MontePython 3: boosted MCMC sampler and other features

Thejs Brinckmann, Julien Lesgourgues
4/19/2018
astro-ph.COastro-ph.IM

Official code: brinckmann/montepython_public (103 stars, MIT, last commit 2024-06-20).

Abstract

MontePython is a parameter inference package for cosmology. We present the latest development of the code over the past couple of years. We explain, in particular, two new ingredients both contributing to improve the performance of Metropolis-Hastings sampling: an adaptation algorithm for the jumping factor, and a calculation of the inverse Fisher matrix, which can be used as a proposal density. We present several examples to show that these features speed up convergence and can save many hundreds of CPU-hours in the case of difficult runs, with a poor prior knowledge of the covariance matrix. We also summarise all the functionalities of MontePython in the current release, including new likelihoods and plotting options.

View on arXivView PDF

Code Implementations(1)

brinckmann/montepython_publicOfficial100%
MIT

Public repository for the Monte Python Code

10393C, ShellApr 19, 20182 years agoMIT

Similar Papers

COSMOPOWER: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys

80% match1 repo832021

Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation

79% match2 repos1722021

CosmoSIS: modular cosmological parameter estimation

78% match2014

CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulators

78% match1 repo502023

Lossless, Scalable Implicit Likelihood Inference for Cosmological Fields

78% match1 repo92021

Cobaya: Code for Bayesian Analysis of hierarchical physical models

78% match1 repo1822020

Cite this paper

@article{brinckmann2018montepython,
  title  = {MontePython 3: boosted MCMC sampler and other features},
  author = {Thejs Brinckmann and Julien Lesgourgues},
  year   = {2018},
  eprint = {1804.07261},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1804.07261}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/1804.07261.svg)](https://codeofpaper.com/paper/1804.07261)

Discussion