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.

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification BEIJING, Feb.06, 2026––WiMi Hologram ...

The authors investigate a quantum support vector algorithm that uses qudits to identify the most accurate way of solving a prototype machine learning task: the binary classification of point clusters.

Quantum computing innovations have garnered significant attention for their potential to revolutionize industries, with the energy sector being one of the most promising areas for application. As ...

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 ...

Upconversion (UC) materials, such as Yb/Er-doped fluorides and oxides, are widely applied in bioimaging, lighting, and quantum photonics. However, interpreting UC spectra to extract material ...

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 ...

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 ...

Abstract: Noisy data is ubiquitous in quantum computer, greatly affecting the performance of various algorithms. However, existing quantum support vector machine models are not equipped with ...