33 citations · 55 across the 9 of their papers we have counts for
9 papers
BVQC: A Backdoor-style Watermarking Scheme for Variational Quantum Circuits
Cheng Chu, Lei Jiang, Fan Chen
Variational Quantum Circuits (VQCs) have emerged as a powerful quantum computing paradigm, demonstrating a scaling advantage for problems intractable for classical computation. As…
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,…
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…
LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
Ahmad Faiz, Sotaro Kaneda, Ruhan Wang +4
The carbon footprint associated with large language models (LLMs) is a significant concern, encompassing emissions from their training, inference, experimentation, and storage proc…
CryptoQFL: Quantum Federated Learning on Encrypted Data
Cheng Chu, Lei Jiang, Fan Chen
Recent advancements in Quantum Neural Networks (QNNs) have demonstrated theoretical and experimental performance superior to their classical counterparts in a wide range of applica…
QDoor: Exploiting Approximate Synthesis for Backdoor Attacks in Quantum Neural Networks
Cheng Chu, Fan Chen, Philip Richerme +1
Quantum neural networks (QNNs) succeed in object recognition, natural language processing, and financial analysis. To maximize the accuracy of a QNN on a Noisy Intermediate Scale Q…
QTrojan: A Circuit Backdoor Against Quantum Neural Networks
Cheng Chu, Lei Jiang, Martin Swany +1
We propose a circuit-level backdoor attack, \textit{QTrojan}, against Quantum Neural Networks (QNNs) in this paper. QTrojan is implemented by few quantum gates inserted into the va…
IQGAN: Robust Quantum Generative Adversarial Network for Image Synthesis On NISQ Devices
Cheng Chu, Grant Skipper, Martin Swany +1
In this work, we propose IQGAN, a quantum Generative Adversarial Network (GAN) framework for multiqubit image synthesis that can be efficiently implemented on Noisy Intermediate Sc…
QMLP: An Error-Tolerant Nonlinear Quantum MLP Architecture using Parameterized Two-Qubit Gates
Cheng Chu, Nai-Hui Chia, Lei Jiang +1
Despite potential quantum supremacy, state-of-the-art quantum neural networks (QNNs) suffer from low inference accuracy. First, the current Noisy Intermediate-Scale Quantum (NISQ)…