SymDR: Symbol Computer Algebra Library for Generation of Classical and Approximate Dispersion Relations for Systems of Partial Differential Equations

Mathematical models of numerous processes in continuum mechanics (CM), plasma physics (PP) and astrophysics (AP) are partial differential equations (PDEs). When developing computer models, these equations are replaced by discrete equations that are solved numerically. In order to investigate mathematical and numerical models of CM, PP and AP, the technique of constructing dispersion relations has been developed. Using dispersion relations allows one to derive particular solutions to systems of PDEs, to investigate the stability of solutions for continuous and discrete models, to estimate the order of approximation and the rate of convergence for discrete models, and to establish of the optimal numerical parameters of a discrete model. Dispersion relations describe wave processes (i.e., processes of perturbation transfer with a velocity different from the velocity of matter) in media. The classical dispersion relation is a nonlinear algebraic equation (relating the wave parameters, namely the wave number $$k$$ and the wave frequency, $$\omega$$ ), which corresponds to a continuous system of PDEs. There is a technique that allows one to derive a dispersion relation (classical or approximate, respectively) for a continuous or discrete CM, PP, and AP model. This paper presents a symbolic computer algebra library, developed by the authors, which automates this technique. The current version supports the use of nonstationary models with a single spatial variable both for continuum and finite-difference notation. The library is written in Python using the SymPy symbolic computing package and is available at https://pypi.org/project/symdr/ .

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Publication Details

Journal
Lobachevskii Journal of Mathematics
Published
2025-01-01
DOI
https://doi.org/10.1134/s1995080224608579
Citations
1
Primary Topic
Numerical methods for differential equations
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article
Field-Weighted Citation Impact
2.63
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article

SymDR: Symbol Computer Algebra Library for Generation of Classical and Approximate Dispersion Relations for Systems of Partial Differential Equations

Tatiana Savvateeva Tatiana Savvateeva, M. S. Arendarenko, O. P. Stoyanovskaya, S. V. Kotov et al.
1 citations
Lobachevskii Journal of Mathematics
Numerical methods for differential equations
2.63
article

SymDR: Symbol Computer Algebra Library for Generation of Classical and Approximate Dispersion Relations for Systems of Partial Differential Equations

Tatiana Savvateeva Tatiana Savvateeva, M. S. Arendarenko, O. P. Stoyanovskaya, S. V. Kotov, A. R. Dzhanbekova, M. S. Malyutin, M. V. Samoylov, V. Y. Utyupina
article en
1 citations

Abstract

Mathematical models of numerous processes in continuum mechanics (CM), plasma physics (PP) and astrophysics (AP) are partial differential equations (PDEs). When developing computer models, these equations are replaced by discrete equations that are solved numerically. In order to investigate mathematical and numerical models of CM, PP and AP, the technique of constructing dispersion relations has been developed. Using dispersion relations allows one to derive particular solutions to systems of PDEs, to investigate the stability of solutions for continuous and discrete models, to estimate the order of approximation and the rate of convergence for discrete models, and to establish of the optimal numerical parameters of a discrete model. Dispersion relations describe wave processes (i.e., processes of perturbation transfer with a velocity different from the velocity of matter) in media. The classical dispersion relation is a nonlinear algebraic equation (relating the wave parameters, namely the wave number $$k$$ and the wave frequency, $$\omega$$ ), which corresponds to a continuous system of PDEs. There is a technique that allows one to derive a dispersion relation (classical or approximate, respectively) for a continuous or discrete CM, PP, and AP model. This paper presents a symbolic computer algebra library, developed by the authors, which automates this technique. The current version supports the use of nonstationary models with a single spatial variable both for continuum and finite-difference notation. The library is written in Python using the SymPy symbolic computing package and is available at https://pypi.org/project/symdr/ .

Lobachevskii Journal of MathematicsVol. 46(1)
National Research University Higher School of Economics (RU), Ural Federal University (RU), Novosibirsk State University (RU), M.N. Mikheev Institute of Metal Physics (RU), Lavrentyev Institute of Hydrodynamics (RU)
Openalex Percentile: Top 13%
Numerical methods for differential equations
2.63
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