fpcross 0.2

Solver in the low-rank tensor-train format with cross approximation approach for solution of the multidimensional Fokker-Planck equation

Package fpcross

Description

This python package, named fpcross (Fokker Planck cross-approximation), provides a solver in the low-rank tensor-train format with cross approximation approach for solution of the multidimensional Fokker-Planck equation (FPE) of the form

d r(x, t) / d t = D delta( r(x, t) ) - div( f(x, t) r(x, t) ),
where r(x, 0) = r0(x).

The function f(x, t), its diagonal partial derivatives d f_i (x, t) / d x_i, initial condition r0(x) and scalar diffusion coefficient D should be known. The equation is solved from the initial moment (t = 0) to the user-specified moment (t), while the solutions obtained at each time step can be used if necessary. The resulting solution r(x, t) represents both the TT-tensor on the multidimensional Chebyshev grid and the Chebyshev interpolation coefficients in the TT-format, and therefore it can be quickly calculated at an arbitrary spatial point.

Installation

The package can be installed via pip: pip install fpcross (it requires the Python programming language of the version >= 3.7). It can be also downloaded from the repository fpcross and installed by python setup.py install command from the root folder of the project.

Required python packages matplotlib, numpy, scipy, teneva and tqdm will be automatically installed during the installation of the main software product.

Usage

A compact example of using the solver for a user-defined FPE is provided in the script demo/demo.py (run it as python demo/demo.py from the root of the project).

The software product also implements classes for the model FPEs:

1. multidimensional simple diffusion problem (see fpcross/equation_demo/EquationDif.py);
2. multidimensional Ornstein-Uhlenbeck process (see fpcross/equation_demo/EquationOUP.py);
3. 3-dimensional dumbbell model (see fpcross/equation_demo/EquationDum.py).

A demonstration of their solution is given in the script demo/check.py (run it as python cdemo/heck.py from the root of the project).

Authors

• Andrei Chertkov ([e-mail]);
• Ivan Oseledets ([e-mail]).

Citation

If you find this approach and/or code useful in your research, please consider citing:

@article{chertkov2021solution,
    author    = {Chertkov, Andrei and Oseledets, Ivan},
    year      = {2021},
    title     = {Solution of the Fokker--Planck equation by cross approximation method in the tensor train format},
    journal   = {Frontiers in Artificial Intelligence},
    volume    = {4},
    issn      = {2624-8212},
    doi       = {10.3389/frai.2021.668215},
    url       = {https://www.frontiersin.org/article/10.3389/frai.2021.668215}
}