3 papers
quant-ph2026
Forked Physics-Informed Neural Networks for Non-Markovian Open Quantum Dynamics and Control
Zhao-Wei Wang, Kai-Yu Yuan, Feng-Hua Ren +1
Physics-informed neural networks (PINNs) provide a pathway to reunify the simulation and control of quantum systems, in which these two tasks are typically decoupled in traditional…
quant-ph2026
Higher-Order Magnus Corrections to Leakage Elimination Operator-Based Quantum Control Pulse Design in the Low-Frequency Regime
Hang Yu, Kai-Yu Yuan, Feng-Hua Ren +1
Effective quantum control is essential for quantum computing and information processing, yet level leakage remains a bottleneck limiting control fidelity. The leakage elimination o…
quant-ph2026
End-to-End Learning of Quantum Control on Latent Dynamical Manifold
Jun-Dong Zhong, Zong-Yuan Ge, Feng-Hua Ren +1
Traditional quantum control relies on an iterative "simulate-then-optimize" paradigm, where dynamics simulation and control design are decoupled, leading to substantial computation…