The uncertainty inherent to quantum mechanics has long left physicists wondering whether the observations we make on the ...

Welcome to another biweekly update on all things quantum computing. Today’s piece is truly dominated by Nvidia’s ($NVDA) ...

Participants will code, simulate, and benchmark advanced quantum algorithms while applying Quantum Machine Learning (QML) to practical, real-world scenarios.

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 ...

This project aims to to build a hybrid quantum/classical machine-learning framework using Qiskit / python based Quantum Machine Learning (QML) and classical machine learning libraries (ML) to find ...

Quantum computing (QC) is one of the most transformative scientific and technological advances of the 21 st century, introducing entirely new paradigms for solving computational problems that have ...

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 ...

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

Quantum computers may be able to run useful algorithms more quickly, thanks to a new quantum router that helps data get to the right place faster. Traditional computers avoid becoming slow when faced ...