3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud
Zhepeng Wang, Yi Sheng, Nirajan Koirala +4
Benefiting from cloud computing, today's early-stage quantum computers can be remotely accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it poses a hi…