Computational complexity of random multi-qudit states and unitaries scales exponentially with qudit number, while physical complexity scales more slowly.
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A hybrid optimal-control-plus-contextual-RL framework learns low-dimensional residual pulse corrections that preserve high-fidelity controlled-phase gates on two qutrits under realistic static model mismatch.
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Computational and physical complexity of synthesizing random multi-qudit quantum states and unitary operators
Computational complexity of random multi-qudit states and unitaries scales exponentially with qudit number, while physical complexity scales more slowly.
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Reinforcement Learning for Robust Calibration of Multi-Qudit Quantum Gates
A hybrid optimal-control-plus-contextual-RL framework learns low-dimensional residual pulse corrections that preserve high-fidelity controlled-phase gates on two qutrits under realistic static model mismatch.