双折射光纤中Radhakrishnan-Kundu-Lakshmanan方程光孤子的构造

IF 2.4 Q2 ENGINEERING, MECHANICAL
N. Ullah, Muhammad Imran Asjad, Hamood UR REHMAN, A. Akgül
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引用次数: 21

摘要

本文应用Sardar-subequation方法(SSM)和新的扩展双曲函数方法(EHFM)发现了Radhakrishnan-Kundu-Lakshmanan方程(RKLE)的双折射光纤中的多光土。我们以指数函数、三角函数和双曲函数的形式构造解,如混合复孤子和多光学孤子解。此外,构造了奇异周期波解,并定义了孤子解存在的约束条件。此外,对于不同的合适参数,以3D和2D图的形式公开了所获得解的物理解释。计算结果表明,所实现的计算方案简单、熟练、简洁,可以应用于更复杂的现象,并伴有代表性的计算。我们得到了几种新的解法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of optical solitons of Radhakrishnan–Kundu–Lakshmanan equation in birefringent fibers
Abstract In this article, we are attracted to discover the multiple-optical soiltons in birefringent fibers for Radhakrishnan–Kundu–Lakshmanan equation (RKLE) by applying the Sardar-subequation method (SSM) and the new extended hyperbolic function method (EHFM). We construct the solutions in the form of exponential, trigonometric, and hyperbolic functions solitons solutions like mixed complex solitons and multiple-optical solitons solutions. In addition, singular periodic wave solutions are constructed, and the restraint conditions for the presence of soliton solutions are also defined. Moreover, the physical interpretation of the obtained solutions is disclosed in forms of 3D and 2D plots for different suitable parameters. The attained results indicate that the implemented computational scheme is straight, proficient, and brief and can be applied in more complex phenomena with the associate of representative computations. We have obtained several sorts of new solutions.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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