Here you can download my latest presentation at the Cosmology School at the Canary Islands on Bayesian estimation of cosmological parameters with CosmoMC and MontePython, and here is a tutorial to get started with the cosmological code MontePython using your own laptop.

BOSS has presented their final galaxy clustering results! To celebrate it, I have made an animation representing thin redshift slices of the BOSS galaxy density distribution (smoothed with a Gaussian angular kernel of 1 degree to make it reminiscent of CMB maps). See it here.

CosmoMC tutorial from the 1st Mexican AstroCosmoStatistics School on Bayesian Inference for Cosmology:

CosmoMC patch (for Oct and Dec 2013 versions, built-in in current versions) to incorporate the Anderson et al. (2014) measurement of the anisotropic reconstructed BAO feature for both CMASS-DR11 and LOWZ-DR11 galaxy samples

CosmoMC chains used in the analysis of the correlation function of CMASS-DR12 and LOWZ-DR12 from the Baryon Oscillation Spectroscopic Survey (Cuesta et al. 2016, arXiv:1509.06371) click here. Note that this is a SDSS product, so if you use it, remember to include the proper acknowledgements

Slides from the course "Introduction to CosmoMC" held at Universidad de Granada, March 2016
Part I: Motivation & Basic concepts
Part II: Installation and Execution
Part III: Analysis - GetDist & GetDist GUI

Note: CosmoMC (code by Lewis and Bridle 2002) is a Markov Chain MonteCarlo code to sample a cosmological parameter space. It is available at the website

Last updated July 2022

"The important thing is not to stop questioning. Curiosity has its own reason for existence.
One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality.
It is enough if one tries merely to comprehend a little of this mystery each day." -- Albert Einstein