CV-ADAPT-VQE with tailored symmetry-preserving pools achieves significantly shallower circuits than Hamiltonian-based VQE for bosonic lattice models in GPU classical simulations.
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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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Continuous-variable ADAPT-VQE for bosonic lattice models
CV-ADAPT-VQE with tailored symmetry-preserving pools achieves significantly shallower circuits than Hamiltonian-based VQE for bosonic lattice models in GPU classical simulations.
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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.