Propagation dynamics of the second-order chirped circular Pearcey Gaussian vortex beam in the fractional nonlinear Schrödinger equation

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-11-16 DOI:10.1016/j.chaos.2024.115734
Shangling He , Xi Peng , Yingji He , Chun Shan , Dongmei Deng
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Abstract

We present the propagation dynamics of the second-order chirped circular Pearcey Gaussian vortex beam (CCPGVB) in the Fractional nonlinear Schrödinger equation (FNSE) numerically and find some interesting behaviors. The CCPGVB can propagate like quasi solitons along the propagation direction. The autofocusing effect of the CCPGVB gets stronger while the autofocusing length monotonously decreases and the number of focus become lessen as the Lévy index approaches 2. By adjusting the Lévy index, the chirp factor β, the input power Pin, as well as the order of the off-axis vortex pair (m,l), the results show that these factors can effectively control the propagation dynamics of the CCPGVB, including intensity distribution, focal length, focal intensity, the light spot and the number of focus. Finally, the Poynting vector and the angular momentum of the CCPGVB prove the autofocusing and diffraction behaviors.
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分数非线性薛定谔方程中二阶啁啾圆皮尔斯高斯涡旋束的传播动力学
我们用数值方法展示了分数非线性薛定谔方程(FNSE)中二阶啁啾圆皮尔斯高斯涡旋束(CCPGVB)的传播动力学,并发现了一些有趣的行为。CCPGVB 可以像准孤子一样沿传播方向传播。当列维指数接近 2 时,CCPGVB 的自动聚焦效应会变得更强,而自动聚焦长度会单调地减小,聚焦次数也会变少。通过调整莱维指数、啁啾因子β、输入功率Pin以及离轴涡旋对(m,l)的阶次,结果表明这些因素可以有效地控制CCPGVB的传播动力学,包括强度分布、焦距、焦点强度、光斑和焦点数量。最后,CCPGVB 的 Poynting 向量和角动量证明了其自动聚焦和衍射行为。
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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