Physique numérique

Computational physics plays a central role in all fields of physics, from classical statistical physics, soft matter problems, and hard-condensed matter. Our goal is to cover the basic concepts underlying computer simulations in classical and quantum problems, and connect these ideas to relevant and contemporary research topics in various fields of physics. In the TD’s you will also learn how to set, perform and analyse the results of simple computer simulations by yourself, covering a wide range of topics. We will use Python, but no previous knowledge of this programming language is needed.

The goal of this course is to introduce the main concepts and challenges of quantum computing, a new set of technologies and techniques that promise to solve hard computational problems.

The numerical resolution of fluid dynamics equations is becoming increasingly important in many aspects of scientific research. In this course, we will develop and analyze the methods used to solve the partial differential equations relevant to fluid dynamics (elliptic, parabolic and hyperbolic).

The development of animals, starting from a single cell to produce a fully formed organism, is a fascinating process. Its study is currently advancing at a rapid pace thanks to combined experimental and theoretical progress, yet many fundamental questions remain to be answered.

This course will address the fundamental theoretical concepts underlying the self-organization of multicellular systems, from gene regulation to the mechanics of active biological materials. The course will be based on various concepts from theoretical physics: dynamical systems, soft and active matter, the mechanics of continuous media, numerical modeling, etc.

Que ce soit pour la modélisation, l’acquisition ou l’analyse de donnée, l’informatique est devenu un outil indispensable pour tout scientifique. L’objectif principal de ce cours est d’apprendre à utiliser les techniques permettant de manipuler les données. 

Statistical machine learning is a growing discipline at the intersection of computer science and applied mathematics (probability / statistics, optimization, etc.) and which increasingly plays an important role in many other scientific disciplines.