A Fourier Optoelectronic Synapse with Single‐Wavelength Modulation

K Kesheng Wang B Baocheng Peng (School of Electronic Science and Engineering National Key Laboratory of Spintronics Nanjing University Nanjing China) S Shanshan Jiang (Eastern Institute for Advanced Study, Ningbo Institute of Digital Twin) Q Qianye Xing (School of Electronic Science & Engineering, and National Key Laboratory of Spintronics, Nanjing University 1 , Nanjing 210023,) H Hainan Zhang (School of Integrated Circuits Anhui University Hefei China) S Shuo Cheng Y Yi Ren (Department of Polymer Science & Engineering, State Key Laboratory of Analytical Chemistry for Life Science, MOE Key Laboratory of High Performance Polymer Materials and Technology, School of Chemistry) K Kailu Shi H Hangyuan Cui B Bingyan Wang B Bo He H Huanhuan Wei Q Qing Wan X Xiaohui Guo G Gang He C Changjin Wan

Abstract

ABSTRACT Analyzing spatial frequency domain features is essential for capturing diverse in‐depth features of targets, thereby enhancing the adaptability to unstructured environments for embodied intelligence. Digital approaches suffer from limited efficiency due to frequent data transfer, while neuromorphic ones lack dedicated frequency‐domain processing hardware. Here, we report a Fourier neuromorphic visual (FIVE) system integrating a Fourier optical system and Fourier optoelectronic synapses (FOSs). The FIVE system extracts frequency‐domain cues optically with negligible time latency and computational energy consumption, and these cues are then filtered based on nonlinearity to the light intensity of FOSs. Furthermore, such a FOS device exhibits multilevel memory tunability by light intensity of single‐wavelength. This property enables the implementation of multilayer perceptron for further classification of frequency domain features. The FIVE system achieves a high accuracy of ∼90% in the image noise classification task and outperforms convolutional neural network (CNN)‐based approaches by orders of magnitude in parameter count.

Article Details

Volume / Issue Vol. 1, Issue 1
Published August 05, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (16)

K

Kesheng Wang

B

Baocheng Peng

School of Electronic Science and Engineering National Key Laboratory of Spintronics Nanjing University Nanjing China

S

Shanshan Jiang

Eastern Institute for Advanced Study, Ningbo Institute of Digital Twin

Q

Qianye Xing

School of Electronic Science & Engineering, and National Key Laboratory of Spintronics, Nanjing University 1 , Nanjing 210023,

H

Hainan Zhang

School of Integrated Circuits Anhui University Hefei China

S

Shuo Cheng

Y

Yi Ren

Department of Polymer Science & Engineering, State Key Laboratory of Analytical Chemistry for Life Science, MOE Key Laboratory of High Performance Polymer Materials and Technology, School of Chemistry

K

Kailu Shi

H

Hangyuan Cui

B

Bingyan Wang

B

Bo He

H

Huanhuan Wei

Q

Qing Wan

X

Xiaohui Guo

G

Gang He

C

Changjin Wan