Exploring the potential of photonic quantum processors in machine learning

Quantum computers have progressed to the point where they can now solve some specific mathematical problems that classical computers cannot solve. This talk will present ongoing research on potential applications to machine learning. I will first introduce near-term photonic quantum processors: although they are not universal for quantum computation, they provide a scalable route to solving some classes of hard sampling problems. I will then describe ways in which current classical neural network architectures may harness these unique computational capabilities for generative modelling and for classification. This talk will highlight both the potential and the limitations of these approaches, as well as opportunities for further research.

Short Bio

William Clements is Head of Applications and Software at ORCA Computing, a leading UK-based photonic quantum computing company. His research focuses on the intersection of physics and computing, and how physical devices can be harnessed to compute faster and better. He has co-authored over 20 publications in machine learning and quantum computing and has a physics PhD from the University of Oxford. Before joining ORCA, he worked in roles spanning basic research to product engineering in leading AI deeptech startups.