Reinforcement Learning for Compiled-CNOT-Efficient VQE Circuits
This work asks whether reinforcement learning (RL) can design circuits that reach a fixed accuracy target with fewer compiled CNOTs than strong hand-designed and greedy baselines than strong hand-designed and greedy baselines.
Joshy Joseph, John Carlson
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