Reinforcement Learning for Many-Body Ground-State Preparation Inspired by Counterdiabatic Driving
Reinforcement Learning for Many-Body Ground-State Preparation Inspired by Counterdiabatic Driving
The quantum alternating operator ansatz (QAOA) is a prominent example of variational quantum algorithms. We propose a generalized QAOA called CD-QAOA, which is inspired by the counterdiabatic driving procedure, designed for quantum many-body systems and optimized using a reinforcement learning (RL) approach. The resulting hybrid control algorithm proves versatile in …