QATNet: A Lightweight Quantum-Classical Tabular Network for Low-Latency Intrusion Detection

Abstract: Modern communication environments ranging from smart mobility infrastructures to digitally integrated healthcare systems demand adaptable and trustworthy network security. In this situation, Software-Defined Networks (SDNs) play a vital role by providing programmable control and global visibility, enabling rapid policy updates and fine-grained traffic management. As a result, the need for efficient and interpretable intrusion […]

Quantum Annealing for Robust Principal Component Analysis

Abstract: Principal component analysis is commonly used for dimensionality reduction, feature extraction, denoising, and visualization. The most commonly used principal component analysis method is based upon optimization of the L2-norm; however, the L2-norm is known to exaggerate the contribution of errors and outliers. When optimizing over the L1-norm, the components generated are known to exhibit […]

A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity

Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constraint greatly inhibits the range of applications that can leverage quantum computers. Moreover, as the available qubits increase, the computational complexity grows exponentially, posing additional challenges. Consequently, there is an urgent need to […]

A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity

Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constraint greatly inhibits the range of applications that can leverage quantum computers. Moreover, as the available qubits increase, the computational complexity grows exponentially, posing additional challenges. Consequently, there is an urgent need to […]

A Low-Complexity Quantum Principal Component Analysis Algorithm

In this article, we propose a low-complexity quantum principal component analysis (qPCA) algorithm. Similar to the state-of-the-art qPCA, it achieves dimension reduction by extracting principal components of the data matrix, rather than all components of the data matrix, to quantum registers, so that the samples of measurement required can be reduced considerably. Both our qPCA […]