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05/17/2023
How to train your demon to do fast information erasure without heat production
Time-dependent protocols that perform irreversible logical operations, s...
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11/20/2022
Demon in the machine: learning to extract work and absorb entropy from fluctuating nanosystems
We use Monte Carlo and genetic algorithms to train neural-network feedba...
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05/16/2022
Training neural networks using Metropolis Monte Carlo and an adaptive variant
We examine the zero-temperature Metropolis Monte Carlo algorithm as a to...
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03/10/2022
Cellular automata can classify data by inducing trajectory phase coexistence
We show that cellular automata can classify data by inducing a form of d...
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02/17/2022
Learning stochastic dynamics and predicting emergent behavior using transformers
We show that a neural network originally designed for language processin...
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12/22/2020
Neuroevolutionary learning of particles and protocols for self-assembly
Within simulations of molecules deposited on a surface we show that neur...
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11/17/2020
Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz
We use a neural network ansatz originally designed for the variational o...
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08/15/2020
Correspondence between neuroevolution and gradient descent
We show analytically that training a neural network by stochastic mutati...
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12/18/2019
Learning to grow: control of materials self-assembly using evolutionary reinforcement learning
We show that neural networks trained by evolutionary reinforcement learn...
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09/02/2019
Evolutionary reinforcement learning of dynamical large deviations
We show how to calculate dynamical large deviations using evolutionary r...
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03/20/2019
Optimizing thermodynamic trajectories using evolutionary reinforcement learning
Using a model heat engine we show that neural network-based reinforcemen...
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09/07/2018