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Informal quantum seminar: Natalia Chepiga (Delft University of Technology)

Infinite randomness criticality and localization of the floating phase in arrays of Rydberg atoms trapped with non-perfect tweezers Natalia Chepiga (Delft University of Technology)   The success of Rydberg-based platforms originates from the precise control of lattice geometries provided by optical tweezers, which allows access to a wide range of synthetic quantum phases. Experiments on […]

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Séminaire du LPTMS : Leticia Cugliandolo (LPTHE, Sorbonne Université, Paris)

Statistical Physics out of equilibrium Leticia Cugliandolo  (LPTHE, Sorbonne Université, Paris)   Equilibrium statistical physics provides a bridge between microscopic dynamics and macroscopic behavior. It explains the emergence of thermodynamic concepts such as temperature and pressure, and accounts for collective phenomena like phase transitions. By contrast, a comparable understanding of systems out of equilibrium remains

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MLP@P seminars : Gianluca Manzan (LISN)

From Hopfield Inference to Federated Learning: challenges and solutions in Teacher–Student models Gianluca Manzan LISN, Paris Saclay University Seminar of the Series MLP@P (Machine Learning Physics @ Plateau), joint with LISN and IPhT. Where: LISN, bat 660 salle 2014 (2° étage) In this work, we investigate inference in neural networks through the teacher–student framework, which

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Physics-Biology Interface seminar: Marc Lagoin

Thermodynamics of Nonequilibrium Systems, from Maxwell Demons to Active Microswimmers in Confined Flows Marc Lagoin (LOMA, U. Bordeaux) Many physical systems can be described using a few coarse variables, ignoring most microscopic details. This idea, formalized in Langevin’s theory of Brownian motion [3], allows us to understand how fluctuations and dissipation produce predictable behaviours even

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MLP@P seminars : Jerome Garnier-Brun (Bocconi)

Uncovering Structure: How Neural Networks Learn and Generalize from Tree-based Data Jerome Garnier-Brun Bocconi University, Milan Seminar of the Series MLP@P (Machine Learning Physics @ Plateau), joint with LISN and IPhT. Where: LPTMS, Salle des Séminaires (1° étage) Statistical-physics approaches have provided key insights into the functioning of neural networks, yet most analyses assume high-dimensional

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Physics-Biology Interface seminar: Valerio Sorichetti

Charged for attraction: How biomolecular condensates pull chromosomes together Valerio Sorichetti (IST Austria) The coacervation of charged polymers is an important driver for the formation of biomolecular condensates. Recent experiments suggest that this mechanism also controls the clustering of eukaryotic chromosomes during the late stages of cell division [1,2]. In this process, inter-chromosome attraction is

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