraNest (Buchner 2016, 2019) samplers.”
Exploring cosmic origins with CORE: Inflation (2016, methodology): “We compute posteriors (conditioned on N) using the PolyChord nested sampler [257, 258], also varying the cosmological and any nuisance parameters.”
Cobaya: code for Bayesian analysis of hierarchical physical models (2020, methodology): “PolyChord [3, 4] is a nested sampling [38] algorithm that utilizes slice sampling [39] for sampling within iso-likelihood contours.”
Updated results on neutrino mass and mass hierarchy from cosmology with Planck 2018 likelihoods (2019, methodology): “We also calculate Bayesian evidences for the purpose of Bayesian model comparison between the NH and IH cases in the above cosmological models using the publicly available package CosmoChord [76], an extension to CosmoMC using PolyChord [77, 78] for nested sam-”
Equation of state sensitivities when inferring neutron star and dense matter properties (2018, methodology): “In order to compare different methods of constraining the EOS and the effect the parametrization has on these constraints we 5Note the typo in equation (A13) in Handley et al. (2015), where x1/(n−i+1)i should be (1 − x1/(n−i+1)i ). explore multiple scenarios of mass–radius posterior distributions.”
First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters (2018, methodology): “To evaluate consistency between our primary re- sult and BAO, we compute the evidence using PolyChord (Handley et al. 2015a,b), and compute the evidence ratio (R) defined in Eq.”
2020 global reassessment of the neutrino oscillation picture (2020, methodology): “[82] W.”