Conservative Constraints on Early Cosmology: an illustration of the Monte Python cosmological parameter inference code

By B. Audren, Julien Lesgourgues, K. Benabed, S. Prunet. 2012

668 citations recorded by the source corpus.

Models for the latest stages of the cosmological evolution rely on a less solid theoretical and observational ground than the description of earlier stages like BBN and recombination. As suggested in a previous work by Vonlanthen et al., it is possible to tweak the analysis of CMB data in such way to avoid making assumptions on the late evolution, and obtain robust constraints on ''early cosmology parameters''. We extend this method in order to marginalise the results over CMB lensing contamination, and present updated results based on recent CMB data. Our constraints on the minimal early cosmology model are weaker than in a standard ΛCDM analysis, but do not conflict with this model. Besides, we obtain conservative bounds on the effective neutrino number and neutrino mass, showing no hints for extra relativistic degrees of freedom, and proving in a robust way that neutrinos experienced their non-relativistic transition after the time of photon decoupling. This analysis is also an occasion to describe the main features of the new parameter inference code MONTE PYTHON, that we release together with this paper. MONTE PYTHON is a user-friendly alternative to other public codes like COSMOMC, interfaced with the Boltzmann code CLASS.

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/78d489520df0ef327e8130d3de5d8352fa86342d

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Citations in the corpus

Nonlocal gravity. Conceptual aspects and cosmological predictions (2017, methodology): “We have implemented the cosmological equations in CLASS [116], and constrained the nonlocal model with observations using the Markov Chain Monte Carlo (MCMC) code Montepython [117].”
New observational constraints on f(R) gravity from cosmic chronometers (2016, methodology): “publicly available code CLASS [90] in the interface with the public Monte Carlo code Monte Python [91].”
H0LiCOW - V. New COSMOGRAIL time delays of HE 0435-1223: H0 to 3.8 per cent precision from strong lensing in a flat ΛCDM model (2016, methodology): “Temperature power spectra were computed using the Cosmic Linear Anisotropy Solving System Boltzman code (CLASS; Blas et al. 2011; Lesgourgues & Tram 2014) and MCMC chains were generated with the MontePython sampler (Audren et al. 2013).”
Reducing the H0 and σ8 tensions with dark matter-neutrino interactions. (2017, methodology): “The constraints are derived using the Markov Chain Monte Carlo tool Monte Python [27], interfaced with our version of CLASS, that fully supports the Planck data release 2015 Likelihood Code [24].”
Implications of an extended dark energy cosmology with massive neutrinos for cosmological tensions (2018, methodology): “[47] Benjamin Audren, Julien Lesgourgues, Karim Benabed, and Simon Prunet, “Conservative Constraints on Early Cosmology: an illustration of the Monte Python cosmological parameter inference code,” J. Cosmol.”
The Ups and Downs of Early Dark Energy solutions to the Hubble tension: A review of models, hints and constraints circa 2023 (2023, background): “[165] Benjamin Audren, Julien Lesgourgues, Karim Benabed, and Simon Prunet, “Conservative Constraints on Early Cosmology: an illustration of the Monte Python cosmological parameter inference code,” JCAP 02, 001 (2013), arXiv:1210.”