Finite-difference methods for solving 1D Poisson problem
- Authors: Ndayisenga S.1, Sevastianov L.A.1,2, Lovetskiy K.P.1
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Affiliations:
- Peoples’ Friendship University of Russia (RUDN University)
- Bogoliubov Laboratory of Theoretical Physics Joint Institute for Nuclear Research
- Issue: Vol 30, No 1 (2022)
- Pages: 62-78
- Section: Articles
- URL: https://journals.rcsi.science/2658-4670/article/view/315380
- DOI: https://doi.org/10.22363/2658-4670-2022-30-1-62-78
- ID: 315380
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Abstract
The paper discusses the formulation and analysis of methods for solving the one-dimensional Poisson equation based on finite-difference approximations - an important and very useful tool for the numerical study of differential equations. In fact, this is a classical approximation method based on the expansion of the solution in a Taylor series, based on which the recent progress of theoretical and practical studies allowed increasing the accuracy, stability, and convergence of methods for solving differential equations. Some of the features of this analysis include interesting extensions to classical numerical analysis of initial and boundary value problems. In the first part, a numerical method for solving the one-dimensional Poisson equation is presented, which reduces to solving a system of linear algebraic equations (SLAE) with a banded symmetric positive definite matrix. The well-known tridiagonal matrix algorithm, also known as the Thomas algorithm, is used to solve the SLAEs. The second part presents a solution method based on an analytical representation of the exact inverse matrix of a discretized version of the Poisson equation. Expressions for inverse matrices essentially depend on the types of boundary conditions in the original setting. Variants of inverse matrices for the Poisson equation with different boundary conditions at the ends of the interval under study are presented - the Dirichlet conditions at both ends of the interval, the Dirichlet conditions at one of the ends and Neumann conditions at the other. In all three cases, the coefficients of the inverse matrices are easily found and the algorithm for solving the problem is practically reduced to multiplying the matrix by the vector of the right-hand side.
About the authors
Serge Ndayisenga
Peoples’ Friendship University of Russia (RUDN University)
Author for correspondence.
Email: 1032195775@rudn.ru
ORCID iD: 0000-0002-9297-9839
Student of Department of Applied Probability and Informatics
6, Miklukho-Maklaya St., Moscow, 117198, Russian FederationLeonid A. Sevastianov
Peoples’ Friendship University of Russia (RUDN University); Bogoliubov Laboratory of Theoretical Physics Joint Institute for Nuclear Research
Email: sevastianov-la@rudn.ru
ORCID iD: 0000-0002-1856-4643
Doctor of Physical and Mathematical Sciences, Professor of Department of Applied Probability and Informatics of Peoples’ Friendship University of Russia (RUDN University), Leading Researcher of Bogoliubov Laboratory of Theoretical Physics, JINR
6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation; 6, Joliot-Curie St., Dubna, Moscow Region, 141980, Russian FederationKonstantin P. Lovetskiy
Peoples’ Friendship University of Russia (RUDN University)
Email: lovetskiy-kp@rudn.ru
ORCID iD: 0000-0002-3645-1060
Candidate of Physical and Mathematical Sciences, Associate Professor of Department of Applied Probability and Informatics
6, Miklukho-Maklaya St., Moscow, 117198, Russian FederationReferences
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