Integrated diffractive neural networks performing near-infrared inference
Dr. Elena Goi, University of Shanghai for Science and Technology, Shanghai, China
Leuchs-Russell Auditorium, A.1.500, Staudtstr. 2
Optical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. Here, such optical devices for data processing in the form of multi-layer nanoscale diffractive neural networks trained to perform optical inference tasks are presented. The functionality of these passive optical devices on the example of decryptors trained to perform optical inference through symmetric and asymmetric decryption and multi-layer diffractive neural networks for direct phase retrieval are demonstrated. The diffractive neural networks, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide–semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm, achieving a neuron density of 108 neurons / mm3. The compact form factor of the resulting optical neural networks and the lithographic fabrication technology that allow for directly integration on opto-electronic sensors, enable the co-integration of the optical perceptrons with additional layers of electronic neural networks, or the use of the sensor’s nonlinear response as nonlinear activation function, in this way forming deep neural networks. This power-efficient commixture of machine learning and on-chip integration may have a transformative impact on optical decryption, sensing, microscopy, high-precision laser nanolithography, medical diagnostics, and computing.
Elena Goi received her B.S. and M.S. in physics from the University of Trieste, Italy. In 2018 she was awarded her Ph.D. from RMIT University, Australia, under the supervision of Prof. Min Gu, researching advanced biomimetic optical materials and topological photonic systems. She is currently a Research Fellow at the University of Shanghai of Science and Technology, China, where she is affiliated with the Centre for Artificial-Intelligence Nanophotonics and the Institute of Photonic Chips. Her current research includes the development and implementation of three-dimensional nanolithographic techniques and the study of novel optical materials and architectures for optical neural networks.
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