Model-Free Quantum Control with Reinforcement Learning

  title={Model-Free Quantum Control with Reinforcement Learning},
  author={V. V. Sivak and A. Eickbusch and H. Liu and Baptiste Royer and Ioannis Tsioutsios and Michel H. Devoret},
  journal={Physical Review X},
Model bias is an inherent limitation of the current dominant approach to optimal quantum control, which relies on a system simulation for optimization of control policies. To overcome this limitation, we propose a circuit-based approach for training a reinforcement learning agent on quantum control tasks in a model-free way. Given a continuously parametrized control circuit, the agent learns its parameters through trial-and-error interaction with the quantum system, using measurement outcomes… 

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