Teaching Advanced computational physics (english)The course covers dense/sparse linear algebra, variational methods in quantum mechanics, and Monte Carlo techniques. Students implement algorithms for complex physical problems. Combines theory with coding exercises. Prepares for research in computational physics and related fields.Quantum physics IV (english)Introduction to the path integral formulation of quantum mechanics. Derivation of the perturbation expansion of Green’s functions in terms of Feynman diagrams. Several applications will be presented, including non-perturbative effects, such as tunneling and instantons.Computational quantum physics (english)The numerical simulation of quantum systems plays a central role in modern physics. This course gives an introduction to key simulation approaches, through lectures and practical programming exercises. Simulation methods based both on classical and quantum computers will be presented.Lecture series on scientific machine learning (english)Machine learning is a data analysis and computational tool that in the last two decades brought groundbreaking progress into many modern technologies. What is more, machine learning is becoming an indispensable tool enabling progress in many scientific disciplines where knowledge is deduced from data. This course will present some recent works in this direction. In the first part of the Introduction to quantum science and technology (english) Introduction (2 weeks): Overview of the frontiers of quantum science, technology and applications. Introduction to qubits, quantum states, measurements, evolution. Axiomatic formulation. Illustration with two level systems, Bloch sphere, Spin, its manipulation in magnetic fields. Heisenberg and spin Hamiltonians, eleme
