Unveiling the Universe with python

Python is widely used in Cosmology, which is the study of the Universe and all forms of energy in it. A large amount of data has been recently obtained through space satellite missions, such as Planck, financed by ESA/NASA. Planck has observed the radiation emitted about 13 billion years ago (the Cosmic Microwave Background, CMB), which gives us information on the content and space-time geometry of the Universe. Many competitive theoretical models have been proposed that aim at describing the evolution of the species contained in the Universe: therefore, cosmologists need a method to identify which theoretical model better fits the data. In order to compare data with theoretical predictions, cosmologists use Bayesian statistics and Monte Carlo simulations. Among the tools developed for the analysis, the package ‘Monte Python’ is publicly available and uses python to perform Monte Carlo simulations: this allows to determine the theoretical model that maximizes the likelihood to obtain the observed data. Such model is now the standard cosmological model and reveals a Universe that is very different from what scientists had ever expected. A Universe in which the atoms we are made of, constitute only 5% of the total energy budget. The rest is the so-called ‘Dark Universe’.

I will illustrate the story of how cosmologists used python to analyse the data of the CMB and unveil the Dark Universe.