QRA: Quantum Reinforcement Agent for Generating Optimal Quantum Sensor Circuits

This study proposes a QRA approach for designing optimal Quantum Sensor Circuits (QSCs) to address complex quantum physics problems. The QRA generates QSCs by selecting sequences of gates that maximize the Quantum Fisher Information (QFI) while minimizing the number of gates. The QSCs generated by the QRA are capable of producing entangled quantum states, specifically the squeezed states, by performing generalized Ramsey measurements on qubits. High QFI indicates increased sensitivity to parameter changes, making the circuit useful for quantum state estimation and control tasks. Evaluation of the QRA on a QSC that consists of two qubits and a sequence of Rx, Ry and S gates demonstrates its efficiency in generating optimal QSCs with a QFI of 1. This work illustrates the potential computational power of quantum agents for solving quantum physics problems.