AI Techniques To Solve HW-SW Challenges For Useful Quantum Computing (Nvidia, U. of Oxford et al.) - Semiconductor Engineering

A new technical paper “Artificial intelligence for quantum computing” was published by researchers at NVIDIA, University of Oxford, University of Toronto, Quantum Motion, University of Waterloo et al. “Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including the nascent field of quantum computing (QC). The counterintuitive nature and high-dimensional mathematics of QC make it a prime candidate for AI’s data-driven learning capabilities, and in fact, many of QC’s biggest scaling challenges may ultimately rest on developments in AI. However, bringing leading techniques from AI to QC requires drawing on disparate expertise from arguably two of the most advanced and esoteric areas of computer science. Here we aim to encourage this cross-pollination by reviewing how state-of-the-art AI techniques are already advancing challenges across the hardware and software stack needed to develop useful QC – from device design to applications. We then close by examining its future opportunities and obstacles in this space.” Alexeev, Y., Farag, M.H., Patti, T.L. et al. Artificial intelligence for quantum computing. Nat Commun 16, 10829 (2025). https://doi.org/10.1038/s41467-025-65836-3 Δdocument.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() ); Thank you. Please check your email to confirm your subscription.