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Predicting the dynamic process and model parameters of vector optical solitons under coupled higher-order effects via WL-tsPINN

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  • Zhu, Bo-Wei
  • Fang, Yin
  • Liu, Wei
  • Dai, Chao-Qing

Abstract

We propose the two-subnet physical information neural network with the weighted loss function (WL-tsPINN) to study the higher-order effects of ultra-short pulses in birefringence fiber transmission and analyze the formation mechanism of vector solitons. We predict the dynamical process of mixed-type single/double soliton and soliton molecules based on the higher-order coupled nonlinear Schrödinger equation (CNLSE) by this WL-tsPINN method. Moreover, we deduce the physical coefficients of the higher-order CNLSE from the mixed single soliton solution. Deep learning based on neural network is a powerful tool for further study of higher-order CNLSE and has potential significance for further study of soliton dynamics.

Suggested Citation

  • Zhu, Bo-Wei & Fang, Yin & Liu, Wei & Dai, Chao-Qing, 2022. "Predicting the dynamic process and model parameters of vector optical solitons under coupled higher-order effects via WL-tsPINN," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:chsofr:v:162:y:2022:i:c:s0960077922006518
    DOI: 10.1016/j.chaos.2022.112441
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    References listed on IDEAS

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    6. Triki, Houria & Zhou, Qin & Liu, Wenjun & Biswas, Anjan & Moraru, Luminita & Yıldırım, Yakup & Alshehri, Hashim M. & Belic, Milivoj R., 2022. "Chirped optical soliton propagation in birefringent fibers modeled by coupled Fokas-Lenells system," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
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    Cited by:

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    3. Chen, Yi-Xiang, 2024. "(3+1)-dimensional partially nonlocal ring-like bright-dark monster waves," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    4. Elsayed M. E. Zayed & Mohamed E. M. Alngar & Reham M. A. Shohib, 2022. "Dispersive Optical Solitons to Stochastic Resonant NLSE with Both Spatio-Temporal and Inter-Modal Dispersions Having Multiplicative White Noise," Mathematics, MDPI, vol. 10(17), pages 1-18, September.
    5. Yin, Yu-Hang & Lü, Xing, 2024. "Multi-parallelized PINNs for the inverse problem study of NLS typed equations in optical fiber communications: Discovery on diverse high-order terms and variable coefficients," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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