Conservative constraints on early cosmology with MONTE PYTHON

By B. Audren, Julien Lesgourgues, K. Benabed, S. Prunet. 2013

198 citations recorded by the source corpus.

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/1626fbb3046b95fbffab858696846592d39268f0

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Citations in the corpus

KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear (2019, methodology): “3 https://github.com/sjoudaki/CosmoLSS the KV450 constraints from CosmoLSS, CosmoSIS, and Monte Python (Audren et al. 2013) are in excellent agreement.”
Nonlocal gravity. Conceptual aspects and cosmological predictions (2017, methodology): “expand on these results. 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]. The details on the implementation of the RR model in CLASS have been discussed in appendix A ”
Planck 2015 results. XI. CMB power spectra, likelihoods, and robustness of parameters (2015, methodology): “We further acknowledge the use of the CLASS Boltzmann code (Lesgourgues 2011) and the Monte Python package (Audren et al. 2013) in earlier stages of this work.”
KiDS-450: The tomographic weak lensing power spectrum and constraints on cosmological parameters (2017, methodology): “Conveniently, its PYTHON-wrapper PYMULTINEST (Buchner et al. 2014) is included in the framework of the cosmological likelihood sampling package MONTE PYTHON10 (Audren et al. 2013) with which we derive all cosmology-related results in this analysis.”
H0LiCOW – XIII. A 2.4 per cent measurement of H0 from lensed quasars: 5.3σ tension between early- and late-Universe probes (2019, unknown): “1 MCMC sampling package (Audren et al. 2013; Brinckmann & Lesgourgues 2018), its associated CLASS code (Lesgourgues 2011), and the JLA and Pantheon SNe samples implemented within MONTEPYTHON, to combine with our lensing distance measurements and sample cosmological parameters.”
Cobaya: code for Bayesian analysis of hierarchical physical models (2020, result): “In that regard, it compares to CosmoMC [2, 12], and later MontePython [13, 14] and CosmoSIS [15], amongst others.”
Exploring cosmic origins with CORE: Inflation (2016, methodology): “The first combines the Einstein-Boltzmann code CLASS [226] and the sampling code MontePython [227], and the second relies on CAMB [175] combined with the sampler CosmoMC [179].”
The trouble with H0 (2016, methodology): “We use the public Boltzmann code CLASS [38, 39] and the Monte Carlo public code Monte Python [40] to analyse the CMB data sets discussed in section 2 when for the selected model there are no posterior samples officially provided by the Planck collaboration.”
The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations with Lyα Forests (2020, methodology): “Assuming flat priors on the BAO parameters, the χ2 scan can be used to construct a proxy for the marginalized posterior distribution of a and â , allowing us to use the χ2 scans in popular packages like CosmoMC (Lewis & Bridle 2002) or MontePython (Audren et al. 2013), where different cosmological ”