Machine learning has emerged as a powerful tool in condensed matter physics, offering new perspectives on the exploration of quantum many-body systems, phase transitions and exotic states of matter.

For years, progress in artificial intelligence has followed a simple rule: make it bigger ...

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 ...

Researchers from Tel Aviv University have developed a new method for simulating complex quantum systems that can be combined with cutting edge AI techniques The density of 6 fermions in a 2D harmonic ...

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 ...

Australia’s quantum push is accelerating, with real systems, bold timelines, and breakthroughs like quantum twins signaling a ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

Letters: Prof Ruben Saakyan and Prof Sheila Rowan respond to Prof Charlotte Deane of UK Research and Innovation ...

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 ...

Microchips power almost every modern device — phones, laptops and even fridges. But behind the scenes, making them is a complex process. But researchers say they have found a way to tap into the power ...

The trio was awarded the prize for research on quantum tunneling, the second year in a row that IT-related work was honored. In a boost to the profile of quantum computing, the Nobel Prize Committee ...