Physique statistique

The first aim of these lectures will be to give a brief overview of the physical and dynamical mechanisms which determine Earth’s climate. We will start with the atmospheric radiative transfer and the energy fluxes provided by the fluid dynamics of the atmosphere and the oceans.

Phase transitions take place in many different branches of physics: from soft and hard condensed matter to cosmology and high-energy physics. This course presents the fundamental ideas, concepts and methods that underpin the modern theory of phase transitions. 

Modern physics is characterized by an increasing complexity of systems under investigation, in domains as diverse as condensed matter, astrophysics, biophysics, etc. Due to the growing availability of experimental data, data-driven modelling is emerging as a powerful way to model those systems. The objective of the course is to provide the theoretical concepts and practical tools necessary to understand and to use these approaches.

Can the whole not merely be the sum of its parts? How do collective patterns appear?
Could three molecules of water form ice?
Could higher-level abilities be created from interacting AI agents?

The notion of complexity pertains to systems in which somewhat unexpected properties emerge from the interplay of a sufficiently large number of  entities — be they particles, living cells, artificial neurons, organisms, people, abtract agents... or even a mixture of some (or all!) of these.

Statistical physics has been the first branch of science to try and model in a mathematical manner such systems, focusing especially on the subtle and often elusive passage from the micro/individual level to the macro/collective level. This lecture course explores further how the mindset of statistical physics can provide fertile ground for the analysis and modelling of complexity — including across disciplinary boundaries.