arXiv Open Access 2022

SuperNest: accelerated nested sampling applied to astrophysics and cosmology

Aleksandr Petrosyan William James Handley

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Abstrak

We present a method for improving the performance of nested sampling as well as its accuracy. Building on previous work by Chen et al., we show that posterior repartitioning may be used to reduce the amount of time nested sampling spends in compressing from prior to posterior if a suitable ``proposal'' distribution is supplied. We showcase this on a cosmological example with a Gaussian posterior, and release the code as an LGPL licensed, extensible Python package https://gitlab.com/a-p-petrosyan/sspr.

Topik & Kata Kunci

physics.comp-ph astro-ph.CO

Penulis (2)

Aleksandr Petrosyan

William James Handley

Format Sitasi

APA MLA BibTeX

Petrosyan, A., Handley, W.J. (2022). SuperNest: accelerated nested sampling applied to astrophysics and cosmology. https://arxiv.org/abs/2212.01760

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓