3 citations · 3 across the 13 of their papers we have counts for
13 papers
Q-MAP: Multi-Platform Benchmarking of Distributed Quantum Computing for Coherent Controlled Islanding
Yuqi Jiang, Zhiding Liang, Qiang Guan +2
The integration of distributed energy resources into power networks is accelerating. The resulting variability narrows operating margins, so a disturbance can cascade into a wide-a…
SPLIT-Q: A Scalable Sequential Quantum Computing Framework for Coherent Controlled Islanding
Yuqi Jiang, Zhiding Liang, Qiang Guan +2
Growing integration of distributed energy resources increases power-system variability and uncertainty. During disturbances, these effects can intensify generation-load imbalances…
PACE-QAOA: Physics-Constrained Quantum Optimization for Qubit-Efficient Power System Islanding
Yuqi Jiang, Zhiding Liang, Qiang Guan +2
Increasing renewable-energy penetration heightens power-system variability and complicates disturbance containment. Controlled islanding mitigates cascading failures by partitionin…
Unified Uncertainty Quantification Framework Bridging Noisy Quantum Backends Across Variational Quantum Algorithms and Quantum Signal Processing
Priyabrata Senapati, Vibin Abraham, Qiang Guan +1
We present an uncertainty quantification (UQ) framework for application level benchmarking and characterization of noisy quantum backends. The framework compares two workload class…
Quantum Sampling Architecture for Protein Structure Reconstruction on Utility-Scale Hardware
Yuqi Zhang, Bo Fang, Yuxin Yang +6
Predicting the structure of short peptides in protein binding pockets remains difficult because this regime requires physics-based conformational search, yet existing methods do no…
Graph-VQE: A CUDA-Q Multi-QPU Simulation Framework for Hamiltonian-Aware Protein-Folding VQE
Yujun Feng, Yuqi Zhang, Jingyi Huang +4
The Variational Quantum Eigensolver (VQE) is essential for molecular simulation in drug discovery, but hardware noise and algorithmic limits restrict its precision. While the NVIDI…
QFoldAgent: An Autonomous Quantum Optimization Multi-Agent System for Protein Structure Prediction
Winson Chen, Yuqi Zhang, Sixu Chen +3
Hybrid quantum-classical protein structure prediction depends strongly on Hamiltonian penalty weights, yet existing lattice-based workflows typically fix these coefficients by hand…
REGRID-QAOA: A Resource-Efficient Hybrid QAOA Framework for Physics-Constrained Power System Islanding
Yuqi Jiang, Yuqi Zhang, Zhiding Liang +3
Quantum computing has rapidly emerged as a powerful paradigm for tackling computationally demanding problems. In particular, quantum optimization shows strong promise for hard comb…
Qronecker: A Certifiable Kronecker Compression Primitive for Quantum-Chemistry Hamiltonians
Yuqi Zhang, Sixu Chen, Feixiong Cheng +1
Processing qubit Hamiltonians derived from electronic-structure problems can become classically prohibitive because many downstream manipulations still rely on dense operator const…
A Hybrid Quantum-AI Framework for Protein Structure Prediction on NISQ Devices
Yuqi Zhang, Yuxin Yang, Feixiong Chen +7
Variational quantum algorithms provide a direct, physics-based approach to protein structure prediction, but their accuracy is limited by the coarse resolution of the energy landsc…
QDockBank: A Dataset for Ligand Docking on Protein Fragments Predicted on Utility-Level Quantum Computers
Yuqi Zhang, Yuxin Yang, Cheng-Chang Lu +4
Protein structure prediction is a core challenge in computational biology, particularly for fragments within ligand-binding regions, where accurate modeling is still difficult. Qua…
A Quantum Framework for Protein Binding-Site Structure Prediction on Utility-Level Quantum Processors
Yuqi Zhang, Yuxin Yang, William Martin +8
Accurate prediction of protein active-site structures remains a central challenge in structural biology, particularly for short and flexible peptide fragments where conventional an…
Escaping Barren Plateau: Co-Exploration of Quantum Circuit Parameters and Architectures
Yipei Liu, Yuhong Song, Jinyang Li +4
Barren plateaus (BP), characterized by exponentially vanishing gradients that hinder the training of variational quantum circuits (VQC), present a pervasive and critical challenge…