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 ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

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 ...

The University of Oxford is to co-lead one of three new UK-Japan quantum technology projects, announced today during the ...

Collaboration between Europe and Japan in quantum technologies and high-performance computing (HPC) is taking a significant step forward with the launch of the Q-Neko project in 2026. The Q-Neko ...

The project aimed to develop a full stack of technologies to bring the practical advantages of quantum computing to industry in the near term Quantum computing is one of the frontiers of research and ...

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Motivation: Our goal is to establish a local infrastructure and a group of colleagues and graduate students focusing on research in the Quantum-NLP and ML domain. We aim at preparing and running ...