A transformer-based reinforcement learning agent learns to reconfigure atoms in neutral atom arrays and reduces estimated logarithmic infidelity by up to about 20% on benchmark circuits, including unseen ones.
6 For more details on estimating n(t) m , see Sec
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Quantum circuits as a game: A reinforcement learning agent for quantum compilation and its application to reconfigurable neutral atom arrays
A transformer-based reinforcement learning agent learns to reconfigure atoms in neutral atom arrays and reduces estimated logarithmic infidelity by up to about 20% on benchmark circuits, including unseen ones.