104 citations · 324 across the 14 of their papers we have counts for
6 papers · 1 filter
Benchmark control problems in nonequilibrium statistical mechanics
Stephen Whitelam, Corneel Casert, Megan Engel +1
We present a set of computer codes designed to test methods for optimizing time-dependent control protocols in fluctuating nonequilibrium systems. Each problem consists of a stocha…
Nonlinear thermodynamic computing out of equilibrium
Stephen Whitelam, Corneel Casert
We present the design for a thermodynamic computer that can perform arbitrary nonlinear calculations in or out of equilibrium. Simple thermodynamic circuits, fluctuating degrees of…
Learning protocols for the fast and efficient control of active matter
Corneel Casert, Stephen Whitelam
We show that it is possible to learn protocols that effect fast and efficient state-to-state transformations in simulation models of active particles. By encoding the protocol in t…
Learning stochastic dynamics and predicting emergent behavior using transformers
Corneel Casert, Isaac Tamblyn, Stephen Whitelam
We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of th…
Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz
Corneel Casert, Tom Vieijra, Stephen Whitelam +1
We use a neural network ansatz originally designed for the variational optimization of quantum systems to study dynamical large deviations in classical ones. We obtain the scaled c…
Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system
C. Casert, T. Vieijra, J. Nys +1
Still under debate is the question of whether machine learning is capable of going beyond black-box modeling for complex physical systems. We investigate the generalizing and inter…