BeyondPlanck III. Commander3

Abstract

We describe the computational infrastructure for end-to-end Bayesian CMB analysis implemented by the BeyondPlanck collaboration. This code is called commander3, and provides a statistically consistent framework for global analysis of CMB and microwave observations, and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs, or to reimplement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, FFT optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BeyondPlanck analysis, and find that a total of 1.5 TB of RAM is required for efficient analysis, and the total cost of a full Gibbs sample is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.

16 Pages, 7 Figures. Part of the BeyondPlanck paper suite

References in corpus (11)

• A full sky, low foreground, high resolution CMB map from WMAP
• BeyondPlanck III. Commander3
• BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data
• BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors
• BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments
• BeyondPlanck X. Bandpass and beam leakage corrections
• BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
• From BeyondPlanck to Cosmoglobe: Preliminary $WMAP$ $Q$-band analysis
• BeyondPlanck XII. Cosmological parameter constraints with end-to-end error propagation
• BeyondPlanck VI. Noise characterization and modelling
• BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation

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• BeyondPlanck III. Commander3
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• Foreground Separation and Constraints on Primordial Gravitational Waves with the PICO Space Mission
• BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data
• BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors
• BeyondPlanck X. Bandpass and beam leakage corrections
• BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
• From BeyondPlanck to Cosmoglobe: Preliminary $WMAP$ $Q$-band analysis
• Cosmoglobe DR1 results. I. Improved Wilkinson Microwave Anisotropy Probe maps through Bayesian end-to-end analysis
• BeyondPlanck VI. Noise characterization and modelling
• Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction
• BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation
• Non-parametric maximum likelihood component separation for CMB polarization data
• BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics
• BeyondPlanck II. CMB map-making through Gibbs sampling
• Statistical estimation of full-sky radio maps from 21cm array visibility data using Gaussian constrained realizations
• Cosmoglobe DR1. III. First full-sky model of polarized synchrotron emission from all WMAP and Planck LFI data
• Cosmoglobe: Towards end-to-end CMB cosmological parameter estimation without likelihood approximations
• LiteBIRD science goals and forecasts: improved full-sky reconstruction of the gravitational lensing potential through the combination of Planck and LiteBIRD data
• Optimal bolometer transfer function deconvolution for CMB experiments through maximum likelihood mapmaking
• SpyDust: an improved and extended implementation for modeling spinning dust radiation
• Implications of scattering for CMB foreground emission modelling
• Supervised Extraction of the Thermal Sunyaev$-$Zel'dovich Effect with a Three-Dimensional Convolutional Neural Network
• The Simons Observatory: Quantifying the impact of beam chromaticity on large-scale B-mode science
• On the computational feasibility of Bayesian end-to-end analysis of LiteBIRD simulations within Cosmoglobe
• B-mode polarization forecasts for GreenPol