AI Techniques Address Hardware-Software Challenges in Quantum Computing

A new technical paper, titled 'Artificial Intelligence for Quantum Computing,' has been published by researchers from NVIDIA, University of Oxford, University of Toronto, Quantum Motion, and University of Waterloo.

The paper discusses how advancements in artificial intelligence (AI) over recent years have had a revolutionary impact in various application areas, including the field of quantum computing (QC). The counterintuitive nature and high-dimensional mathematics of QC make it an ideal candidate for AI's data-driven learning capabilities.

The researchers emphasize that many of the significant scaling challenges in QC may ultimately depend on developments in AI. However, the integration of AI techniques into QC requires expertise from both fields, which are considered among the most advanced and complex areas of computer science.

The paper reviews how state-of-the-art AI techniques are already addressing challenges across the hardware and software stack necessary for developing practical quantum computing, from device design to applications.

The authors also explore future opportunities and obstacles within this intersection of AI and quantum computing. The paper was published in December 2025 and can be found in Nature Communications.