The role of machine learning in quantum software and compilation
Olivia Di Matteo· University of British Columbia
Olivia Di Matteo introduces quantum computing and compilation, examining how the translation from high-level quantum programs to efficient hardware instructions becomes a bottleneck as applications scale. The seminar identifies parts of the quantum software stack where machine learning and artificial intelligence can improve this process. It presents the group’s work using graph-based reinforcement learning to optimize quantum circuits, then considers outstanding challenges and research questions for scalable quantum software.
Ended
Fri, Oct 30 · 19:00 UTC · Online
Quantum TechnologyReinforcement Learning