Intersubband engineered nonlinear activation function for photonic neural networks

Fast, sensitive, and compact photonic nonlinear activation devices are crucial for forming photonic neural networks with high computational efficiency. However, conventional photonic activation units lack suitable nonlinearity due to weak optical nonlinearities. Using intersubband nanostructures, we introduce the smallest possible optoelectronic approach for nonlinear processing in photonic neural networks. Here we also demonstrate the simulation and fabrication of the intersubband nanostructures. The simulation results shows a 3.5 microwatt threshold and an optical response time of 10 picoseconds within a device that is only 4 microns in length.

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Publication Details

Published
2024-10-02
DOI
https://doi.org/10.1117/12.3027777
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Intersubband engineered nonlinear activation function for photonic neural networks

Zheheng Xu, Sadhvikas Addamane, David Burghoff
Neural Networks and Reservoir Computing
article

Intersubband engineered nonlinear activation function for photonic neural networks

Zheheng Xu, Sadhvikas Addamane, David Burghoff
article en

Abstract

Fast, sensitive, and compact photonic nonlinear activation devices are crucial for forming photonic neural networks with high computational efficiency. However, conventional photonic activation units lack suitable nonlinearity due to weak optical nonlinearities. Using intersubband nanostructures, we introduce the smallest possible optoelectronic approach for nonlinear processing in photonic neural networks. Here we also demonstrate the simulation and fabrication of the intersubband nanostructures. The simulation results shows a 3.5 microwatt threshold and an optical response time of 10 picoseconds within a device that is only 4 microns in length.

The University of Texas at Austin (US)
Openalex Percentile: Top 85%
Neural Networks and Reservoir Computing
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