From the 1 of 6 linked papers with an AI index.
6 papers
iSWAP maximises the second-moment spectral gap in random quantum circuits
Yanying Liang, Haoran Zhu
We prove that the gate maximises the spectral gap of the Hermitian second-moment operator on every connected graph with at least three vertices, among all two-loca…
Spectral gaps of ironed two-qubit gadgets matching the iSWAP gap
Yanying Liang, Haoran Zhu
The paper proves that ironed two‑qubit gadgets with KAK parameter a=5/9 have the same second‑moment spectral gap as the iSWAP gadget on complete graphs with at least five vertices,…
A Dynamical Lie-Algebraic Framework for Hamiltonian Engineering and Quantum Control
Yanying Liang, Ruibin Xu, Mao-Sheng Li +2
Determining the unitary dynamics accessible from finite Hamiltonian resources is a central problem in Hamiltonian engineering and quantum control. Dynamical Lie algebras (DLAs) con…
Learnability of a hybrid quantum-classical neural network for graph-structured quantum data
Yanying Liang, Sile Tang, Zhehao Yi +2
Graph-structured data commonly arise in many real-world applications, and this extends naturally into the quantum setting, where quantum data with inherent graph structures are fre…
Entangled mixed-state datasets generation by quantum machine learning
Ruibin Xu, Zheng Zheng, Yanying Liang +1
The advancement of classical machine learning is inherently linked to the establishment and progression of classical dataset. In quantum machine learning (QML), there is an analogo…
Enhancing Variational Quantum Circuit Training: An Improved Neural Network Approach for Barren Plateau Mitigation
Zhehao Yi, Yanying Liang, Haozhen Situ
Combining classical optimization with parameterized quantum circuit evaluation, variational quantum algorithms (VQAs) are among the most promising algorithms in near-term quantum c…