Robust sampling for weak lensing and clustering analyses with the Dark Energy Survey

DES Collaboration

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here, we investigate three such samplers to motivate and validate the algorithm and settings used for the Dark Energy Survey (DES) analyses of the first 3 yr (Y3) of data from combined measurements of weak lensing and galaxy clustering. We employ the full DES Year 1 likelihood alongside a much faster approximate likelihood, which enables us to assess the outcomes from each sampler choice and demonstrate the robustness of our full results. We find that the ellipsoidal nested sampling algorithm MULTINEST reports inconsistent estimates of the Bayesian evidence and somewhat narrower parameter credible intervals than the sliced nested sampling implemented in POLYCHORD. We compare the findings from MULTINEST and POLYCHORD with parameter inference from the Metropolis–Hastings algorithm, finding good agreement. We determine that POLYCHORD provides a good balance of speed and robustness for posterior and evidence estimation, and recommend different settings for testing purposes and final chains for analyses with DES Y3 data. Our methodology can readily be reproduced to obtain suitable sampler settings for future surveys.

Original languageEnglish (US)
Pages (from-to)1184-1199
Number of pages16
JournalMonthly Notices of the Royal Astronomical Society
Volume521
Issue number1
DOIs
StatePublished - May 1 2023

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Keywords

  • cosmological parameters
  • cosmology: observations
  • large-scale structure of the Universe
  • methods: statistical

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