Joint PHI Lab Research with University of Tokyo Goes Neural

The NTT Research Physics & Informatics (PHI) Lab likes to describe its mission in these mashed-up terms: “Quantum Physics Meets Brain Science on Optical Platform.” The recently announced agreement with The University of Tokyo’s International Research Center for Neurointelligence (IRCN) to develop Coherent Ising Machine (CIM)-related technologies underscores the neuroscience and optical aspects of that slogan. The agreement specifically anticipates developing new numerical tools and a simulator for the CIM, an information processing platform based on photonic oscillator networks. 

A broad goal of this three-and-a-half year joint research with the IRCN is to develop a novel neuromorphic computing principle for combinatorial optimization and machine learning that can be implemented on a modern digital CIM platform. A near-term goal is to provide a field-programmable gate array (FPGA)-based CIM simulator with 16,000 spins and all-to-all couplings. Another good example of the NTT Research “Open Lab” strategy, PHI Lab Director Yoshihisa Yamamoto said he expects that the resulting algorithms and simulator “will be used by our numerous collaborators in other research and academic organizations, which is also likely to accelerate the search for applications in this field.” 

A core part of the IRCN project is previewed in a presentation that IRCN Project Associate Professor Timothée Leleu delivered last year at the NTT Research Upgrade 2020 summit, titled, “Neuromorphic in Silico Simulator for the CIM.” 

The cross-disciplinary aspects of this project are considerable. University of Tokyo Professor Kazuyuki Aihara, IRCN Deputy Director and PI for this project, has developed a theoretical platform composed of advanced control theory of complex systems, complex network theory and nonlinear data analysis and data-driven modeling; and on the applications side, he has also worked to bridge biological and clinical studies with human disease prediction and next-generation artificial intelligence (AI). 

“We have a strong foundation and considerable momentum going in,” Dr. Aihara said, “and will continue to draw inspiration from advances in mathematical and chaos engineering, optics and neuroscience as the research collaboration unfolds.”