首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Propagation properties of spatial optical solitons in different nonlocal nonlinear media with arbitrary degrees of nonlocality
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Propagation properties of spatial optical solitons in different nonlocal nonlinear media with arbitrary degrees of nonlocality

机译:空间光学孤子在具有任意非局域度的不同非局域非线性介质中的传播特性

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摘要

We address the physical features exhibited by spatial optical solitons propagating in nonlocal Kerr-type media with Gaussian-shaped response and exponential-decay response, respectively. An Iteration algorithm based on the split-step Fourier method is developed to obtain the numerical solutions of the solitons for the nonlocal nonlinear Schrodinger equation with arbitrary degrees of nonlocality. Our numerical results show that the soliton properties in the normalized system are different with the change of the degree of nonlocality and with the different responses. The profiles undergo a gradual and Continuous transition from a Gaussian-shaped function in the strongly nonlocal case to a hyperbolic secant function in the local case for the Gaussian-shaped response, but for the exponential-decay response, the soliton profile is not Gaussian-shaped even in the strongly nonlocal cases. For the same response function, the stronger the nonlocality is, the higher the critical powers for solitons are and the larger of the phase shifts of the solitons. For the same degrees of nonlocality, when the degrees of nonlocality is larger enough, both the critical power and the phase shift for the Gaussian-shaped response are larger than that for the exponential-decay response. (c) 2007 Elsevier GmbH. All rights reserved.
机译:我们解决了空间光学孤子分别在具有高斯形响应和指数衰减响应的非局域Kerr型介质中传播的物理特征。提出了一种基于分步傅里叶方法的迭代算法,得到了具有任意非局部度的非局部非线性薛定inger方程的孤子数值解。我们的数值结果表明,归一化系统中的孤子性质随非局域度的变化和响应的不同而不同。对于高斯型响应,轮廓从强非局部情况下的高斯型函数逐渐过渡到局部情况下的双曲正割函数,但对于指数衰减响应,孤子轮廓不是高斯型。即使在强烈的非本地情况下也能形成形状。对于相同的响应函数,非局部性越强,孤子的临界功率越高,孤子的相移就越大。对于相同程度的非局部性,当非局部性的程度足够大时,高斯型响应的临界功率和相移都大于指数衰减响应的临界功率和相移。 (c)2007 Elsevier GmbH。版权所有。

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