Reinforcement Learning to Harness Approximation Errors for Long-Time Quantum Simulation

arXiv:2608.20139 · quant-ph, cond-mat.dis-nn, cond-mat.stat-mech, cond-mat.str-el · Submitted 2026-08-20 · Read on arXiv

quant-ph, cond-mat.dis-nn, cond-mat.stat-mech, cond-mat.str-el

Submitted: 2026-08-20

Updated: 2026-10-08

Terminology

• Reinforcement Learning — 31× in this paper · explained in 4 episodes
• Actor — 29× in this paper · explained in 3 episodes
• Generalization — 29× in this paper · explained in 13 episodes
• Robustness — 15× in this paper · explained in 5 episodes
• Deep Reinforcement Learning — 11× in this paper · explained in 3 episodes
• Fidelity — 9× in this paper · explained in 2 episodes
• Reward Function — 8× in this paper · explained in 2 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Action Space — 6× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Conservation Laws — 4× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Entanglement — 2× in this paper · explained in 4 episodes
• Phase Transition — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptive Algorithm — 1× in this paper · explained in 1 episode
• Adaptive Selection — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Effective Hamiltonian — 1× in this paper · explained in 2 episodes
• Entanglement Entropy — 1× in this paper · explained in 2 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Quantum fluctuations — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• Taming Trotter Errors with Quantum Resources
• Continuous control with deep reinforcement learning
• Reinforcement Learning for Quantum Technology
• Reinforcement Learning in Ultracold Atom Experiments
• Domino-cooling Oscillator Networks with Deep Reinforcement Learning
• Learning effective Hamiltonians for adaptive time-evolution quantum algorithms
• Adam: A Method for Stochastic Optimization

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