Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

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.

Researchers developed an experimental method for confirming quantum activity in a quantum computing system. When you purchase through links on our site, we may earn an affiliate commission. Here’s how ...

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 two articles of this series, we introduced the foundations of Quantum Machine Learning (QML) and explored how quantum properties such as superposition and entanglement can enhance 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 ...

Department of Biological, Chemical and Environmental Sciences, Wheaton College Massachusetts, Norton, MA, United States Population geneticists increasingly confront a paradox: even with genome-scale ...

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 ...

Quantum computing exists beyond the realm of science fiction. Technology is now integrating with artificial intelligence to transform machine learning capabilities, adaptation and reasoning abilities.