2020/04/30 by Anton Chudaykin, Mikhail M. Ivanov, Oliver H. E. Philcox +1 · 2 citations
Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Algorithm #Astrophysics #Bayesian probability #Computational science #Computer science #Cosmology and Gravitation Theories #Galaxies: Formation, Evolution, Phenomena #Galaxy #Markov chain Monte Carlo #Nonlinear system #Particle physics #Physics #Quantum mechanics #Redshift #Resummation #Spectral density #Statistical physics #astro-ph.CO
paper · pdf · doi:10.1103/physrevd.102.063533
published as Phys. Rev. D 102, 063533 (2020) · v1: 48 pages, 9 figures. v2: 56 pages, 14 figures, minor edits, version to appear in PRD. The code and custom-built BOSS likelihoods are available at https://github.com/Michalychforever/CLASS-PT and https://github.com/Michalychforever/lss_montepython
arxiv created 2020/08/29 · openalex publication_date 2020/09/28 · arxiv updated 2020/10/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present a new open-source code that calculates one-loop power spectra and cross spectra for matter fields and biased tracers in real and redshift space. These spectra incorporate all ingredients required for a direct application to data: nonlinear bias and redshift-space distortions, infrared resummation, counterterms, and the Alcock-Paczynski effect. Our code is based on the Boltzmann solver class and inherits its advantageous properties: user friendliness, ease of modification, high speed, and simple interface with other software. We present detailed descriptions of the theoretical model, the code structure, approximations, and accuracy tests. A typical end-to-end run for one cosmology takes 0.3 seconds, which is sufficient for Markov chain Monte Carlo parameter extraction. As an example, we apply the code to the Baryon Oscillation Spectroscopic Survey (BOSS) data and infer cosmological parameters from the shape of the galaxy power spectrum.