Bayesian evidence for the tensor-to-scalar ratio r and neutrino masses m_nu: Effects of uniform vs logarithmic priors (supplementary inference products)

These are the nested sampling inference products and input files that were used to compute results for arXiv:2102.11511.

Example plotting scripts (as .ipynb or as .html files) and figures from the papers are included to demonstrate usage.

Filename conventions:

• lcdm: Concordance cosmological model called \(\Lambda\mathrm{CDM}\) (without extension this assumes \(r=0\) and a single massive neutrino with mass \(m_\nu=0.06\,\mathrm{eV}\)).
• _r: \(\Lambda\mathrm{CDM}\) with variable tensor-to-scalar ratio \(r\).
• _nu: \(\Lambda\mathrm{CDM}\) with three massive neutrinos, sampling over the lightest neutrino mass \(m_\mathrm{light}\) and the squared mass splittings \(\delta m^2\) and \(\Delta m^2\).
• mcmc: Cobaya's Markov Chain Monte Carlo Metropolis sampler.
  https://github.com/CobayaSampler/cobaya/releases/tag/v3.0.2
• pc#d###: PolyChord run with #d repeats per parameter block (where d is the number of parameters in that block) and with ### live points.
  https://github.com/PolyChord/PolyChordLite/releases/tag/1.17.1
• _class: theory code CLASS.
  https://github.com/lesgourg/class_public/releases/tag/v2.9.4
• _p18_TTTEEElowTE_SZ: Planck 2018 TT,TE,EE+lowl+lowE data.
  https://pla.esac.esa.int/pla/#cosmology
• _nufit50: NuFIT 5.0 data.
  http://www.nu-fit.org/?q=node/228
• _NH and _IH: normal and inverted neutrino hierarchy.
• _logr##: logarithmic sampling of tensor-to-scalar ratio \(r\) with lower log bound given .by log10r=-##.
• _mdD: sampling over the lightest neutrino mass \(m_\mathrm{light}\) and the squared mass splittings \(\delta m^2\) and \(\Delta m^2\) (medium and heavy neutrino mass are derived parameters) with mass units in eV.
• _logmdD##: logarithmic (instead of uniform) sampling of the lightest neutrino mass \(m_\mathrm{light}\) with lower log bound given by log10mlight=-##.

Datasets used for the nested sampling runs:

• Planck 2018 TT,TE,EE+lowl+lowE: https://pla.esac.esa.int/pla/#cosmology
• NuFIT 5.0: http://www.nu-fit.org/?q=node/228

Software used:

• Cobaya: https://github.com/CobayaSampler/cobaya/releases/tag/v3.0.2
• CLASS: https://github.com/lesgourg/class_public/releases/tag/v2.9.4
• PolyChord: https://github.com/PolyChord/PolyChordLite/releases/tag/1.17.1
• Anesthetic: https://github.com/lukashergt/anesthetic/tree/138299739544e888cc318746be087c898f1aff15

For more details see Cobaya's (https://cobaya.readthedocs.io/en/latest/index.html) and Anesthetic's (https://anesthetic.readthedocs.io/en/latest/) documentation.