Accurate Loss Prediction of Realistic Hollow-Core Anti-Resonant Fibers Using Machine Learning-Reference-Cited by-同舟云学术

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Accurate Loss Prediction of Realistic Hollow-Core Anti-Resonant Fibers Using Machine Learning

Published:2024-11 Issue:6: Advances and Applications Volume:30 Page:1-8
ISSN:1077-260X
Container-title:IEEE Journal of Selected Topics in Quantum Electronics
language:
Short-container-title:IEEE J. Select. Topics Quantum Electron.

Author:

Jewani Yordanos¹,Petry Michael²^ORCID,Sanchez-Arias Rei¹^ORCID,Amezcua-Correa Rodrigo³,Habib Md Selim⁴^ORCID

Affiliation:

1. Department of Data Science and Business Analytics, Florida Polytechnic University, Lakeland, FL, USA

2. Faculty of Electrical Engineering and Information Technology, University of Applied Sciences Karlsruhe, Karlsruhe, Germany

3. CREOL, University of Central Florida, Orlando, FL, USA

4. Department of Electrical Engineering and Computer Science, Florida Institute of Technology, Melbourne, FL, USA

Funder

U.S. Fulbright Scholarship

Woodrow W. Everett, Jr. SCEEE Development Fund

Southeastern Association of Electrical Engineering Department Heads

U.S. Department of Treasury

Coronavirus State and Local Fiscal Recovery Funds

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/2944/10399926/10437998.pdf?arnumber=10437998

Reference72 articles.

1. Fibre Optic Communication In 21st Century

2. The First 0.14-dB/km Loss Optical Fiber and its Impact on Submarine Transmission

3. Demonstration of a waveguide regime for a silica hollow - core microstructured optical fiber with a negative curvature of the core boundary in the spectral region > 35 μm

4. Low loss silica hollow core fibers for 3–4 μm spectral region

5. Light transmission in negative curvature hollow core fiber in extremely high material loss region

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