Quantum computing firm Xanadu has launched a new research initiative with defense giant Lockheed ...

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 ...

Researchers at the University of Tokyo have identified a precise sweet spot where quantum reservoir computing, a machine learning approach that treats quantum systems as computational engines, reaches ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

The 2025 Nobel Prize in physics has been awarded to a trio of scientists – a Briton, a Frenchman and an American – for their ground-breaking discoveries in the field of quantum mechanics.John Clarke, ...

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 ...

At a time when data are doubling every two years, the U.S. is projected to create over 40 billion gigabytes of data by 2025. To prepare for the influx, Kennesaw State University associate professor ...

Classical computations rely on binary bits, which can be in either of the two states, 0 or 1. In contrast, quantum computing is based on qubits, which can be 0, 1, or a superposition or entanglement ...