Abstract: Quantum algorithms have demonstrated extraordinary potential in numerous fields. The demand for fraud detection in credit cards is growing increasingly, which calls for more efficient ...

Quantum machine learning is being explored as the next frontier in cybersecurity, but new research shows it remains far from replacing established artificial intelligence systems in detecting phishing ...

ABSTRACT: Grover’s algorithm achieves O( N ) query complexity for unstructured search, a result proven optimal by Zalka for algorithms using a fixed oracle operator. This paper presents the ...

TNO Quantum provides generic software components aimed at facilitating the development of quantum applications. This package implements a scikit-learn compatible, (quantum) support vector machine.

In the first article of this series, we introduced the idea of Quantum Machine Learning (QML), explained how quantum computing differs from classical computing and why researchers believe the ...

Quantum Machine Learning (QML) is one of the most promising and rapidly evolving fields at the intersection of artificial intelligence and quantum computing. Artificial intelligence has already ...

Population geneticists increasingly confront a paradox: even with genome-scale datasets and advanced machine learning models, subtle population structure often remains undetected, particularly in ...

This project provides a rigorous and practical benchmark of a Quantum Support Vector Classifier (QSVC) for breast cancer diagnosis. Using the well-known Wisconsin Breast Cancer dataset from ...

A new study suggests that quantum computing could play a decisive role in the escalating arms race between cybersecurity defenders and increasingly sophisticated cyber threats. Researchers from the ...