Efficiently representing and characterising quantum systems is challenging because Hilbert space is huge, but artificial intelligence, which is good at high-dimensional pattern recognition and function approximation, helps to predict quantum properties and to construct surrogates for quantum states. Applications include quantum certification and benchmarking to enhancing quantum algorithms and characterising strongly correlated phases of matter. ArXiv:2509.04923 (Nature Reviews Physics, in press)

Prof Barry Sanders holds two Diplomas, a PhD, and a DSc from Imperial College London and is a Fellow of the Royal Society of Canada, Optica, the American Physical Society, and the UK Institute of Physics and a recipient of the Chevalier dans l’Ordre des Palmes académiques of France in 2025, CDL Toronto Mentor of the Year in 2024, and City of Calgary International Achievement Award in 2022. He made foundational contributions to quantum optics and quantum information and also is a researcher emerging dual-use technologies. Sanders is Scientific Director of the University of Calgary’s Quantum City, a Senior Fellow at the Canadian Centre for International Governance and Innovation, and Visiting Professorial Fellow at the University of New South Wales in Australia. He is an advisor for CERN’s Open Quantum Institute, the Google-GESDA XPRIZE for applied quantum computing, a few start-ups, and some investment funds. He serves on four editorial boards and has trained over one hundred graduate students and postdoctoral researchers.