Modelling and numerical simulation optimization of output spectra of PbSe doped quantum dot fiber light source based on genetic algorithm

Research Article
Open access

Modelling and numerical simulation optimization of output spectra of PbSe doped quantum dot fiber light source based on genetic algorithm

Luwei Fan 1* , Jiayang Lin 2
  • 1 Dalian University of Technology    
  • 2 Xi’an University of Posts & Telecommunications    
  • *corresponding author luwei_fan@mail.dlut.edu.cn
Published on 25 September 2023 | https://doi.org/10.54254/2755-2721/10/20230147
ACE Vol.10
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-009-7
ISBN (Online): 978-1-83558-010-3

Abstract

Optical fiber amplifiers mainly use rare earth elements as dopants. In the past 20 years, with the research on plastic optical fiber amplifiers doped with different natural elements (such as erbium and thulium), the performance of optical fiber amplifiers has been significantly improved. However, the application potential of natural elements has reached its limit. To improve optical communication, researchers are working on a fiber amplifier with a better flat gain and more intense light. In this paper, the quantum dot fiber amplifier is treated as a three-level structure, and a genetic algorithm is used to optimize the quantum dot fiber amplifier to maximize the total output power. In this study, by solving and analyzing the rate and power propagation equations of the numerical model, the gain spectrum of the amplifier at a wavelength of 1200~1700nm is obtained as a function of fiber length and doping concentration. Draw three-dimensional images based on fiber length, doping concentration, and ASE power axis to find the maximum power at the highest point of the image. Then, combined with the optimization results of the genetic algorithm, the maximum value of the total power is obtained.

Keywords:

optical fiber amplifiers, genetic algorithm, quantum dot fiber amplifier.

Fan,L.;Lin,J. (2023). Modelling and numerical simulation optimization of output spectra of PbSe doped quantum dot fiber light source based on genetic algorithm. Applied and Computational Engineering,10,79-85.
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References

[1]. Hao L C 2017 Research on Optical Transmission Characteristics of Quantum Dot Fiber Amplifiers. Guizhou University, MA thesis.

[2]. Cheng C and Zhang H 2006 Semiconductor nanocrystal PbSe quantum dot fiber amplifier J. Phys. pp 4139-4144.

[3]. Peng M 2020 Deep learning optimization method and application based on genetic algorithm South China University MA thesis.

[4]. Jiang S R 2021 Research on Grinding Process of Nanocrystalline Cemented Carbide GU092 Fujian University of Engineering MA Thesis.

[5]. Wang Z Y 2022 Research on Material Ordering and Transportation Optimization Problem Based on Multistage Evaluation and Selection Genetic Algorithm. Science and Technology Innovation doi:10.15913/j.cnki.kjycx.2022.22.001.

[6]. Ding K J 2018 Design and Implementation of a Course Scheduling System Based on Chaotic Gray Code Genetic Algorithm Hubei University of Technology MA thesis.

[7]. Jiang C 2009 Ultrabroadband Gain Characteristics of a Quantum-Dot-Doped Fiber Amplifier  IEEE J. Sel. Top. Quantum Electron. 15(1) pp 140-144 doi: 10.1109/JSTQE.2008.2010267.

[8]. Hu N S and Cheng C 2016 1250-1370 nm band PbSe quantum dot broadband fiber amplifier. Acta Optica Sinica 36 pp 0406002.

[9]. Cheng C and Zhang H 2007 Characteristics of bandwidth, gain and noise of a PbSe quantum dot-doped fiber amplifier Optics Communications 277 pp 372-378.

[10]. Cheng C and Shao W 2015 Preparation and Spectral Measurement of Solid Core PbSe Quantum Dot Fibers with UV Gel J. Optics 35 (09) pp 74-80.

Cite this article

Fan,L.;Lin,J. (2023). Modelling and numerical simulation optimization of output spectra of PbSe doped quantum dot fiber light source based on genetic algorithm. Applied and Computational Engineering,10,79-85.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Mechatronics and Smart Systems

ISBN：978-1-83558-009-7(Print) / 978-1-83558-010-3(Online)
Editor：Alan Wang, Seyed Ghaffar
Conference website: https://2023.confmss.org/
Conference date: 24 June 2023
Series: Applied and Computational Engineering
Volume number: Vol.10
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Hao L C 2017 Research on Optical Transmission Characteristics of Quantum Dot Fiber Amplifiers. Guizhou University, MA thesis.

[2]. Cheng C and Zhang H 2006 Semiconductor nanocrystal PbSe quantum dot fiber amplifier J. Phys. pp 4139-4144.

[3]. Peng M 2020 Deep learning optimization method and application based on genetic algorithm South China University MA thesis.

[4]. Jiang S R 2021 Research on Grinding Process of Nanocrystalline Cemented Carbide GU092 Fujian University of Engineering MA Thesis.

[5]. Wang Z Y 2022 Research on Material Ordering and Transportation Optimization Problem Based on Multistage Evaluation and Selection Genetic Algorithm. Science and Technology Innovation doi:10.15913/j.cnki.kjycx.2022.22.001.

[6]. Ding K J 2018 Design and Implementation of a Course Scheduling System Based on Chaotic Gray Code Genetic Algorithm Hubei University of Technology MA thesis.

[7]. Jiang C 2009 Ultrabroadband Gain Characteristics of a Quantum-Dot-Doped Fiber Amplifier  IEEE J. Sel. Top. Quantum Electron. 15(1) pp 140-144 doi: 10.1109/JSTQE.2008.2010267.

[8]. Hu N S and Cheng C 2016 1250-1370 nm band PbSe quantum dot broadband fiber amplifier. Acta Optica Sinica 36 pp 0406002.

[9]. Cheng C and Zhang H 2007 Characteristics of bandwidth, gain and noise of a PbSe quantum dot-doped fiber amplifier Optics Communications 277 pp 372-378.

[10]. Cheng C and Shao W 2015 Preparation and Spectral Measurement of Solid Core PbSe Quantum Dot Fibers with UV Gel J. Optics 35 (09) pp 74-80.

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