The paper applies Q-learning and DQN to synthesizing small quantum circuits via matrix-based MDPs, reporting success rates from 100% down to 1% depending on task and algorithm.
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Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations
The paper applies Q-learning and DQN to synthesizing small quantum circuits via matrix-based MDPs, reporting success rates from 100% down to 1% depending on task and algorithm.