Reinforced Learning for Quantum Design

Abstract

A computer-implemented process for generating a policy for design of quantum devices using a quantum hardware design kit including instructions and parameters associated with the instructions includes the following operations. An environment for a reinforcement learning architecture that includes a neural network as at least part of an agent is defined. A policy is generated by training the neural network using the environment. The defining the environment includes: defining actions of the neural network from a set of the instructions and parameters combinations associated with the quantum hardware design kit; and defining a reward function for generation of the policy.

Publication
US Patent App. US18/463240

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