Course leaders: Rémi Monasson
This course provides an introduction to the concepts and methods of Statistical Physics, whose aim is to deduce the macroscopic properties of a physical system from the microscopic laws governing the behavior of its constituents.
Statistical Physics has a wide range of fundamental and applied application fields. Without it, the distinction between a metal and an insulator, phase transition phenomena, the functioning of a transistor, the stability of stars, superconductivity or superfluidity, the greenhouse effect or the origins of the Universe would remain incomprehensible.
Ideas and methods stemming from Statistical Physics also have numerous applications in fields outside physics itself, such as combinatorial optimization or network modeling (neural networks, social networks, the Internet, etc.). The modeling of road traffic, the spread of epidemics, the functioning of financial markets and certain economic phenomenon have recently benefited from the contributions of this discipline.
Statistical Physics is a tool and a set of concepts that are indispensable to all physicists, and engineers, but also to the general culture of an future polytechnic executive.
There are no prerequisites, but the study of the 7th chapter of the PHY430 (PHY_41030_EP) course on identical particles in quantum mechanics is strongly recommended.
Course language: French
- Teaching coordinator: Behnia Kamran
- Teaching coordinator: Goerbig Mark Oliver
- Teaching coordinator: Grebenkov Denis
- Teaching coordinator: Monasson Rémi
- Teaching coordinator: Schehr Grégory
- Teaching coordinator: Serban Didina
- Teaching coordinator: Van Rees Balt
- Teaching coordinator: Voituriez Raphaël