Contributors: Mikhail (Misha) Ivanov, Anton Chudaykin, Oliver Philcox
These are various large-scale structure likelihoods for the MCMC sampler Montepython that were analyzed in the papers
The repo includes:
Note that you need CLASS-PT to evaluate FS and FS+BAO likelihoods. We recommend using the '_marg' likelihoods, which include exact analytic marginalization over Gaussian parameters and significant optimizations.
Update from 11/25/2020: minor typos in the window function treatement have been corrected; the power spectra and covariance matrices are replaced by the new measurements carried out in the project Cosmological constraints from BOSS with analytic covariance matrices