4 papers
Learning Symmetric Hamiltonian
Jing Zhou, D. L. Zhou
Hamiltonian Learning is a process of recovering system Hamiltonian from measurements, which is a fundamental problem in quantum information processing. In this study, we investigat…
Mean transforms of unbounded weighted composition operator pairs
Jing-Bin Zhou, Shihai Yang
In this paper, we first characterize the polar decomposition of unbounded weighted composition operator pairs in an -space. Based on this characterization…
PALQO: Physics-informed Model for Accelerating Large-scale Quantum Optimization
Yiming Huang, Yajie Hao, Jing Zhou +3
Variational quantum algorithms (VQAs) are leading strategies to reach practical utilities of near-term quantum devices. However, the no-cloning theorem in quantum mechanics preclud…
On the original Ulam's problem and its quantization
Changguang Dong, Jing Zhou
In this paper we show that under general resonance the classical piecewise linear Fermi-Ulam accelerator behaves substantially different from its quantization in the sense that the…