Group “Classical and Quantum Dynamical Systems”
Statistical properties of dynamical systems: Probabilistic methods are used to study limit theorems in the case of deterministic and random dynamical systems, in particular the Central Limit Theorem (CLT), the Almost Sure Invariance Principle, large deviations, and the distribution of rare events. The rate of decay of correlations for non-uniformly hyperbolic systems is estimated using new techniques (coupling, renewal). Random systems (by random composition of mappings acting on the same space) and sequential dynamical systems (non-stationary or non-autonomous, where a concatenation of mappings acts on a space) are also studied. We have formulated and developed the theory of extreme values for random and non-autonomous systems, with extensions to networks of coupled mappings.
Fusion plasma physics: We develop reduced fluid and kinetic Hamiltonian models derived from Dirac’s constraint theory to study the fundamental mechanisms of turbulent magnetized plasmas that degrade confinement in tokamak devices. Parasitic instabilities in a hybrid non-Hamiltonian model for the interaction of energetic particles with a thermal plasma are also studied, as well as secondary instabilities following magnetic reconnection. Another part of the research activity concerns the application of stochastic process theory to study the formation of transport barriers in tokamaks.
Biophysics: We focus on fundamental physical processes, in particular resonant electrodynamic forces acting over long distances, which are thought to be responsible for the high efficiency of molecular machinery within living cells and for long-range coherence in biological systems. This activity is pursued both theoretically and experimentally in collaboration with molecular biologists.
Complexity: New methods for measuring the complexity of networks are developed within the framework of Riemannian Information Geometry. Applications to networks of proteomic interactions in cancer cells are currently being developed.
| ASCH | Joachim | Research teacher | +33.4.91.26.95.20 | Contact |
| ASCHBACHER | Walter | Research teacher | +33.4.91.26.95.16 | Contact |
| DAQUIN | Jerome | Research teacher | Contact | |
| EL KETTANI | Perla | Research teacher Unit leader « Systèmes dynamiques classiques et quantiques » | +33.4.91.26.97.93 | Contact |
| FLORIANI | Elena | Research teacher | +33.4.91.26.95.22 | Contact |
| LEBOUAZDA | Yohann | Ph.D. | Contact | |
| LEONCINI | Xavier | Research teacher Team leader « Dynamical Systems: Theory and Applications » | +33.4.91.26.95.38 | Contact |
| PETTINI | Marco | Research teacher | +33.4.91.26.95.49 | Contact |
| ROUVET | Simon | Ph.D. | Contact | |
| VAIENTI | Sandro | Research teacher | +33.4.91.26.95.44 | Contact |
| VITTOT | Michel | Researcher | +33.4.91.26.95.24 | Contact |
Magnetically confined charged particles: From steep density profiles to the breaking of the adiabatic invariant
2025
Experimental detection of long-distance interactions between biomolecules through their diffusion behavior: Numerical study
2025
Catching homologies by geometric entropy
2025
Quantifying Networks Complexity from Information Geometry Viewpoint
2025
Persistent Homology analysis of Phase Transitions
2025
A geometric entropy detecting the Erdös-Rényi phase transition
2025
Physics on the Infinite Canvas, A new tool for popularization and pedagogy
2025 European Physical Society Conference on High Energy Physics (EPS-HEP2025), Jul 2025, Marseille, France. pp.611, (10.22323/1.485.0611)
Pose ensemble graph neural networks to improve docking performances
Chemical Science, 2025, 16 (42), pp.19876-19887. (10.1039/d4sc07875f)
Topology and Phase Transitions: Paradigmatic Evidence
2023
Analysis of bank leverage via dynamical systems and deep neural networks
SIAM Journal on Financial Mathematics, 2023, 14 (2), pp.598-643. (10.1137/21M1412517)