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在模拟从普通次扩散到超扩散的转变过程中,具有关于另一个函数的分数阶Caputo时间导数的次扩散方程。

Subdiffusion equation with fractional Caputo time derivative with respect to another function in modeling transition from ordinary subdiffusion to superdiffusion.

作者信息

Kosztołowicz Tadeusz

机构信息

Institute of Physics, Jan Kochanowski University, Uniwersytecka 7, 25-406 Kielce, Poland.

出版信息

Phys Rev E. 2023 Jun;107(6-1):064103. doi: 10.1103/PhysRevE.107.064103.

DOI:10.1103/PhysRevE.107.064103
PMID:37464604
Abstract

We use a subdiffusion equation with fractional Caputo time derivative with respect to another function g (g-subdiffusion equation) to describe a smooth transition from ordinary subdiffusion to superdiffusion. Ordinary subdiffusion is described by the equation with the "ordinary" fractional Caputo time derivative, superdiffusion is described by the equation with a fractional Riesz-type spatial derivative. We find the function g for which the solution (Green's function, GF) to the g-subdiffusion equation takes the form of GF for ordinary subdiffusion in the limit of small time and GF for superdiffusion in the limit of long time. To solve the g-subdiffusion equation we use the g-Laplace transform method. It is shown that the scaling properties of the GF for g-subdiffusion and the GF for superdiffusion are the same in the long time limit. We conclude that for a sufficiently long time the g-subdiffusion equation describes superdiffusion well, despite a different stochastic interpretation of the processes. Then, paradoxically, a subdiffusion equation with a fractional time derivative describes superdiffusion. The superdiffusive effect is achieved here not by making anomalously long jumps by a diffusing particle, but by greatly increasing the particle jump frequency which is derived by means of the g-continuous-time random walk model. The g-subdiffusion equation is shown to be quite general, it can be used in modeling of processes in which a kind of diffusion change continuously over time. In addition, some methods used in modeling of ordinary subdiffusion processes, such as the derivation of local boundary conditions at a thin partially permeable membrane, can be used to model g-subdiffusion processes, even if this process is interpreted as superdiffusion.

摘要

我们使用一个关于另一个函数(g)的具有分数阶Caputo时间导数的次扩散方程((g -)次扩散方程)来描述从普通次扩散到超扩散的平滑过渡。普通次扩散由具有“普通”分数阶Caputo时间导数的方程描述,超扩散由具有分数阶Riesz型空间导数的方程描述。我们找到了这样一个函数(g),对于它,(g -)次扩散方程的解(格林函数,GF)在短时间极限下具有普通次扩散的格林函数形式,在长时间极限下具有超扩散的格林函数形式。为了求解(g -)次扩散方程,我们使用(g -)拉普拉斯变换方法。结果表明,在长时间极限下,(g -)次扩散的格林函数和超扩散的格林函数的标度性质是相同的。我们得出结论,尽管过程的随机解释不同,但对于足够长的时间,(g -)次扩散方程能很好地描述超扩散。然后,矛盾的是,一个具有分数阶时间导数的次扩散方程描述了超扩散。这里的超扩散效应不是通过扩散粒子进行异常长的跳跃来实现的,而是通过大幅增加粒子跳跃频率来实现的,这是通过(g -)连续时间随机游走模型推导出来的。(g -)次扩散方程被证明是相当通用 的,它可用于对扩散类型随时间连续变化的过程进行建模。此外,一些用于普通次扩散过程建模的方法,比如在薄的部分渗透膜处推导局部边界条件的方法,可用于对(g -)次扩散过程进行建模,即使该过程被解释为超扩散。

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