2026 - 2027
M2 SUBA Course “Quantum Field Theory” – September 1 to September 23, 2026 – Contact : Aldo Deandrea
(intensive course with 6 hours per week)
Quantum Field Theory:
Review: Lagrangian formulation; action symmetries and Noether’s theorem; Hamiltonian formulation
Klein-Gordon, Proca, and Dirac equations; Quantization: bosons and fermions; scattering matrix; LSZ formula; Feynman propagator; quantum electrodynamics.
Courses in the SDM (Materials Science) master's program are generally open to doctoral students Contact : contact.sciencesdelamatiere@ens-lyon.fr
https://www.ens-lyon.fr/MasterSDM/fr/master/organisation-du-master/m2-physics
Description:
Quantum chromodynamics (QCD) is the gauge theory of the strong interaction, which binds quarks together within hadrons (protons, neutrons, mesons, etc.). This 12-hour course introduces and explores the theoretical foundations, loop calculation techniques, and phenomenological applications of QCD, ranging from Lie group concepts to parton distribution functions used in high-energy collision physics.
Prerequisite: having taken a course on quantum field theory
First Class: Tuesday,22/09, Darwin C salle Caullery (RDC) à 14h
Master 2 Course: “Complex Systems” Track
Complex Networks
Complex graphs and networks can be used to describe a wide variety of systems of interacting entities, ranging from genetics to social networks to transportation systems. This course offers an introduction to these objects, covering their static characterization (generation of random networks with properties similar to those of real networks, centrality metrics, the “small-world” effect, ...) to the study of the dynamic processes occurring within them (rules of microscopic evolution, mean-field approaches, percolation, transition matrices, ...)
The session schedule, times, and locations (at the Monod campus of ÉNS-Lyon) are available on the course page:
cazabetremy.fr/Teaching/CN/ComplexNetworks.html
For more information
This course covers the description and modeling of self-organization phenomena in physical, chemical, biological, ecological, and social systems. Due to its negentropic nature, self-organization occurs in non-equilibrium systems that consume energy. Several theoretical and experimental tools for analyzing the temporal evolution of these systems will be presented, in particular reaction-diffusion models, hydrodynamic models, and models of self-propelled agents. These will lead to a discussion of self-organization phenomena such as the formation of propagation fronts and aggregation patterns. These concepts will be illustrated through seminars led by the speakers and the students themselves (journal club), drawing on research in the broad field of active matter—ranging from the collective motion of self-propelled particles to that of bacteria and cells, and extending to herds of animals or groups of Homo sapiens.
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This Master 2 course introduces machine learning and deep learning as applied to real-world physics problems. It combines theory (9 hours) and hands-on practice (13.5 hours of lab work) focusing on classification, clustering, and neural networks.
Schedule: Thursday afternoons, from November 12, 2026, to January 14, 2027
16h de cours magistraux, 8h de TD, en amphi Anne L'Huillier, les mardis après-midi (13h30-15h30 puis 15h45-17h45) du 5 janvier au 9 Février 2027