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Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations (2024)
Journal Article

We present a framework to integrate tensor network (TN) methods with reinforcement learning (RL) for solving dynamical optimization tasks. We consider the RL actor-critic method, a model-free approach for solving RL problems, and introduce TNs as the... Read More about Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations.

Using (1+1)D quantum cellular automata for exploring collective effects in large-scale quantum neural networks (2023)
Journal Article

Central to the field of quantum machine learning is the design of quantum perceptrons and neural network architectures. A key question in this regard is the impact of quantum effects on the way such models process information. Here, we establish a co... Read More about Using (1+1)D quantum cellular automata for exploring collective effects in large-scale quantum neural networks.

Nonequilibrium Phase Transitions in (1+1)-Dimensional Quantum Cellular Automata with Controllable Quantum Correlations (2020)
Journal Article

Motivated by recent progress in the experimental development of quantum simulators based on Rydberg atoms, we introduce and investigate the dynamics of a class of (1+1)-dimensional quantum cellular automata. These non-equilibrium many-body models, wh... Read More about Nonequilibrium Phase Transitions in (1+1)-Dimensional Quantum Cellular Automata with Controllable Quantum Correlations.