Optical soliton perturbation of Fokas-Lenells equation by the Laplace-Adomian decomposition algorithm

Abstract

This paper displays numerical simulation for bright and dark optical solitons that emerge from Fokas-Lenells equation which is studied in the context of dispersive solitons in polarization-preserving fibers. The Laplace-Adomian decomposition scheme is the numerical tool adopted in the paper. The numerical results, for bright and dark solitons, are expository and therefore supplement the analytical developments, thus far.

Introduction

One of the governing models to study dispersive solitons is Fokas-Lennels equation (FLE) [1–13]. In such a model, in addition to group velocity dispersion (GVD), one considers, inter-modal dispersion as well as nonlinear dispersion thus treating it with a flavor of additional dispersive effects. There has been a plethora of analytical tools that have been implemented to study FLE. They range from semi-inverse variational principle, Lie symmetry analysis, Riccati equation approach, exp-function method, traveling wave hypothesis, trial function method and further wide varieties. This paper will be changing gears to study the model from a different perspective. One of the very many and modern numerical algorithms that will be implemented is the Laplace-Adomian decomposition integration scheme. This method has been successfully applied to variety of other models from optics [14–16]. This paper now studies FLE, for the first time, by the aid of Laplace-Adomian decomposition scheme. The details are sketched in the remainder of the paper, after introducing the model.

The Fokas-Lenells equation (FLE) in presence of perturbation terms

The dimensionless form of the perturbed Fokas-Lenells equation (FLE) is given by

$$ {\begin{aligned} {iu}_{t}&+a_{1}u_{xx}+a_{2}u_{xt}+\vert u\vert^{2}\left(bu+i\sigma u_{x}\right)\\&\quad=i\left[\alpha u_{x}+\lambda \left(\vert u\vert^{2}u\right)_{x}\ + \mu \left(\vert u\vert^{2}\right)_{x}u\right]. \end{aligned}} $$

(1)

This equation was first studied in [17–24] and arises in various systems such as water waves, plasma physics, solid state physics and nonlinear optics. In Eq. (1), u(x,t) represents a complex field envelope, and x and t are spatial and temporal variables, respectively. Here, the coefficient a₁ is the group velocity dispersion (GVD) and a₂ is the spatio-temporal dispersion (STD) the coefficient b is self-phase modulation moreover σ accounts for nonlinear dispersion. In the perturbative term of Eq. (1), the first term represents the inter-modal dispersion (IMD), the second term is the self-steepening effect and finally the last term accounts for another version of nonlinear dispersion (ND).

Bright optical solitons

The bright optical soliton solution to (1) is given by [5, 11]:

$$ u(x,t)=A\text{sech}\left[(x-\nu t)\right] e^{i[-\kappa x+\omega t+\theta ]}. $$

(2)

Here, ν is the soliton velocity, κ is the soliton frequency, ω is the angular velocity and θ is the phase center.

The amplitude A of the soliton in this case is given by

$$ A=\pm\sqrt{\frac{2(a_{1}-a_{2}\nu)}{b-\kappa\lambda+\kappa\sigma}}, $$

(3)

where, the velocity of the soliton in relation to the coefficients that appear in the Eq. (1) is

$$ \nu=\frac{\alpha+2a_{1}\kappa-a_{2}\omega}{a_{2}\kappa-1}, $$

(4)

and the constraints conditions on the parameters are

$$ a_{2}\kappa\neq 1, \quad 3\lambda+2\mu-\sigma=0. $$

(5)

In the previous context κ is any parameter that satisfies the Eq. (5).

Dark optical solitons

noindent The dark optical soliton solution to (1) is given by [5, 11]:

$$ u(x,t)=B\text{tanh}\left[(x-\nu t)\right] e^{i\left[-\kappa x+\omega t+\theta \right]}. $$

(6)

Here, ν is the soliton velocity, κ is the soliton frequency, ω is the angular velocity and θ is the phase center.

The amplitude B of the soliton in this case is given by

$$ B=\pm\sqrt{\frac{-2(a_{1}-a_{2}\nu)}{b-\kappa\lambda+\kappa\sigma}}, $$

(7)

where, the velocity of the soliton in relation to the coefficients that appear in the Eq. (1) is

$$ \nu=\frac{\alpha+2a_{1}\kappa-a_{2}\omega}{a_{2}\kappa-1}, $$

(8)

and the constraints conditions on the parameters are

$$ a_{2}\kappa\neq 1, \quad 3\lambda+2\mu-\sigma=0. $$

(9)

In the previous context κ is any parameter that satisfies the Eq. (9).

The Laplace Adomian Decomposition Method (LADM)

To illustrate the basic concept of Laplace-Adomian decomposition algorithm, we consider the general form of second order nonlinear partial differential equations in the form

$$ F\left(u(x,t)\right)=0,\quad $$

(10)

with initial conditions

$$ u(x,0)=f(x),\quad u_{x}(x,0)=g(x). $$

(11)

where F is a differential operator. Now, let us decompose this operator as F=L+R+N where $L(u)=\frac {\partial u}{\partial t}$ stands for a linear differential operator. The operators R and N are the remaining linear and nonlinear parts, respectively.

With these considerations, Eq. (10) can now be rewritten as

$$ L u(x,t)=Ru(x,t)+Nu(x,t). $$

(12)

Solving for Lu(x,t) and applying the Laplace transform respect to t to Eq. (12), gives

$$ \mathcal{L}\left\{L u(x,t)\right\}= \mathcal{L}\left\{Ru(x,t)+Nu(x,t)\right\}. $$

(13)

Thus, Eq. (13) turns out to be equivalent to

$$ su(x,s)-u(x,0)= \mathcal{L}\left\{Ru(x,t)+Nu(x,t)\right\}. $$

(14)

Using Eq. (11), one get

$$ u(x,s)=\frac{f(x)}{s}+\frac{1}{s}\mathcal{L}\left\{Ru(x,t)+Nu(x,t)\right\}. $$

(15)

Finally, by applying inverse Laplace transformation $\mathcal {L}^{-1}$ on both sides of the Eq. (15), we obtain

$$ u(x,t)=f(x)+\mathcal{L}^{-1}\left[\frac{1}{s}\mathcal{L}\{Ru(x,t)+Nu(x,t)\}\right]. $$

(16)

The Laplace-Adomian decomposition algorithm assumes the solution u(x,t) can be expanded into infinite series given by

$$ u(x,t)= \sum_{n=0}^{\infty}u_{n}(x,t). $$

(17)

Moreover, Also the nonlinear operator N is decomposed as

$$ Nu(x,t)= \sum_{n=0}^{\infty}A_{n}(u_{0},u_{1},\ldots, u_{n}),. $$

(18)

Each A_n is an Adomian polynomial of u₀,u₁,…,u_n that can be calculated for all forms of nonlinearity according to the following formula [25–27]:

$$A_{0}=N(u_{0}), $$

$$ A_{n}=\frac{1}{n}\sum_{i=1}^{m}\sum_{k=0}^{n-1}(k+1)u_{i,k+1}\frac{\partial}{\partial u_{i,0}}A_{n-1-k},\quad n\geq 1. $$

(19)

Therefore Adomian’s polynomials are given by A₀=N(u₀)

A₁=u₁N^′(u₀)

$A_{2}=u_{2}N'(u_{0})+\frac {1}{2}u_{1}^{2}N''(u_{0})$

$A_{3}=u_{3}N'(u_{0})+u_{1}u_{2}N''(u_{0})+\frac {1}{3!}u_{1}^{3}N^{(3)}(u_{0})$

$A_{4}=u_{4}N'(u_{0})+\left (\frac {1}{2}u_{2}^{2}+u_{1}u_{3}\right)N''(u_{0})+\frac {1}{2!}u_{1}^{2}u_{2}N^{(3)}(u_{0})+\frac {1}{4!}u_{1}^{4}N^{(4)}(u_{0})$

⋮

All other polynomials are calculated in a similar way.

Substituting (17) and (18) into Eq. (16) gives rise to

$$ \begin{aligned} \sum_{n=0}^{\infty}u_{n}(x,t)=& f(x)+\mathcal{L}^{-1}\left[\frac{1}{s}\mathcal{L}\left\{R\sum_{n=0}^{\infty}u_{n}(x,t)\right.\right.\\ &\left.\left. +\sum_{n=0}^{\infty}A_{n}(u_{0},u_{1},\ldots, u_{n})\right\}\right]. \end{aligned} $$

(20)

Hence, Eq. (20) suggests the following iterative algorithm

$$ {\begin{aligned} \left\{ \begin{array}{ll} u_{0}(x,t)=f(x),\\ u_{n+1}(x,t)=\mathcal{L}^{-1}\left[\frac{1}{s}\mathcal{L}\left\{{Ru}_{n}(x,t)+A_{n}(u_{0},u_{1},\ldots, u_{n})\right\}\right],\;\; n=0,1,2,\ldots \end{array}\right. \end{aligned}} $$

(21)

Finally, after determining u_n’s, the N-term truncated approximation of the solution is obtained as

$$ u_{N}(x,t)=\sum_{n=0}^{N-1}u_{n}(x,t),\;\; N\geq 1. $$

(22)

From this analysis it is evident that, the Adomian decomposition method, combined with the Laplace transform requires less effort in comparison with the traditional Adomian decomposition method. This method considerably decreases the number of calculations. In addition, Adomian decomposition procedure is easily established without requiring to linearize the problem.

Solution of the perturbed Fokas-Lenells equation by LADM

In this section, we outline the application of LADM to obtain explicit solution of Eq. (1) with the initial conditions u(x,0)=f(x), u_x(x,0)=g(x).

Let us consider the dimensionless form of the perturbed Fokas-Lenells equation Eq. (1) in an operator form

$$ Lu(x,t)+Ru(x,t)+N_{1}u(x,t)+N_{2}u(x,t)+N_{3}u(x,t)=0 $$

(23)

where the notation N₁u=−i|u|²(bu+iσu_x), N₂u=−λ(|u|²u)_x and N₃u=−μu(|u|²)_x symbolize the nonlinear term, respectively. The notation Ru=−(αu_x+ia₁u_xx+ia₂u_xt) symbolize the linear differential operator and Lu=u_t simply means derivative with respect to time.

The LADM represents solution as an infinite series of components given below,

$$ u(x,t)= \sum_{n=0}^{\infty}u_{n}(x,t). $$

(24)

The nonlinear terms N₁u, N₂u and N₃u can be decomposed into infinite series of Adomian polynomials given by:

$$ N_{1}u=-i\vert u\vert^{2}(bu+i\sigma u_{x})=\sum_{n=0}^{\infty}P_{n}(u_{0},u_{1},\ldots, u_{n}), $$

(25)

$$ N_{2}u=-\lambda\left(\vert u\vert^{2}u\right)_{x}=\sum_{n=0}^{\infty}Q_{n}(u_{0},u_{1},\ldots, u_{n}), $$

(26)

and

$$ N_{3}u=-\mu u\left(\vert u\vert^{2}\right)_{x}=\sum_{n=0}^{\infty}R_{n}(u_{0},u_{1},\ldots, u_{n}). $$

(27)

Here P_n, Q_n and R_n are the Adomian polynomials and can be calculated by the formula given by the Eq. (19), that is,

$$P_{0}=N_{1}(u_{0}),\quad Q_{0}=N_{2}(u_{0}),\quad R_{0}=N_{3}(u_{0}), $$

and for every n≥1 we have

$$ P_{n}=\frac{1}{n}\sum_{i=1}^{m}\sum_{k=0}^{n-1}(k+1)u_{i,k+1}\frac{\partial}{\partial u_{i,0}}P_{n-1-k}, $$

(28)

$$ Q_{n}=\frac{1}{n}\sum_{i=1}^{m}\sum_{k=0}^{n-1}(k+1)u_{i,k+1}\frac{\partial}{\partial u_{i,0}}Q_{n-1-k}, $$

(29)

$$ R_{n}=\frac{1}{n}\sum_{i=1}^{m}\sum_{k=0}^{n-1}(k+1)u_{i,k+1}\frac{\partial}{\partial u_{i,0}}R_{n-1-k}. $$

(30)

The first few Adomian polynomials are given by

$$\begin{array}{*{20}l} P_{0}&=-{ibu}_{0}^{2}\bar{u}_{0},\\ P_{1}&=-2{ibu}_{0}u_{1}\bar{u}_{0}-{ibu}_{0}^{2}\bar{u}_{1},\\ P_{2}&=-2{ibu}_{0}u_{2}\bar{u}_{0}-{ibu}_{1}^{2}\bar{u}_{0}-2{ibu}_{0}u_{1}\bar{u}_{1}-{ibu}_{0}^{2}\bar{u}_{2},\\ P_{3}&=-2{ibu}_{0}u_{3}\bar{u}_{0}-2{ibu}_{1}u_{2}\bar{u}_{0}-2{ibu}_{0}u_{2}\bar{u}_{1}-{ibu}_{1}^{2}\bar{u}_{1}\\&\quad-2{ibu}_{0}u_{1}\bar{u}_{2}-{ibu}_{0}^{2}\bar{u}_{3},\\ P_{4}&=-ib\bar{u}_{0}u_{2}^{2}-2{ibu}_{0}\bar{u}_{0}u_{4}-2ib\bar{u}_{0}u_{1}u_{3}-2{ibu}_{0}\bar{u}_{1}u_{3}\\&\quad-2{ibu}_{1}\bar{u}_{1}u_{2}+2u_{0}\bar{u}_{2}u_{2}-{ibu}_{1}^{2}\bar{u}_{2} \\& -2{ibu}_{0}\bar{u}_{1}u_{3}-{ibu}_{0}^{2}\bar{u}_{4},\\ \vdots \end{array} $$

$$\begin{array}{*{20}l} Q_{0}&=-(\lambda+\mu)u_{0}^{2}\bar{u}_{0x},\\[-2pt] Q_{1}&= -(\lambda+\mu)\left(u_{0}^{2}\bar{u}_{1x}+2u_{0}u_{1}\bar{u}_{0x}\right),\\[-2pt] Q_{2}&=\!-(\lambda\,+\,\mu)\left(u_{1}^{2}\bar{u}_{0x}\,+\,u_{0}^{2}\bar{u}_{2x}\,+\,2u_{0}u_{1}\bar{u}_{1x}\,+\,2u_{0}u_{2}\bar{u}_{0x}\right), \\ Q_{3}&=-(\lambda+\mu)\left(u_{1}^{2}\bar{u}_{1x}+u_{0}^{2}\bar{u}_{3x}+2u_{0}u_{1}\bar{u}_{2x}\right.\\[-2pt] &\quad \left. +2u_{0}u_{2}\bar{u}_{1x}+2u_{0}u_{3}\bar{u}_{0x}+2u_{1}u_{2}\bar{u}_{0x}\right),\\ Q_{4}&=-(\lambda+\mu)\left(u_{2}^{2}\bar{u}_{0x}\,+\,u_{1}^{2}\bar{u}_{2x}\,+\,2u_{0}u_{1}\bar{u}_{3x}+2u_{0}u_{2}\bar{u}_{2x}\right.\\& \left.+2u_{0}u_{3}\bar{u}_{1x}+2u_{0}u_{4}\bar{u}_{0x}+2u_{1}u_{2}\bar{u}_{1x} +2u_{1}u_{3}\bar{u}_{0x}\right),\\ \vdots \end{array} $$

$$\begin{array}{*{20}l} R_{0}&=(\sigma-2\lambda-\mu)u_{0}\bar{u}_{0}u_{0x},\\[-2pt] R_{1}&= (\sigma-2\lambda-\mu)(u_{0}\bar{u}_{0}u_{1x}+u_{0}\bar{u}_{1}u_{0x}+u_{1}\bar{u}_{0}u_{0x}),\\[-2pt] R_{2}&=(\sigma-2\lambda-\mu)\left(u_{0}\bar{u}_{0}u_{2x}+u_{0}\bar{u}_{1}u_{1x}+u_{0}\bar{u}_{2}u_{0x}\right.\\[-2pt] &\left.+u_{1}\bar{u}_{0}u_{1x}+u_{1}\bar{u}_{1}u_{0x}+u_{2}\bar{u}_{0}u_{0x}\right),\\[-2pt] R_{3}&=(\sigma-2\lambda-\mu)\left(u_{0}\bar{u}_{0}u_{3x}+u_{0}\bar{u}_{1}u_{2x}+u_{0}\bar{u}_{2}u_{1x}\right.\\[-2pt] & +u_{0}\bar{u}_{3}u_{0x}+u_{1}\bar{u}_{0}u_{2x}+u_{1}\bar{u}_{1}u_{1x}+u_{1}\bar{u}_{2}u_{0x}\\[-2pt] &\left.+u_{2}\bar{u}_{0}u_{1x}+u_{2}\bar{u}_{1}u_{0x}+u_{3}\bar{u}_{0}u_{0x}\right),\\[-2pt] R_{4}&=(\sigma-2\lambda-\mu)\left(u_{0}\bar{u}_{0}u_{4x}+u_{0}\bar{u}_{1}u_{3x}+u_{0}\bar{u}_{2}u_{2x}\right.\\[-2pt] &+u_{0}\bar{u}_{3}u_{1x}+u_{0}\bar{u}_{4}u_{0x}+u_{1}\bar{u}_{0}u_{3x}+u_{1}\bar{u}_{1}u_{2x}\\[-2pt] &+u_{1}\bar{u}_{2}u_{1x}+u_{1}\bar{u}_{3}u_{0x}+u_{2}\bar{u}_{0}u_{2x}+u_{2}\bar{u}_{1}u_{1x}\\[-2pt] &\left.+u_{2}\bar{u}_{2}u_{0x}+u_{3}\bar{u}_{0}u_{1x}+u_{3}\bar{u}_{1}u_{0x}+u_{4}\bar{u}_{0}u_{0x}\right),\\ \vdots \end{array} $$

Then, the Adomian polynomials corresponding to the nonlinear part Nu=N₁u+N₂u+N₃u are

$$\begin{array}{*{20}l} {} A_{0}&=-{ibu}_{0}^{2}\bar{u}_{0}-(\lambda+\mu)u_{0}^{2}\bar{u}_{0x}+(\sigma-2\lambda-\mu)u_{0}\bar{u}_{0}u_{0x},\\[-2pt] {} A_{1}&=-2{ibu}_{0}u_{1}\bar{u}_{0}\,-\,{ibu}_{0}^{2}\bar{u}_{1}-\!(\lambda+\mu)(u_{0}^{2}\bar{u}_{1x}+2u_{0}u_{1}\bar{u}_{0x})\\[-2pt] &\quad+(\sigma-2\lambda-\mu)(u_{0}\bar{u}_{0}u_{1x}+u_{0}\bar{u}_{1}u_{0x}+u_{1}\bar{u}_{0}u_{0x}),\\ {} A_{2}&=-2{ibu}_{0}u_{2}\bar{u}_{0}-{ibu}_{1}^{2}\bar{u}_{0}-2{ibu}_{0}u_{1}\bar{u}_{1}-{ibu}_{0}^{2}\bar{u}_{2}\\[-4pt]&\quad-(\lambda+\mu)\left(u_{1}^{2}\bar{u}_{0x}+u_{0}^{2}\bar{u}_{2x}+2u_{0}u_{1}\bar{u}_{1x}+2u_{0}u_{2}\bar{u}_{0x}\right)\\&\quad+(\sigma-2\lambda-\mu)(u_{0}\bar{u}_{0}u_{2x}+u_{0}\bar{u}_{1}u_{1x}+u_{0}\bar{u}_{2}u_{0x}\\ \end{array} $$

$$\begin{array}{*{20}l} &\quad+u_{1}\bar{u}_{0}u_{1x}+u_{1}\bar{u}_{1}u_{0x}+u_{2}\bar{u}_{0}u_{0x}),\\ {} A_{3}&=-2{ibu}_{0}u_{3}\bar{u}_{0}-2{ibu}_{1}u_{2}\bar{u}_{0}-2{ibu}_{0}u_{2}\bar{u}_{1}-{ibu}_{1}^{2}\bar{u}_{1}\\ &\quad-2{ibu}_{0}u_{1}\bar{u}_{2}-{ibu}_{0}^{2}\bar{u}_{3}-(\lambda+\mu)(u_{1}^{2}\bar{u}_{1x}+u_{0}^{2}\bar{u}_{3x}\\&\quad+2u_{0}u_{1}\bar{u}_{2x}+2u_{0}u_{2}\bar{u}_{1x}+2u_{0}u_{3}\bar{u}_{0x}+2u_{1}u_{2}\bar{u}_{0x})\\&\quad+(\sigma-2\lambda-\mu)\times (u_{0}\bar{u}_{0}u_{3x}+u_{0}\bar{u}_{1}u_{2x}+u_{0}\bar{u}_{2}u_{1x}\\&\quad+u_{0}\bar{u}_{3}u_{0x}+u_{1}\bar{u}_{0}u_{2x}+u_{1}\bar{u}_{1}u_{1x}+u_{1}\bar{u}_{2}u_{0x}\\&\quad+u_{2}\bar{u}_{0}u_{1x}+u_{2}\bar{u}_{1}u_{0x}+u_{3}\bar{u}_{0}u_{0x}),\\ \end{array} $$

and so on for other Adomian polynomials.

By applying the Laplace transform with respect to t on both sides of the Eq. (23) and using the linearity of the Laplace transform gives:

$$ {\begin{aligned} \mathcal{L}\left\{Lu(x,t)\right\}&= -\mathcal{L}\{Ru(x,t)\}-\mathcal{L}\left\{N_{1} u(x,t)\right\}\\&\quad-\mathcal{L}\left\{N_{2} u(x,t)\right\}-\mathcal{L}\left\{N_{3} u(x,t)\right\}. \end{aligned}} $$

(31)

Because of the differentiation property of Laplace transform, Eq. (31) can be written as

$$ {\begin{aligned} s\mathcal{L}\{u(x,t)\}&-u(x,0)= -\mathcal{L}\left\{Ru(x,t)\right\}-\mathcal{L}\left\{N_{1} u(x,t)\right\}\\&\quad-\mathcal{L}\left\{N_{2} u(x,t)\right\}-\mathcal{L}\left\{N_{3} u(x,t)\right\}. \end{aligned}} $$

(32)

Thus,

$$ {{} \begin{aligned} \mathcal{L}\left\{u(x,t)\right\}&=\frac{1}{s}u(x,0)-\frac{1}{s}\left(\mathcal{L}\left\{Ru(x,t)\right\}+\mathcal{L}\left\{N_{1} u(x,t)\right\}\right.\\ &\left.+\mathcal{L}\left\{N_{2} u(x,t)\right\}+\mathcal{L}\left\{N_{3} u(x,t)\right\}\right). \end{aligned}} $$

(33)

By substituting (24), (25), (26) and (27) into (33), we obtain

$$ \begin{aligned} \mathcal{L}\left\{\sum_{n=0}^{\infty}u_{n}(x,t)\right\}=&\frac{f(x)}{s}-\frac{1}{s}\left(\mathcal{L}\left\{R\sum_{n=0}^{\infty}u_{n}(x,t)\right\}\right.\\ &\left.+\!\mathcal{L}\left\{\sum_{n=0}^{\infty}P_{n}\right\}\,+\,\mathcal{L}\left\{\sum_{n=0}^{\infty}Q_{n}\right\}\,+\,\mathcal{L}\left\{\sum_{n=0}^{\infty}R_{n}\right\}\right). \end{aligned} $$

(34)

Comparing both sides of the Eq. (34), the following relations arise:

$$ \mathcal{L}\left\{u_{0}(x,t)\right\}=\frac{f(x)}{s} $$

(35)

$$ {\begin{aligned} \mathcal{L}\left\{u_{1}(x,t)\right\}=-\frac{1}{s}\left(\mathcal{L}\left\{{Ru}_{0}(x,t)\right\}+\mathcal{L}\left\{P_{0}\right\}+\mathcal{L}\left\{Q_{0}\right\}+\mathcal{L}\left\{R_{0}\right\}\right) \end{aligned}} $$

(36)

$$ {\begin{aligned} \mathcal{L}\left\{u_{2}(x,t)\right\}\,=\,-\frac{1}{s} \left(\mathcal{L}\left\{{Ru}_{1}(x,t)\right\}\,+\,\mathcal{L}\left\{P_{1}\right\}\,+\,\mathcal{L}\left\{Q_{1}\right\}\,+\,\mathcal{L}\left\{R_{1}\right\}\right). \end{aligned}} $$

(37)

In general, we get the following recursive algorithm

$$ {\begin{aligned} \mathcal{L}\left\{u_{n+1}(x,t)\right\}&=-\frac{1}{s}\left(\mathcal{L}\left\{{Ru}_{n}(x,t)\right\}+\mathcal{L}\left\{P_{n}\right\}\right.\\&\left.+\mathcal{L}\left\{Q_{n}\right\}+\mathcal{L}\left\{R_{n}\right\}\right), \quad n\geq 1. \end{aligned}} $$

(38)

Finally, by applying inverse Laplace transformation we deduce the following recurrence formulas for each n=0,1,2,…,

$$ {{} \begin{aligned} \left\{ \begin{array}{ll} u_{0}(x,t)=f(x),\\ u_{n+1}(x,t)=&\!\!\!\!\!\!-\mathcal{L}^{-1}\left[\frac{1}{s}\mathcal{L}\{{Ru}_{n}(x,t)+P_{n}(u_{0},\ldots, u_{n})\right.\\ &\left.+Q_{n}(u_{0},\ldots, u_{n})+R_{n}(u_{0},\ldots, u_{n})\}{\vphantom{\frac{1}{s}}}\right]. \end{array} \right. \end{aligned}} $$

(39)

Numerical simulations and graphical results

We perform numerical simulations for bright and dark optical solitions.

Application to bright optical solitions

The result and the profile of four cases are shown in Table 1 and in Figs. 1, 2, 3 and 4.

Fig. 1

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 1 with |Max Error|=2.1×10⁻¹⁰

Fig. 2

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 2 with |Max Error|=3.0×10⁻¹⁰

Fig. 3

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 3 with |Max Error|=1.5×10⁻¹⁰

Fig. 4

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 4 with |Max Error|=1.0×10⁻¹⁰

Table 1 Bright optical solitons

Application to dark optical solitions

The result and the profile of four cases are shown in Table 2 and in Figs. 5, 6, 7 and 8.

Fig. 5

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 5 with |Max Error|=2.5×10⁻¹⁰

Fig. 6

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 6 with |Max Error|=2.5×10⁻¹⁰

Fig. 7

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 7 with |Max Error|=1.0×10⁻¹⁰

Fig. 8

Dynamic evolution profile of |u|² via LADM (left) and contour plot of the wave amplitude of |u|² (right) for the values of the parameters used in case 8 with |Max Error|=1.5×10⁻¹⁰

Table 2 Dark optical solitons

Conclusions

This paper successfully studied FLE in polarization-preserving fibers by the aid of Laplace-Adomian decomposition scheme. The numerical scheme yielded bright and dark soliton solutions. The results thus appear with a complete spectrum of soliton solutions. Although singular solitons is a third form of solitons that emerge from this model, it does not provide any interest with any kind of numerical scheme. The results of the paper are truly encouraging to study the methodology further along. Later, this scheme will be applied to vector coupled FLE that studies solitons in birefringent fibers. Further along the model will be extended to address WDM/DWDM/UDWDM topology numerically. Such studies are currently under way.