Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium
(2024)
Journal Article
Carnazza, F., Carollo, F., Martius, G., Andergassen, S., Klopotek, M., & Lesanovsky, I. (2024). Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium. Machine Learning: Science and Technology, 5(4), Article 045002. https://doi.org/10.1088/2632-2153/ad7ad7
We develop a machine learning algorithm to infer the emergent stochastic equation governing the evolution of an order parameter of a many-body system. We train our neural network to independently learn the directed force acting on the order parameter... Read More about Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium.