Wednesday, 27 March,
The physical properties of light and matter can be exploited to realize novel computing paradigms that can have low latency, high energy efficiency, and capabilities beyond digital systems. These opportunities have spurred the recent interest in machine learning accelerators, neuromorphic computing, and quantum computing enabled by photonics. This panel will discuss the photonic devices and circuits needed for these new types of computing systems to be competitive with digital hardware. Both current and future technologies will be presented and explored. Some of the questions that we aim to answer include but are not limited to:
- How can we harness the advantages of photonics in practice to scale computing throughput?
- What are the applications that can truly benefit from photonics-enabled in-physics computing? And those cannot?
- What are the critical challenges in devices and integration (e.g., power consumption, size, loss etc.) the scientific community must overcome in order to realize the full potential of in-physics computing?
Joyce Poon, Max Planck Institute of Microstructure Physics, Germany
Patrick Runge , Fraunhofer HHI, Germany
Wei Shi, Laval University, Canada
Jose Capmany, Valencia Polytechnic University, Spain
Chris Cole, Parallax Group, United States
Dirk Englund, Massachusetts Institute of Technology, United States
Patricia Lee, Quantinuum, United States
Hiro Onodera, NTT Research & Cornell University, United States
Maurice Steinman, Lightelligence, United States
Zach Vernon, Xanadu Quantum Technologies, Canada