In the life sciences and healthcare industries, the speed of innovation impacts how soon new products, medications and ...

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 ...

Multi-target quantum compilation protocol. Its core is a quantum circuit designed for quantum computers. The circuit is built from a pool of gates, with the input being a set of target operations. It ...

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 ...

A team of researchers has shown that even small-scale quantum computers can enhance machine learning performance, using a novel photonic quantum circuit. Their findings suggest that today s quantum ...

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 ...

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 ...

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 ...

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 ...