1 citations · 2 across the 12 of their papers we have counts for
12 papers
Quantum-Audit: Evaluating the Reasoning Limits of LLMs on Quantum Computing
Mohamed Afane, Kayla Laufer, Wenqi Wei +4
Language models have become practical tools for quantum computing education and research, from summarizing technical papers to explaining theoretical concepts and answering questio…
Differentiable Architecture Search for Adversarially Robust Quantum Computer Vision
Mohamed Afane, Quanjiang Long, Haoting Shen +4
Current quantum neural networks suffer from extreme sensitivity to both adversarial perturbations and hardware noise, creating a significant barrier to real-world deployment. Exist…
Optimizing Inter-chip Coupler Link Placement for Modular and Chiplet Quantum Systems
Zefan Du, Pedro Chumpitaz Flores, Wenqi Wei +3
Quantum computing offers unparalleled computational capabilities but faces significant challenges, including limited qubit counts, diverse hardware topologies, and dynamic noise an…
SQUASH: A SWAP-Based Quantum Attack to Sabotage Hybrid Quantum Neural Networks
Rahul Kumar, Wenqi Wei, Ying Mao +3
We propose a circuit-level attack, SQUASH, a SWAP-Based Quantum Attack to sabotage Hybrid Quantum Neural Networks (HQNNs) for classification tasks. SQUASH is executed by inserting…
Efficient Circuit Cutting and Scheduling in a Multi-Node Quantum System with Dynamic EPR Pairs
Zefan Du, Wenrui Zhang, Wenqi Wei +4
Despite advancements, current quantum hardware faces significant challenges, including limited qubit counts and high susceptibility to noise, which hinder the execution of large, c…
Hardware-aware Circuit Cutting and Distributed Qubit Mapping for Connected Quantum Systems
Zefan Du, Yanni Li, Zijian Mo +4
Quantum computing offers unparalleled computational capabilities but faces significant challenges, including limited qubit counts, diverse hardware topologies, and dynamic noise/er…
Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation
Shuwen Kan, Yanni Li, Hao Wang +2
Circuit cutting is a promising technique that leverages both quantum and classical computational resources, enabling the practical execution of large quantum circuits on noisy inte…
Next-Generation Phishing: How LLM Agents Empower Cyber Attackers
Khalifa Afane, Wenqi Wei, Ying Mao +2
The escalating threat of phishing emails has become increasingly sophisticated with the rise of Large Language Models (LLMs). As attackers exploit LLMs to craft more convincing and…
Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning
Xueqing Zhang, Junkai Zhang, Ka-Ho Chow +6
This demo paper examines the susceptibility of Federated Learning (FL) systems to targeted data poisoning attacks, presenting a novel system for visualizing and mitigating such thr…
Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System
Shuwen Kan, Zefan Du, Miguel Palma +6
Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as…
Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms
Shuwen Kan, Miguel Palma, Zefan Du +5
Quantum state preparation involves preparing a target state from an initial system, a process integral to applications such as quantum machine learning and solving systems of linea…
Resource-Efficient and Self-Adaptive Quantum Search in a Quantum-Classical Hybrid System
Zihao Jiang, Zefan Du, Shaolun Ruan +5
Over the past decade, the rapid advancement of deep learning and big data applications has been driven by vast datasets and high-performance computing systems. However, as we appro…