38 citations · 72 across the 8 of their papers we have counts for
9 papers
Multiscale Entropies as Order Parameters for Nonequilibrium Phase Transitions
Gerhard Jung, Misaki Ozawa
We develop a multiscale entropy framework based on the wavelet conditional renormalization group that decomposes the total Shannon entropy into contributions from different spatial…
Collective adaptation to time-dependent targets for active Brownian particles
Gerhard Jung, Eric Bertin
We consider a minimal model of active agents which collectively learn to reach a target macroscopic state via a decentralized adaptation process. Agents are modeled as active Brown…
Theory of collective learning in populations of adaptive agents
Gerhard Jung, Johann Asnacios, Misaki Ozawa +2
We investigate homogeneous populations of smart active agents that exchange information with their neighbors to perform a decentralized learning process aimed at achieving a prescr…
Entropy of Liquids and Glasses from Recurring Structural Patterns
Nina Javerzat, Gerhard Jung, Jorge Kurchan +1
We compute the low-temperature configurational entropy of a two-dimensional supercooled liquid. Our method, based on a higher-dimensional version of the Grassberger--Procaccia algo…
Numerical investigation of the equilibrium Kauzmann transition in a two-dimensional atomistic glass
Gerhard Jung, Misaki Ozawa, Giulio Biroli +1
Dense liquids gradually transform into non-equilibrium amorphous solids as they pass through the experimental glass transition. Experimentally, ergodicity is lost because measureme…
Kinetic theory of decentralized learning for smart active matter
Gerhard Jung, Misaki Ozawa, Eric Bertin
Smart active matter has the ability to control its motion guided by individual policies to achieve collective goals. We introduce a theoretical framework to study a decentralized l…
Normalizing flows as an enhanced sampling method for atomistic supercooled liquids
Gerhard Jung, Giulio Biroli, Ludovic Berthier
Normalizing flows can transform a simple prior probability distribution into a more complex target distribution. Here, we evaluate the ability and efficiency of generative machine…
Roadmap on machine learning glassy dynamics
Gerhard Jung, Rinske M. Alkemade, Victor Bapst +10
Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge when studying the glass transition. The absence…
Dynamic heterogeneity at the experimental glass transition predicted by transferable machine learning
Gerhard Jung, Giulio Biroli, Ludovic Berthier
We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic…