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4 papers · 1 filter
Robust optimization for quantum reinforcement learning control using partial observations
Chen Jiang, Yu Pan, Zheng-Guang Wu +2
The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of quantum sta…
Automatic Depth Optimization for Quantum Approximate Optimization Algorithm
Yu Pan, Yifan Tong, Yi Yang
Quantum Approximate Optimization Algorithm (QAOA) is a hybrid algorithm whose control parameters are classically optimized. In addition to the variational parameters, the right cho…
Sampled-data design for robust control of a single qubit
Daoyi Dong, Ian R. Petersen, Herschel Rabitz
This paper presents a sampled-data approach for the robust control of a single qubit (quantum bit). The required robustness is defined using a sliding mode domain and the control l…
Sliding Mode Control of Two-Level Quantum Systems
Daoyi Dong, Ian R. Petersen
This paper proposes a robust control method based on sliding mode design for two-level quantum systems with bounded uncertainties. An eigenstate of the two-level quantum system is…