META-LEARNING-BASED QUANTUM STATE ESTIMATION METHOD AND SYSTEM

Abstract

There is provided a method for meta-learning-based quantum state estimation. The method may comprise: acquiring a first count indicating a number of times a first state is continuously output before a second state is first output as a result of inputting a quantum state into a quantum circuit having a first parameter; sampling parameters of the quantum circuit using results of reinforcement learning based on the first count; acquiring a second count indicating a number of times the first state is continuously output as a result of inputting the quantum state into the quantum circuit having the sampled parameters; updating the first parameter of the quantum circuit to a second parameter using the results of the reinforcement learning if the second count is less than a threshold count; and estimating the quantum state that has been input into the quantum circuit.

CPC Classifications