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Reinforcement Learning Assisted Quantum Simulation of Many-Body Excited States and Real-Time Dynamics
The computation of electronic excited states and real-time quantum dynamics of many-fermion systems is among the most promising applications of near-term quantum computing. In this work, we generalize the reinforcement learning contracted quantum eigensolver (RL-CQE), previously developed for ground
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