1. Introduction
The nonlinear Schrödinger equation (NLS) was raised by Feynman and Hibbs from the path integral over the Brownian paths [
1], which presents an effective model for describing the quantum state of physical systems. The space-fractional NLS was generated by Laskin via extending the Feynman path integral to a novel path integral over the Lévy quantum mechanical paths, which opens a new perspective for quantum mechanics and can characterize many new phenomena absent from the classical NLS [
2,
3]. The fractional NLS plays an important role in mathematical physics and it is ubiquitous in various fields as diverse as quantum optics, water wave dynamics [
4], beam propagation inside crystals, the study of Boson–Einstein condensation, and the continuum limit with long-range lattice interaction [
5]. The space-fractional NLS on 2D domains appears as follows:
with
and real numbers
,
,
,
, and
is the Riesz fractional derivative with respect to
x [
6]:
with
and
being the
-th left- and right-hand Riemann–Liouville derivatives of
x, respectively, and
is similarly defined. The fractional NLS happens to be the classical cubic NLS when
, which is necessary to characterize the evolution of nonrelativistic systems and can provide a detailed description of the true nature of the microscopic events in a probabilistic sense.
The space-fractional NLS and CNLS have been of great interest over recent years. However, due to their nonlocal fractional operators involved in space, solving them numerically appears extremely challenging, so the existent algorithms still remain limited for high-dimensional problems. There are many research works devoted to studying the 1D space-fractional NLS, but fewer works investigate the numerical approaches for the high-dimensional space-fractional NLS/CNLS. Amore et al. derived a simple collocation method based on little Sinc functions for the quantum mechanical equation involving the fractional Laplacian [
7]. Herzallaha and Gepreel developed an adomian decomposition method to solve the time–space-fractional NLS [
8]. In [
9,
10,
11], several second-order finite difference (FD) methods have been established for the 1D single and coupled space-fractional NLS, where the mass and energy conservation properties are rigorously discussed. The Fourier spectral method was first proposed by Klein et al. to study the finite time blow-up, the stability of nonlinear ground states and the long-time behavior of solutions in classical or semiclassical settings [
12]. Such a spectral method was further investigated by Duo and Zhang for the 1D space-fractional NLS in a semiclassical regime with the split step, Crank–Nicolson and relaxation schemes being used in time [
13]. In [
14,
15,
16], the linearized Galerkin FE schemes for the space-fractional NLS and CNLS on 1D domains were developed. In [
17], we proposed an implicit FE scheme to solve the 1D time–space-fractional equations of NLS type and further extended this scheme to the 2D situation. Li et al. gave a fast linearized conservative FE scheme for the 1D strongly space-fractional CNLS [
18]. Fan and Qi proposed an efficient FE method for the 2D time–space-fractional NLS [
19]. In [
20], Aboelenen constructed a high-order nodal discontinuous Galerkin FE method for the 1D space-fractional problem of NLS type.
Aside from the difficulty in designing the algorithm to approximate the fractional derivatives in high dimensions, another main concern about the construction of numerical schemes for the fractional NLS and CNLS is how to efficiently discretize the nonlinear terms. A wealth of experience has shown that the split-step method is one of the important approaches to solve high-dimensional nonlinear problems, which is linearized and can reduce the computational cost and memory requirement. A few works have been devoted to this area. Wang and Huang developed a split-step conservative ADI FD method for the 2D space-fractional NLS [
21], which solves the problem without any iteration by splitting the governing equation into linear and nonlinear subparts. Along the same line, a high-order split-step FD method for the 1D space-fractional CNLS was proposed in [
22]. Recently, Wang et al. considered the semiclassical linear space-fractional Schrödinger equation by a Lie–Trotter operator splitting spectral method [
23]. In [
24], Aboelenen proposed a split-step Fourier pseudo-spectral scheme for the 1D space-fractional CNLS. Wang et al. developed a split-step spectral Galerkin scheme for 2D space-fractional NLS [
25].
In this work, we consider the 2D space-fractional CNLS
with the real numbers
,
,
and
. When
, the above problem degenerates to the single fractional NLS, which preserves
along with the time evolution [
21], where
is the conjugate of
u.
Although the spectral Galerkin method based on orthogonal polynomials is a kind of high-accuracy technique, it has a strict limit on computational domains, which are usually multiplicative rectangular regions. Besides, it requires high regularity for the model problem. The FE method is a high-performing and commonly used algorithm for complex domain problems with unstructured meshes in scientific and engineering computing, which can achieve high accuracy with lower regularity, but due to the nonlocality of fractional derivative operators, seldom works have been reported on this method for the high-dimensional space-fractional NLS and CNLS. Inspired by this, we try to establish an efficient split-step Galerkin FE scheme for the 2D space-fractional CNLS (
4)–(7). The mass conservation property is proved and the convergence is also analyzed. The proposed method is utilized to simulate these problems on unstructured meshes, and no internal iteration is required at each time layer, thereby greatly reducing the computational complexity.
The outline is as follows. In
Section 2, some preliminaries are introduced, and in
Section 3, the variational formulation is derived. In
Section 4, we engage in a detailed derivative course of the split-step FE scheme for Equations (
4)–(7) and further analyze its mass conservation property and error estimates. In
Section 5, a numerical study on the dynamics of NLS and CNLS involving fractional derivatives is conducted, and a short conclusion is made lastly.
2. Preliminaries
We recall some auxiliary definitions and results about the fractional derivatives. If
is smooth enough, the
-th left-hand Riemann–Liouville derivative is defined by
and
-th right-hand Riemann–Liouville derivative is defined by
where
,
and
.
Another commonly used fractional derivative is called the Riesz derivative:
and similarly, we can define the fractional derivatives with regard to
y.
Meanwhile, letting
,
and
, we denote
by
,
by
and
,
by
with
. For a real-valued
on
, we define the following fractional derivative spaces [
26,
27]:
Definition 1. Letting
, we define the left seminormand left normand let
be the closure of
with respect to
. Definition 2. Letting
, we define the right seminormand right normand let
be the closure of
with respect to
. Definition 3. Letting
and
be the Fourier transform of u defined in Ω
, i.e.,we define the seminormand normand denote the closure of
with respect to
by
, where
and
is the extension of u by zero outside of Ω
. Similar to
,
and
, we define
,
and
by the closures of
with respect to
,
and
, respectively. If
,
,
,
and
are equivalent with the equivalent seminorms and norms, i.e.,
where
and
and
are two positive constants independent of
u.
Lemma 1. Letting
, we have the below identities in the
-nrom sense: Proof. Firstly, according to [
27], we have
with
. Then, from
and the property of Fourier transform, it follows that
and the similar result
Consequently, we come to Equation (
8) by summing these equations together, and Equation (9) can be easily deduced in the same way as above. □
Moreover, for any
, we have
, and for
,
,
, there holds
, which are the well-known fractional Poincaré–Friedrichs inequalities, where C is a positive constant independent of u. For any
or
and
, the similar inequalities can be validated, such as
,
.
3. Variational Formulation
To derive the weak problem, we define the energy norm
and introduce a family of regular triangular subdivisions
of
with the meshsize
h. Also, for
or
, we have
and the analogous results hold for
,
[
26].
Rewrite
u and
v in Equations (
4)–(7) by their real and imaginary parts, i.e.,
,
, and introduce the symmetric bilinear form:
which satisfies the coercivity and continuity properties:
Using the property (
10) and splitting
u and
v, the weak problem can be defined as follows: find
to fulfill
with
and
, subjected to
Denoting the set of polynomials of degree not greater than
on element
K by
, we define the FE subspace
on
as follows:
Then, the semidiscrete FE scheme is defined as follows: find
, such that
with
subjected to
where
,
,
and
are the appropriate approximations of
,
,
and
, respectively.
The semidiscrete FE scheme (
19)–(24) preserves the mass, i.e.,
and
. By taking
and
, the sum of Equations (
19)–(20) and the symmetry of bilinear form give the conservation property of
u, and the result with respect to
v followed by a similar procedure.
6. Conclusions
The high-dimensional space-fractional CNLS is a coupled nonlinear system, and its main difficulty comes from the nonlocality of fractional derivatives. This paper considered a split-step Galerkin FE scheme for the 2D space-fractional CNLS, and the proposed method is particularly adequate for solving this type of equation. The designed split-step FE scheme avoids solving nonlinear algebraic equations and can effectively reduce computational burden in practice. We also studied its mass conservation property in a discrete sense and unconditional convergence. The algorithm was evaluated by a constructive numerical test and the simulation of a double solitons collision and plane wave on unstructured meshes. The numerical outcomes and comparison with the pure Crank–Nicolson FE method with Newton’s iteration have illustrated its superiority and capacity.
The fractional NLS extends the application scope of classical NLS, and it tremendously enriches the connotation of quantum mechanics. The nonlocal convolution structure in fractional derivatives brings forward a great challenge in numerical simulation. Hence, an efficient numerical technique like our method can not only help to study the inner mechanisms of a microscopic quantum system but also play a certain role in increasing the popularity of fractional NLS/CNLS, and this would indirectly promote the upgrading of technological products. For example, we can study how a light beam travels in a fractional diffraction system in a numerical sense to provide a reference for the production of highly sensitive optical switches, optical devices, beam splitters, etc. Moreover, it is worth mentioning that artificial neural networks have also recently emerged as a promising alternative to simulate the systems involving fractional calculus [
34,
35,
36,
37]. As a kind of artificial intelligence algorithm, they have many advantages, such as strong fault tolerance and robustness for all quantitative applications and sensibility to spatial dimensions. We believe that they can be extended to simulate the high-dimensional space-fractional CNLS as well and would possess strong competitiveness as compared to the existing methods for our algorithm. We will consider this interesting topic in the future.