When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Machine learning, and more generally, artificial intelligence, has achieved dramatic success over the past decade. This has been apparent in the tackling of notoriously challenging problems such as ...

The initiative will fund research and education to create hybrid algorithms for complex scientific and industrial challenges.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...

Inside the Self-Driving Lab Revolutionizing Quantum Computing Quantum computing has long been heralded as the next frontier in computational power, ...

Introduction: The Portfolio Optimization Process Needs to Be Revamped. For decades, portfolio optimization has been the pinnacle of modern finance. In the 1950s, with the introduction of Harry ...

Traditional encryption methods have long been vulnerable to quantum computers, but two new analyses suggest a capable enough ...

Small-scale quantum computers can enhance machine learning performance, as shown in an experimental study using a photonic quantum processor. (Nanowerk News) One of the current hot research topics is ...