
A coupled system of fractional order Gross-Pitaevskii equations is under consideration in which the time-fractional derivative is given in Caputo sense and the spatial fractional order derivative is of Riesz type. This kind of model may shed light on some time-evolution properties of the rotating two-component Bose¢ Einstein condensates. An unconditional convergent high-order scheme is proposed based on L2-1σ finite difference approximation in the time direction and Galerkin Legendre spectral approximation in the space direction. This combined scheme is designed in an easy algorithmic style. Based on ideas of discrete fractional Grönwall inequalities, we can prove the convergence theory of the scheme. Accordingly, a second order of convergence and a spectral convergence order in time and space, respectively, without any constraints on temporal meshes and the specified degree of Legendre polynomials N. Some numerical experiments are proposed to support the theoretical results.
Citation: A.S. Hendy, R.H. De Staelen, A.A. Aldraiweesh, M.A. Zaky. High order approximation scheme for a fractional order coupled system describing the dynamics of rotating two-component Bose-Einstein condensates[J]. AIMS Mathematics, 2023, 8(10): 22766-22788. doi: 10.3934/math.20231160
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A coupled system of fractional order Gross-Pitaevskii equations is under consideration in which the time-fractional derivative is given in Caputo sense and the spatial fractional order derivative is of Riesz type. This kind of model may shed light on some time-evolution properties of the rotating two-component Bose¢ Einstein condensates. An unconditional convergent high-order scheme is proposed based on L2-1σ finite difference approximation in the time direction and Galerkin Legendre spectral approximation in the space direction. This combined scheme is designed in an easy algorithmic style. Based on ideas of discrete fractional Grönwall inequalities, we can prove the convergence theory of the scheme. Accordingly, a second order of convergence and a spectral convergence order in time and space, respectively, without any constraints on temporal meshes and the specified degree of Legendre polynomials N. Some numerical experiments are proposed to support the theoretical results.
Hydraulic jumps are frequently observed in lab studies, river flows, and coastal environments. The shallow water equations, commonly known as Saint-Venant equations, have important applications in oceanography and hydraulics. These equations are used to represent fluid flow when the depth of the fluid is minor in comparison to the horizontal scale of the flow field fluctuations [1]. They have been used to simulate flow at the atmospheric and ocean scales, and they have been used to forecast tsunamis, storm surges, and flow around constructions, among other things [2,3]. Shallow water is a thin layer of constant density fluid in hydrostatic equilibrium that is bordered on the bottom by a rigid surface and on the top by a free surface [4].
Nonlinear waves have recently acquired importance due to their capacity to highlight several complicated phenomena in nonlinear research with spirited applications [5,6,7,8]. Teshukov in [9] developed the equation system that describes multi-dimensional shear shallow water (SSW) flows. Some novel solitary wave solutions for the ill-posed Boussinesq dynamic wave model under shallow water beneath gravity were constructed [10]. The effects of vertical shear, which are disregarded in the traditional shallow water model, are included in this system to approximate shallow water flows. It is a non-linear hyperbolic partial differential equations (PDE) system with non-conservative products. Shocks, rarefactions, shear, and contact waves are all allowed in this model. The SSW model can capture the oscillatory character of turbulent hydraulic leaps, which corrects the conventional non-linear shallow water equations' inability to represent such occurrences [11]. Analytical and numerical techniques for solving such problems have recently advanced; for details, see [12,13,14,15,16,17] and the references therein.
The SSW model consists of six non-conservative hyperbolic equations, which makes its numerical solution challenging since the concept of a weak solution necessitates selecting a path that is often unknown. The physical regularization mechanism determines the suitable path, and even if one knows the correct path, it is challenging to construct a numerical scheme that converges to the weak solution since the solution is susceptible to numerical viscosity [18].
In the present work, we constructed the generalized Rusanov (G. Rusanov) scheme to solve the SSW model in 1D of space. This technique is divided into steps for predictors and correctors [19,20,21,22,23]. The first one includes a numerical diffusion control parameter. In the second stage, the balance conservation equation is retrieved. Riemann solutions were employed to determine the numerical flow in the majority of the typical schemes. Unlike previous schemes, the interesting feature of the G. Rusanov scheme is that it can evaluate the numerical flow even when the Riemann solution is not present, which is a very fascinating advantage. In actuality, this approach may be applied as a box solver for a variety of non-conservative law models.
The remainder of the article is structured as follows. Section 2 offers the non-conservative shear shallow water model. Section 3 presents the structure of the G. Rusanov scheme to solve the 1D SSW model. Section 4 shows that the G. Rusanov satisfies the C-property. Section 5 provides several test cases to show the validation of the G. Rusanov scheme versus Rusanov, Lax-Friedrichs, and reference solutions. Section 6 summarizes the work and offers some conclusions.
The one-dimensional SSW model without a source term is
∂W∂t+∂F(W)∂x+K(W)∂h∂x=S(W), | (2.1) |
W=(hhv1hv2E11E12E22),F(W)=(hv1R11+hv21+gh22R12+hv1v2(E11+R11)v1E12v1+12(R11v2+R12v1)E22v1+R12v2), |
K(W)=(000ghv112ghv20),S(W)=(0−gh∂B∂x−Cf|v|v1−Cf|v|v2−ghv1∂B∂x+12D11−Cf|v|v21−12ghv2∂B∂x+12D12−Cf|v|v1v212D22−Cf|v|v22), |
while R11 and R12 are defined by the following tensor Rij=hpij, and also, E11, E12 and E22 are defined by the following tensor Eij=12Rij+12hvivj with i≥1,j≤2. We write the previous system 2.1 in nonconservative form with non-dissipative (Cf=0,D11=D12=D22=0), see [24], which can be written as follows
∂W∂t+(∇F(W)+C(W))∂W∂x=S1(W). | (2.2) |
Also, we can write the previous system as the following
∂W∂t+A(W)∂W∂x=S1(W) | (2.3) |
with
A(W)=[010000gh00200000020−3E11v1h+2v31+ghv23E11h−3v2103v100−2E12v1h−E11v2h+2v21v2+ghv222E12h−2v1v2E11h−v21v22v10−E22v1h−2E12v2h+v22v1E22h+v222E12h−2v2v102v2v1] |
and
S1(W)=(0−gh∂B∂x0−ghv1∂B∂x−12ghv2∂B∂x0). |
System (2.3) is a hyperbolic system and has the following eigenvalues
λ1=λ2=v1,λ3=v1−√2E11h−v21,λ4=v1+√2E11h−v21, |
λ5=v1−√gh+3(v21−2E11h),λ6=v1+√gh+3(v21−2E11h). |
In order deduce the G. Rusanov scheme, we rewrite the system (2.1) as follows
∂W∂t+∂F(W)∂x=−K(W)∂h∂x+S1(W)=Q(W). | (3.1) |
Integrating Eq (3.1) over the domain [tn,tn+1]×[xi−12,xi+12] gives the finite-volume scheme
Wn+1i=Wni−ΔtΔx(F(Wni+1/2)−F(Wni−1/2))+ΔtQin | (3.2) |
in the interval [xi−1/2,xi+1/2] at time tn. Wni represents the average value of the solution W as follows
Wni=1Δx∫xi+1/2xi−1/2W(tn,x)dx, |
and F(Wni±1/2) represent the numerical flux at time tn and space x=xi±1/2. It is necessary to solve the Riemann problem at xi+1/2 interfaces due to the organization of the numerical fluxes. Assume that for the first scenario given below, there is a self-similar Riemann problem solution associated with Eq (3.1)
W(x,0)={WL,ifx<0,WR,ifx>0 | (3.3) |
is supplied by
W(t,x)=Rs(xt,WL,WR). | (3.4) |
The difficulties with discretization of the source term in (3.2) could arise from singular values of the Riemann solution at the interfaces. In order to overcome these challenges and reconstruct a Wni+1/2 approximation, we created a finite-volume scheme in [19,20,21,22,23,25,26,27] for numerical solutions of conservation laws including source terms and without source terms. The principal objective here is building the intermediate states Wni±1/2 to be utilized in the corrector stage (3.2). The following is obtained by integrating Eq (3.1) through a control volume [tn,tn+θni+1/2]×[x−,x+], that includes the point (tn,xi+1/2), with the objective to accomplish this:
∫x+x−W(tn+θni+1/2,x)dx=Δx−Wni+Δx+Wni+1−θni+1/2(F(Wni+1)−F(Wni))+θni+1/2(Δx−−Δx+)Qni+12 | (3.5) |
with Wni±1/2 denoting the approximation of Riemann solution Rs across the control volume [x−,x+] at time tn+θni+1/2. While calculating distances Δx− and Δx+ as
Δx−=|x−−xi+1/2|,Δx+=|x+−xi+1/2|, |
Qni+12 closely resembles the average source term Q and is given by the following
Qni+12=1θni+12(Δx−+Δx+)∫tn+θni+12tn∫x+x−Q(W)dtdx. | (3.6) |
Selecting x−=xi, x+=xi+1 causes the Eq (3.5) to be reduced to the intermediate state, which given as follows
Wni+1/2=12(Wni+Wni+1)−θni+1/2Δx(F(Wni+1)−F(Wni))+θni+12Qni+12, | (3.7) |
where the approximate average value of the solution W in the control domain [tn,tn+θni+1/2]×[xi,xi+1] is expressed by Wni+1/2 as the following
Wni+1/2=1Δx∫xi+1xiW(x,tn+θni+1/2)dx | (3.8) |
by selecting θni+1/2 as follows
θni+1/2=αni+1/2ˉθi+1/2,ˉθi+1/2=Δx2Sni+1/2. | (3.9) |
This choice is contingent upon the results of the stability analysis[19]. The following represents the local Rusanov velocity
Sni+1/2=maxk=1,...,K(max(∣λnk,i∣,∣λnk,i+1∣)), | (3.10) |
where αni+1/2 is a positive parameter, and λnk,i represents the kth eigenvalues in (2.3) evaluated at the solution state Wni. Here, in our case, k=6 for the shear shallow water model. One can use the Lax-Wendroff technique again for αni+1/2=ΔtΔxSni+1/2. Choosing the slope αni+1/2=˜αni+1/2, the proposed scheme became a first-order scheme, where
˜αni+1/2=Sni+1/2sni+1/2, | (3.11) |
and
sni+1/2=mink=1,...,K(max(∣λnk,i∣,∣λnk,i+1∣)). | (3.12) |
In this case, the control parameter can be written as follows:
αni+1/2=˜αni+1/2+σni+1/2Φ(rmi+1/2), | (3.13) |
where ˜αni+1/2 is given by (3.11), and Φi+1/2=Φ(ri+1/2) is a function that limits the slope. While for
ri+1/2=Wi+1−q−Wi−qWi+1−Wi,q=sgn[F′(Xn+1,Wni+1/2)] |
and
σni+1/2=ΔtΔxSni+1/2−Sni+1/2sni+1/2. |
One may use any slope limiter function, including minmod, superbee, and Van leer [28] and [29]. At the end, the G. Rusanov scheme for Eq (2.3) can be written as follows
{Wni+12=12(Wni+Wni+1)−αni+122Snj+12[F(Wni+1)−F(Wni)]+αni+122Snj+12Qni+12,Wn+1i=Wni−rn[F(Wni+12)−F(Wni−12)]+ΔtnQin. | (3.14) |
With a definition of the C-property [30], the source term in (2.1) is discretized in the G. Rusanov method in a way that is well-balanced with the discretization of the flux gradients. According to [30,31], if the following formulas hold, a numerical scheme is said to achieve the C-property for the system (3.1).
(hp11)n= constant,hn+B= constantandvn1=vn2=0. | (4.1) |
When we set v1=v2=0 in the stationary flow at rest, we get system (3.1), which can be expressed as follows.
∂∂t(h0012hp1112hp1212hp22)+∂∂x(0hp11+12gh2hp12000)=(0−gh∂B∂x0000)=Q(x,t). | (4.2) |
We can express the predictor stage (3.14) as follows after applying the G. Rusanov scheme to the previous system
Wni+12=(12(hni+hni+1)−αni+124Sni+12(hni+hni+1)[(hni+1+Bi+1)−(hni+Bi)]−αni+122Sni+12((hp11)ni+1−(hp11)ni−αni+122Sni+12((hp12)ni+1−(hp12)ni)14((hp11)ni+1+(hp11)ni)14((hp12)ni+1+(hp12)ni)14((hp22)ni+1+(hp22)ni)). | (4.3) |
Also, we can write the previous equations as follows
Wni+12=(hni+120−αni+122Sni+12((hp12)ni+1−(hp12)ni)12(hp11)ni+1212(hp12)ni+1212(hp22)ni+12), | (4.4) |
and the stage of the corrector updates the solution to take on the desired form.
((h)n+1i(hv1)n+1i(hv2)n+1i(E11)n+1i(E12)n+1i(E22)n+1i)=((h)ni(hv1)ni(hv2)ni(E11)ni(E12)ni(E22)ni)−ΔtnΔx(0g2((hni+12)2−(hni−12)2)(hp12)ni+12−(hp12)ni−12000) | (4.5) |
+(0ΔtnQni0000). |
The solution is stationary when Wn+1i=Wni and this leads us to rewrite the previous system (4.5) as follows
Δtn2Δxg((hni+12)2−(hni−12)2)−ΔtnQni. |
This lead to the following
Qni=−g8Δx(hni+1+2hni+hni−1)(Bi+1−Bi−1). | (4.6) |
Afterward, when the source term in the corrector stage is discretized in the earlier equations, this leads to the G. Rusanov satisfying the C-property.
In order to simulate the SSW system numerically, we provide five test cases without a source term using the G. Rusanov, Rusanov, and Lax-Friedrichs schemes to illustrate the effectiveness and precision of the suggested G. Rusanov scheme. The computational domain for all cases is L=[0,1] divided into 300 gridpoints, and the final time is t=0.5s, except for test case 2, where the final time is t=10s. We evaluate the three schemes with the reference solution on the extremely fine mesh of 30000 cells that was produced by the traditional Rusanov scheme. Also, we provide one test case with a source term using the G. Rusanov scheme in the domain [0,1] divided into 200 gridpoints and final time t=0.5. We select the stability condition [19] in the following sense
Δt=CFLΔxmaxi(|αni+12Sni+12|), | (5.1) |
where a constant CFL=0.5.
This test case was studied in [24] and [32], and the initial condition is given by
(h,v1,v2,p11,p22,p12)={(0.01,0.1,0.2,0.04,0.04,1×10−8)ifx≤L2,(0.02,0.1,−0.2,0.04,0.04,1×10−8)ifx>L2. | (5.2) |
The solution include five waves, which are represented by 1− shock and 6− rarefaction. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells. Figures 1–3 show the numerical results and variation of parameter of control. We note that all waves are captured by this scheme and the numerical solution agrees with the reference solution. Table 1 shows the CPU time of computation for the three schemes by using a Dell i5 laptop, CPU 2.5 GHZ.
Scheme | G. Rusanov | Rusanov | Lax-Friedrichs |
CPU time | 0.068005 | 0.056805 | 0.0496803 |
This test case (the shear waves problem) was studied in [24] and [32], and the initial condition is given by
(h,v1,v2,p11,p22,p12)={(0.01,0,0.2,1×10−4,1×10−4,0)ifx≤L2,(0.01,0,−0.2,1×10−4,1×10−4,0)ifx>L2. | (5.3) |
The solution is represented by two shear waves with only transverse velocity discontinuities, the p12 and p22 elements of a stress tensor. We compare the numerical results by G. Rusanov, Rusanov, and Lax-Friedrichs with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=10s, see Figures 4 and 5. We observe that Figure 5 displays a spurious rise in the central of the domain of computation, which has also been seen in the literature using different methods, see [24,32].
This test case was studied in [24] with the following initial condition
(h,v1,v2,p11,p22,p12)={(0.02,0,0,4×10−2,4×10−2,0)ifx≤L2,(0.01,0,0,4×10−2,4×10−2,0)ifx>L2. | (5.4) |
The solution for h, v1, and p11 consists of two shear rarefaction waves, one moving to the right and the other moving to the left, and a shock wave to the right. See Figures 6 and 7 which show the behavior of the height of the water, velocity, pressure, and variation of the parameter of control.
We take the same example, but with another variant of the modified test case, where p12=1×10−8 is set to a small non-zero value. We notice that the behavior of h, v1, and p11 is the same, but there is a change in the behavior of p12 such that it displays all of the five waves (four rarefaction and one shock) of the shear shallow water model, see Figures 8 and 9.
This test case was studied in [24] with the following initial condition
(h,v1,v2,p11,p22,p12)={(0.02,0,0,1×10−4,1×10−4,0)ifx≤L2,(0.03,−0.221698,0.0166167,1×10−4,1×10−4,0)ifx>L2. | (5.5) |
The solution for this test case consists of a single shock wave. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=0.5s. Figures 10 and 11 show the numerical results, and we note that all waves are captured by this scheme and the numerical solution agrees with the reference solution, but the solution of p11 does not agree with the exact solution [24]. There is an oscillation with Lax-Friedrichs scheme in the water height h and the pressure p11.
This test case (the shear waves problem) was studied in [24] and [32] with the following initial condition
(h,v1,v2,p11,p22,p12)={(0.02,0,0,1×10−4,1×10−4,0)ifx≤L2,(0.01,0,0,1×10−4,1×10−4,0)ifx>L2. | (5.6) |
The solution of this test case has a single shock wave and a single rarefaction wave, separated by a contact discontinuity. We compare the numerical results with the reference solution, which is calculated with the Rusanov scheme with very fine mesh of 30000 cells and a final time t=0.5s. Figures 12 and 13 show the numerical results, and we note that all waves are captured by this scheme and the numerical solution agrees with the reference solution, but the solution of p11 does not agree with the reference solution [24].
In this test case, we take the previous test case 3 and we added the discontinuous fond topography with the following initial condition
(h,v1,v2,p11,p22,p12,B)={(0.02,0,0,4×10−2,4×10−2,1×10−8,0)ifx≤L2,(0.01,0,0,4×10−2,4×10−2,1×10−8,0.01)ifx>L2. | (5.7) |
We simulate this test case with the G. Rusanov scheme with 200 gridpoints on the domain L=[0,1] at the final time t=0.5s, and we note that the behavior of the solution for h consists of one shear rarefaction wave moving to the left, a contact discontinuity after that two shear rarefaction waves, one moving to the right and the other moving to the left (see the left side of Figure 14. The right side of the Figure 14 shows the behavior of the velocity v1, which it consists of a rarefaction wave, a contact discontinuity after that, and two shear rarefactions. The left side of Figure 14 displays the behavior of the velocity v1. It is composed of two shear rarefactions followed by a contact discontinuity and three rarefaction waves moving to the right. The the right side of Figure 14 displays the behavior of the velocity v2. It is composed of two shear rarefactions moving to the left followed by a contact discontinuity after that, and two rarefaction waves moving to the right.
In summary, we have reported five numerical examples to solve the SSW model. Namely, we implemented the G. Rusanov, Rusanov, and Lax-Friedrichs schemes. We also compared the numerical solutions with the reference solution obtained by the classical Rusanov scheme on the very fine mesh of 30000 gridpoints. The three schemes were capable of capturing shock waves and rarefaction. Also, we have given the last numerical test with a source term. Finally, we discovered that the G. Rusanov scheme was more precise than the Rusanov and Lax-Friedrichs schemes.
The current study is concerned with the SSW model, which is a higher order variant of the traditional shallow water model since it adds vertical shear effects. The model features a non-conservative structure, which makes numerical solutions problematic. The 1D SSW model was solved using the G. Rusanov technique. We clarify that this scheme satisfied the C-property. Several numerical examples were given to solve the SSW model using the G. Rusanov, Rusanov, Lax-Friedrichs, and reference solution techniques. The simulations given verified the G. Rusanov technique's high resolution and validated its capabilities and efficacy in dealing with such models. This approach may be expanded in a two-dimensional space.
H. S. Alayachi: Conceptualization, Data curation, Formal analysis, Writing - original draft; Mahmoud A. E. Abdelrahman: Conceptualization, Data curation, Formal analysis, Writing - original draft; K. Mohamed: Conceptualization, Software, Formal analysis, Writing - original draft.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number 445-9-753.
The authors declare that they have no competing interests.
[1] | M. Abbaszadeh, M. Dehghan, Y Zhou, Crank–nicolson/galerkin spectral method for solving two-dimensional time-space distributed-order weakly singular integro-partial differential equation, J. Comput. Appl. Math., 374 (2020), 112739. |
[2] |
M. Ainsworth, Z. Mao, Analysis and approximation of gradient flows associated with a fractional order gross–pitaevskii free energy, Commun. Appl. Math. Comput., 1 (2019), 5–19. https://doi.org/10.1007/s42967-019-0008-9 doi: 10.1007/s42967-019-0008-9
![]() |
[3] |
A. A. Alikhanov, A new difference scheme for the time fractional diffusion equation. J. Comput. Phys., 280 (2015), 424–438. https://doi.org/10.1016/j.jcp.2014.09.031 doi: 10.1016/j.jcp.2014.09.031
![]() |
[4] |
M. H. Anderson, J. R. Ensher, M. R. Matthews, C. E. Wieman, E. A. Cornell, Observation of Bose-Einstein condensation in a dilute atomic vapor, Science, 269 (1995), 198–201. https://doi.org/10.1126/science.269.5221.198 doi: 10.1126/science.269.5221.198
![]() |
[5] |
X. Antoine, W. Bao, C. Besse, Computational methods for the dynamics of the nonlinear schrödinger/gross–pitaevskii equations, Comput. Phys. Commun., 184 (2013), 2621–2633. https://doi.org/10.1016/j.cpc.2013.07.012 doi: 10.1016/j.cpc.2013.07.012
![]() |
[6] |
X. Antoine, R. Duboscq, Modeling and computation of bose-einstein condensates: Stationary states, nucleation, dynamics, stochasticity, Nonlinear Optical and Atomic Systems: at the Interface of Physics and Mathematics, 2015, 49–145. https://doi.org/10.1016/j.endm.2015.06.022 doi: 10.1016/j.endm.2015.06.022
![]() |
[7] |
X. Antoine, Q. Tang, J, Zhang, On the numerical solution and dynamical laws of nonlinear fractional schrödinger/gross–pitaevskii equations, Int. J. Comput. Math., 95 (2018), 1423–1443. https://doi.org/10.1080/00207160.2018.1437911 doi: 10.1080/00207160.2018.1437911
![]() |
[8] | W. Bao, Y. Cai, Mathematical theory and numerical methods for bose-einstein condensation, Kinet. Relat. Mod., 6 (2013), 1. |
[9] |
B. Cheng, Z. Guo, D. Wang, Dissipativity of semilinear time fractional subdiffusion equations and numerical approximations, Appl. Math. Lett., 86 (2018), 276–283. https://doi.org/10.1016/j.aml.2018.07.006 doi: 10.1016/j.aml.2018.07.006
![]() |
[10] |
H. Ertik, H. Şirin, D. Demirhan, F. Büyükkiliç, Fractional mathematical investigation of Bose–Einstein condensation in dilute 87 Rb, 23 Na and 7 Li atomic gases, Int. J. Mod. Phys. B, 26 (2012), 1250096. https://doi.org/10.1142/S0217984912500960 doi: 10.1142/S0217984912500960
![]() |
[11] |
V. J. Ervin, J. P. Roop, Variational solution of fractional advection dispersion equations on bounded domains in Rd, Numer. Meth. Part. D. E., 23 (2007), 256–281. https://doi.org/10.1002/num.20169 doi: 10.1002/num.20169
![]() |
[12] | A. Griffin, D. W. Snoke, S. Stringari, Bose-einstein condensation. Cambridge University Press, 1996. |
[13] |
R. M. Hafez, M. A. Zaky, A. S. Hendy, A novel spectral Galerkin/Petrov–Galerkin algorithm for the multi-dimensional space–time fractional advection–diffusion–reaction equations with nonsmooth solutions, Math. Comput. Simulat., 190 (2021), 678–690. https://doi.org/10.1016/j.matcom.2021.06.004,2021 doi: 10.1016/j.matcom.2021.06.004,2021
![]() |
[14] |
A. S. Hendy, J. E. Macías-Díaz, A Conservative Scheme with Optimal Error Estimates for a Multidimensional Space–Fractional Gross–Pitaevskii Equation, Int. J. Appl. Math. Comput. Sci., 29 (2019), 713–723. https://doi.org/10.2478/amcs-2019-0053 doi: 10.2478/amcs-2019-0053
![]() |
[15] | A. S. Hendy, J. E. Macías-Díaz, A discrete grönwall inequality and energy estimates in the analysis of a discrete model for a nonlinear time-fractional heat equation, Mathematics, 8 (2020), 1539. |
[16] |
A. S. Hendy, M. A. Zaky, Global consistency analysis of l1-galerkin spectral schemes for coupled nonlinear space-time fractional schrödinger equations, Appl. Numer. Math., 156 (2020), 276–302. https://doi.org/10.1016/j.apnum.2020.05.002 doi: 10.1016/j.apnum.2020.05.002
![]() |
[17] | A. S. Hendy, M. A. Zaky, Graded mesh discretization for coupled system of nonlinear multi-term time-space fractional diffusion equations, Eng. Comput., 38 (2022), 1351–1363. |
[18] | A. S. Hendy, M. A. Zaky, R. M. Hafez, R. H. De Staelen, The impact of memory effect on space fractional strong quantum couplers with tunable decay behavior and its numerical simulation, Sci. Rep., 2021, Article number: 10275. https://doi.org/10.1038/s41598-021-89701-7 |
[19] |
P. Henning, A. Målqvist, The Finite Element Method for the Time-Dependent Gross–Pitaevskii Equation with Angular Momentum Rotation, SIAM J. Numer. Anal., 55 (2017), 923–952. https://doi.org/10.1137/15M1009172 doi: 10.1137/15M1009172
![]() |
[20] |
A. Jacob, P. G Juzeliūnas, L. Santos, Landau levels of cold atoms in non-Abelian gauge fields, New J. Phys., 10 (2008), 045022. https://doi.org/10.1088/1367-2630/10/4/045022 doi: 10.1088/1367-2630/10/4/045022
![]() |
[21] | X. Li, L. Zhang, A conservative sine pseudo-spectral-difference method for multi-dimensional coupled Gross–Pitaevskii equations, Adv. Comput. Math., 46 (2020), 1–30. |
[22] |
X. Liang, A. Q. M. Khaliq, H. Bhatt, K. M. Furati, The locally extrapolated exponential splitting scheme for multi-dimensional nonlinear space-fractional schrödinger equations, Numer. Algorithms, 76 (2017), 939–958. https://doi.org/10.1007/s11075-017-0291-3 doi: 10.1007/s11075-017-0291-3
![]() |
[23] |
F. Liao, L. Zhang, Optimal error estimates of explicit finite difference schemes for the coupled Gross–Pitaevskii equations, Int. J. Comput. Math., 95 (2018), 1874–1892. https://doi.org/10.1080/00207160.2017.1343942 doi: 10.1080/00207160.2017.1343942
![]() |
[24] |
H. Liao, W. McLean, J. Zhang, A discrete Grönwall inequality with applications to numerical schemes for subdiffusion problems, SIAM J. Numer. Anal., 57 (2019), 218–237. https://doi.org/10.1137/16M1175742 doi: 10.1137/16M1175742
![]() |
[25] | L. Pitaevskii, S. Stringari, Bose-Einstein condensation and superfluidity, 164 (2016), Oxford University Press. |
[26] | I. Podlubny, Fractional Differential Equations. An Introduction to Fractional Derivatives, Fractional Differential Equations, Some Methods of Their Solution and Some of Their Applications, Mathematics in science and engineering; v. 198. Academic Press, San Diego, 1999. |
[27] |
A. Serna-Reyes, J. E. Macías-Díaz, A. Gallegos, N. Reguera, Cmmse: analysis and comparison of some numerical methods to solve a nonlinear fractional gross–pitaevskii system, J. Math. Chem., 60 (2022), 1272–1286. https://doi.org/10.1007/s10910-022-01360-9 doi: 10.1007/s10910-022-01360-9
![]() |
[28] |
J. Shen, Efficient spectral-galerkin method I. direct solvers of second-and fourth-order equations using legendre polynomials, SIAM J. Sci. Comput., 15 (1994), 1489–1505. https://doi.org/10.1137/0915089 doi: 10.1137/0915089
![]() |
[29] | J. Shen, T. Tang, L. Wang, Spectral Methods: Algorithms, Analysis and Applications, 41 (2011), Springer Science & Business Media. |
[30] |
Z. Sun, D. Zhao, On the L∞ convergence of a difference scheme for coupled nonlinear Schrödinger equations, Comput. Math. Appl., 59 (2010), 3286–3300. https://doi.org/10.1016/j.camwa.2010.03.012 doi: 10.1016/j.camwa.2010.03.012
![]() |
[31] |
N. Uzar, S. Ballikaya, Investigation of classical and fractional Bose–Einstein condensation for harmonic potential, Physica A, 392 (2013), 1733–1741. https://doi.org/10.1016/j.physa.2012.11.039 doi: 10.1016/j.physa.2012.11.039
![]() |
[32] | N. Uzar, D. Han, E. Aydiner, T. Tufekci, E. Aydıner, Solutions of the Gross-Pitaevskii and time-fractional Gross-Pitaevskii equations for different potentials with Homotopy Perturbation Method, arXiv preprint arXiv: 1203.3352, 2012. |
[33] |
T. Wang, Optimal point-wise error estimate of a compact difference scheme for the coupled Gross–Pitaevskii equations in one dimension, J. Sci. Comput., 59 (2014), 158–186. https://doi.org/10.1007/s10915-013-9757-1 doi: 10.1007/s10915-013-9757-1
![]() |
[34] | Y. Wang, F. Liu, L. Mei, V. V. Anh, A novel alternating-direction implicit spectral galerkin method for a multi-term time-space fractional diffusion equation in three dimensions, Numer. Algorithms, 2020. |
[35] |
M. A. Zaky, A. S. Hendy, Convergence analysis of an L1-continuous Galerkin method for nonlinear time-space fractional Schrödinger equations, Int. J. Comput. Math., 98 (2021), 1420–1437. https://doi.org/10.1080/00207160.2020.1822994 doi: 10.1080/00207160.2020.1822994
![]() |
[36] | M. A. Zaky, A. S. Hendy, J. E. Macías-Díaz, Semi-implicit galerkin–legendre spectral schemes for nonlinear time-space fractional diffusion–reaction equations with smooth and nonsmooth solutions, J. Sci. Comput., 82 (2020), Article number: 13. |
[37] |
F. Zeng, F. Liu, C. Li, K. Burrage, I. Turner, V. Anh, A crank–nicolson adi spectral method for a two-dimensional riesz space fractional nonlinear reaction-diffusion equation, SIAM J. Numer. Anal., 52 (2014), 2599–2622. https://doi.org/10.1137/130934192 doi: 10.1137/130934192
![]() |
[38] | H. Zhang, X. Jiang, C. Wang, W. Fan, Galerkin-legendre spectral schemes for nonlinear space fractional schrödinger equation, Numer. Algorithms, 79 (2018), 337–356. |
[39] | R. Zhang, Z. Han, Y. Shao, Z. Wang, Y. Wang, The numerical study for the ground and excited states of fractional bose–einstein condensates, Comput. Math. Appl., 78 (2019), 1548–1561. |
[40] |
Y. Zhang, W. Bao, H. Li, Dynamics of rotating two-component Bose–Einstein condensates and its efficient computation, Physica D., 234 (2007), 49–69. https://doi.org/10.1016/j.physd.2007.06.026 doi: 10.1016/j.physd.2007.06.026
![]() |
1. | Georges Chamoun, Finite Volume Analysis of the Two Competing-species Chemotaxis Models with General Diffusive Functions, 2025, 22, 2224-2902, 232, 10.37394/23208.2025.22.24 |
Scheme | G. Rusanov | Rusanov | Lax-Friedrichs |
CPU time | 0.068005 | 0.056805 | 0.0496803 |