Hybrid photonic computing in delay-coupled non-linear systems with memory (HyPCom)

• Applicants: Professorin Dr. Kathy Lüdge; Professor Dr. Janik Wolters
• Subject Area: Theoretical Condensed Matter Physics ; Optics, Quantum Optics and Physics of Atoms, Molecules and Plasmas ; Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 445183921

In recent years, artificial intelligence (AI) as a groundbreaking innovation has developed into a driver of digitization and autonomoussystems in all areas of life. This has created great potential for mastering global challenges, such as environmental, resource and climate protection, as well as the security and performance of communication and IT systems. The current progress of AI, especially in the field of machine learning, is based on the exponential increase in hardware performance and its use for processing large amounts of data. However, despite the famous nature of Moore’s Law, the overall increase in hardware performance has slowed down in recent years, as for example measured by transistor-density. This motivates research into other approaches. Reservoir computing is one such promising novel paradigm, which has emerged in analogue neuromorphic computing. It shows great potential to overturn the digital transistor-hegemony and explore novel computational mechanisms and substrates for artificial intelligence. In a joint theoretical and experimental effort, this project aims at realizing non- linear optical networks with reconfigurable topology, enabled by combining feedback-coupled optical amplifiers with coherent optical memories. The potential of these systems for neuro-inspired information processing in the reservoir computing approach is explored.

• DFG Programme: Research Grants