Femtojoule Optical ReLU for Neural Networks with Incoherent Light

We implement an optical ReLU-like function by integrating liquid crystals and silicon photodiodes at single-pixel level, achieving a femtojoule energy threshold and incoherent light compatibility, and demonstrate an optical multilayer neural network.

Authors

Can Berk Uzundal
Qixin Feng (ORCID: https://orcid.org/0000-0003-1756-0090)
Feng Wang (ORCID: https://orcid.org/0000-0001-8369-6194)
Ruihan Guo (ORCID: https://orcid.org/0000-0002-9724-396X)

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.1364/cleo_si.2025.ss103_2
Primary Topic: Neural Networks and Reservoir Computing
Type: article
Field-Weighted Citation Impact: 0.00

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article

Femtojoule Optical ReLU for Neural Networks with Incoherent Light

Can Berk Uzundal, Qixin Feng, Feng Wang, Ruihan Guo

Jan 1, 2025

Neural Networks and Reservoir Computing

article

Femtojoule Optical ReLU for Neural Networks with Incoherent Light

Can Berk Uzundal, Qixin Feng, Feng Wang, Ruihan Guo

January 1, 2025article en

Abstract

Openalex Percentile: Top 87%

Neural Networks and Reservoir Computing

DOI Source OpenAlex

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Femtojoule Optical ReLU for Neural Networks with Incoherent Light — Can Berk Uzundal, Qixin Feng, et al. · (2025) | TGRS Research Map | TGRS