Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning

Simone Lauria; Mohammed F. Saleh

doi:10.1364/CLEO_FS.2023.FTu4B.2

Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning

Simone Lauria^*
, Mohammed F. Saleh

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We have developed a recurrent neural network that efficiently simulates the unidirectional pulse propagation equation. The model is validated via predicting complex nonlinear interactions in a periodically poled nanophotonic LiNbO₃ waveguide.

Original language	English
Title of host publication	2023 Conference on Lasers and Electro-Optics
Publisher	IEEE
ISBN (Electronic)	9781957171258
DOIs	https://doi.org/10.1364/CLEO_FS.2023.FTu4B.2
Publication status	Published - 27 Sept 2023
Event	2023 Conference on Lasers and Electro-Optics - San Jose, United States Duration: 7 May 2023 → 12 May 2023

Conference

Conference	2023 Conference on Lasers and Electro-Optics
Abbreviated title	CLEO 2023
Country/Territory	United States
City	San Jose
Period	7/05/23 → 12/05/23

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Electronic, Optical and Magnetic Materials
Instrumentation
Atomic and Molecular Physics, and Optics

Access to Document

10.1364/CLEO_FS.2023.FTu4B.2

https://opg.optica.org/abstract.cfm?URI=CLEO_FS-2023-FTu4B.2

Cite this

@inproceedings{b23e4036efbd42ac93eced6f1827a324,

title = "Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning",

abstract = "We have developed a recurrent neural network that efficiently simulates the unidirectional pulse propagation equation. The model is validated via predicting complex nonlinear interactions in a periodically poled nanophotonic LiNbO3 waveguide.",

author = "Simone Lauria and Saleh, \{Mohammed F.\}",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s); 2023 Conference on Lasers and Electro-Optics, CLEO 2023 ; Conference date: 07-05-2023 Through 12-05-2023",

year = "2023",

month = sep,

day = "27",

doi = "10.1364/CLEO\_FS.2023.FTu4B.2",

language = "English",

booktitle = "2023 Conference on Lasers and Electro-Optics",

publisher = "IEEE",

address = "United States",

}

Lauria, S & Saleh, MF 2023, Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning. in 2023 Conference on Lasers and Electro-Optics., FTu4B.2, IEEE, 2023 Conference on Lasers and Electro-Optics, San Jose, California, United States, 7/05/23. https://doi.org/10.1364/CLEO_FS.2023.FTu4B.2

TY - GEN

T1 - Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning

AU - Lauria, Simone

AU - Saleh, Mohammed F.

PY - 2023/9/27

Y1 - 2023/9/27

N2 - We have developed a recurrent neural network that efficiently simulates the unidirectional pulse propagation equation. The model is validated via predicting complex nonlinear interactions in a periodically poled nanophotonic LiNbO3 waveguide.

AB - We have developed a recurrent neural network that efficiently simulates the unidirectional pulse propagation equation. The model is validated via predicting complex nonlinear interactions in a periodically poled nanophotonic LiNbO3 waveguide.

UR - https://www.scopus.com/pages/publications/85176313149

U2 - 10.1364/CLEO_FS.2023.FTu4B.2

DO - 10.1364/CLEO_FS.2023.FTu4B.2

M3 - Conference contribution

AN - SCOPUS:85176313149

BT - 2023 Conference on Lasers and Electro-Optics

PB - IEEE

T2 - 2023 Conference on Lasers and Electro-Optics

Y2 - 7 May 2023 through 12 May 2023

ER -

Predicting the interplay between second- and third-order nonlinear interaction in periodically-poled nanophotonic waveguides using machine learning

Abstract

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this