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quant-ph2024
LSTM-QGAN: Scalable NISQ Generative Adversarial Network
Cheng Chu, Aishwarya Hastak, Fan Chen
Current quantum generative adversarial networks (QGANs) still struggle with practical-sized data. First, many QGANs use principal component analysis (PCA) for dimension reduction,…
quant-ph2024
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
Zhenxiao Fu, Min Yang, Cheng Chu +3
Variational quantum circuits (VQCs) have become a powerful tool for implementing Quantum Neural Networks (QNNs), addressing a wide range of complex problems. Well-trained VQCs serv…
quant-ph2024
TITAN: A Distributed Large-Scale Trapped-Ion NISQ Computer
Cheng Chu, Zhenxiao Fu, Yilun Xu +4
Trapped-Ion (TI) technology offers potential breakthroughs for Noisy Intermediate Scale Quantum (NISQ) computing. TI qubits offer extended coherence times and high gate fidelity, m…