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Main Authors: Chen, Baiqiao, Jia, Qi, Feng, Rui, Sun, Fangkui, Cao, Yongyin, Wang, Jian, Ding, Weiqiang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.14735
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author Chen, Baiqiao
Jia, Qi
Feng, Rui
Sun, Fangkui
Cao, Yongyin
Wang, Jian
Ding, Weiqiang
author_facet Chen, Baiqiao
Jia, Qi
Feng, Rui
Sun, Fangkui
Cao, Yongyin
Wang, Jian
Ding, Weiqiang
contents Euler's formula, an extraordinary mathematical formula, establishes a vital link between complex-valued operations and trigonometric functions, finding widespread application in various fields. With the end of Moore's Law, electronic computing methods are encountering developmental bottlenecks. With its enviable potential, optical computing has successfully achieved high-speed operation of designed complex numbers. However, the challenge of processing and manipulating arbitrary complex numbers persists. This study introduces a generalized complex exponential operator (GCEO), utilizing a diffractive optical neural network (DONN) for the computation of the complex exponential through Euler's formula. Experiments validate a series of complex exponential calculations using the GCEO. The GCEO has demonstrated generalizability and can compute inputs of any precision within an appropriate error margin. The proposed operator highlights the immense potential of DONN in optical computation and is poised to significantly contribute to the development of computational methods for optoelectronic integration.
format Preprint
id arxiv_https___arxiv_org_abs_2405_14735
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Generalized all-optical complex exponential operator
Chen, Baiqiao
Jia, Qi
Feng, Rui
Sun, Fangkui
Cao, Yongyin
Wang, Jian
Ding, Weiqiang
Optics
Euler's formula, an extraordinary mathematical formula, establishes a vital link between complex-valued operations and trigonometric functions, finding widespread application in various fields. With the end of Moore's Law, electronic computing methods are encountering developmental bottlenecks. With its enviable potential, optical computing has successfully achieved high-speed operation of designed complex numbers. However, the challenge of processing and manipulating arbitrary complex numbers persists. This study introduces a generalized complex exponential operator (GCEO), utilizing a diffractive optical neural network (DONN) for the computation of the complex exponential through Euler's formula. Experiments validate a series of complex exponential calculations using the GCEO. The GCEO has demonstrated generalizability and can compute inputs of any precision within an appropriate error margin. The proposed operator highlights the immense potential of DONN in optical computation and is poised to significantly contribute to the development of computational methods for optoelectronic integration.
title Generalized all-optical complex exponential operator
topic Optics
url https://arxiv.org/abs/2405.14735