English

BayesEoR: Bayesian 21-cm Power Spectrum Estimation from Interferometric Visibilities

Instrumentation and Methods for Astrophysics 2025-01-23 v1 Cosmology and Nongalactic Astrophysics

Abstract

BayesEoR is a GPU-accelerated, MPI-compatible Python package for estimating the power spectrum of redshifted 21-cm emission from interferometric observations of the Epoch of Reionization (EoR). Utilizing a Bayesian framework, BayesEoR jointly fits for the 21-cm EoR power spectrum and a "foreground" model, referring to bright, contaminating emission between us and the cosmological signal, and forward models the instrument with which these signals are observed. To perform the sampling, we use MultiNest [arXiv:1402.0004], which calculates the Bayesian evidence as part of the analysis. Thus, BayesEoR can also be used as a tool for model selection [see e.g. arXiv:1701.03384].

Keywords

Cite

@article{arxiv.2501.12928,
  title  = {BayesEoR: Bayesian 21-cm Power Spectrum Estimation from Interferometric Visibilities},
  author = {Peter H. Sims and Jacob Burba and Jonathan C. Pober},
  journal= {arXiv preprint arXiv:2501.12928},
  year   = {2025}
}
R2 v1 2026-06-28T21:13:40.943Z