A new approach to the formation of systems of linear algebraic equations for solving ordinary differential equations by the collocation method

Мұқаба

Дәйексөз келтіру

Толық мәтін

Аннотация

A new algorithm for the numerical solution of one-dimensional Cauchy problems and Poisson equations is implemented. The algorithm is based on the collocation method and representation of the solution as an expansion in Chebyshev polynomials. It is proposed instead of the usual approach, which consists in combining all known conditions — differential (the equation itself) and initial / boundary — into one system of approximate linear algebraic equations, to go to the method of solving the problem in several separate stages. First, spectral coefficients are identified that determine the “general” solution of the original problem. The collocation method determines the interpolation coefficients of the derivative of the solution, and thus the expansion coefficients of the solution itself (except for the initial ones). At this stage, the choice of a good basis with discrete orthogonality makes it possible to use very efficient algorithms for finding the desired coefficients. The complexity of reducing the matrix of a system of linear algebraic equations to a diagonal form becomes equivalent to the complexity of multiplying the Chebyshev matrix of coefficients by the vector of the right side of the system. Then the expansion coefficients of the solution itself (except for the first one or two) are obtained by multiplying the known tridiagonal integration matrix (inverse to the Chebyshev differentiation matrix) by the vector of interpolation coefficients of the derivative. At the last stage, considering the initial/boundary conditions select a “particular” desired solution, unambiguously redefining the missing coefficients of the desired expansion.

Авторлар туралы

Leonid Sevastianov

Peoples’ Friendship University of Russia (RUDN University); Joint Institute for Nuclear Research

6, Miklukho-Maklaya St., Moscow, 117198, Russia

Konstantin Lovetskiy

Peoples’ Friendship University of Russia (RUDN University)

6, Miklukho-Maklaya St., Moscow, 117198, Russia

Dmitry Kulyabov

Peoples’ Friendship University of Russia (RUDN University)

6, Miklukho-Maklaya St., Moscow, 117198, Russia

Әдебиет тізімі

  1. Boyd J. P. Chebyshev and Fourier Spectral Methods: Second Revised Edition. Dover Books on Mathematics, 2013. 668 p.
  2. Mason J. C., Handscomb D. C. Chebyshev Polynomials. Chapman and Hall/CRC Press, 2002. 360 p. https://doi.org/10.1201/9781420036114
  3. Fornberg B. A Practical Guide to Pseudospectral Methods. New York : Cambridge University Press, 1996. 231 p. https://doi.org/10.1017/CBO9780511626357
  4. Press W. H., Teukolsky S. A., Vetterling W. T., Flannery B. P. Numerical Recipes: The Art of Scientific Computing. 3rd ed. New York : Cambridge University Press, 2007. 1235 p.
  5. Shen J., Tang T., Wang L.-L. Spectral Methods: Algorithms, Analysis and Applications. Berlin ; Heidelberg : Springer, 2011. 472 p. (Springer Series in Computational Mathematics, vol. 41). https://doi.org/10.1007/978-3-540-71041-7
  6. Olver S., Townsend A. A Fast and Well-Conditioned Spectral Method // SIAM Review. 2013. Vol. 55, iss. 3. P. 462–489. https://doi.org/10.1137/120865458
  7. Chandrasekaran S., Gu M. Fast and Stable Algorithms for Banded Plus Semiseparable Systems of Linear Equations // SIAM Journal on Matrix Analysis and Applications. 2003. Vol. 25, iss. 2. P. 373–384. https://doi.org/10.1137/S0895479899353373
  8. Amiraslani A., Corless R. M., Gunasingam M. Differentiation matrices for univariate polynomials // Numerical Algorithms. 2020. Vol. 83, iss. 1. P. 1–31. https://doi.org/10.1007/s11075-019-00668-z
  9. Zhang X., Boyd J. P. Asymptotic coefficients and errors for Chebyshev polynomial approximations with weak endpoint singularities: Effects of different bases // Science China Mathematics. 2023. Vol. 66, iss. 1. P. 191–220. https://doi.org/10.1007/s11425-021-1974-x
  10. Boyd J. P., Gally D. H. Numerical experiments on the accuracy of the Chebyshev – Frobenius companion matrix method for finding the zeros of a truncated series of Chebyshev polynomials // Journal of Computational and Applied Mathematics. 2007. Vol. 205, iss. 1. P. 281–295. https://doi.org/10.1016/j.cam.2006.05.006
  11. Dutykh D. A Brief Introduction to Pseudo-spectral Methods: Application to Diffusion Problems. 2019. 55 p. URL: https://arxiv.org/pdf/1606.05432 (дата обращения: 30.05.2022).
  12. Dawkins P. Differential Equations. 2018. 524 p. URL: https://tutorial.math.lamar.edu/Classes/DE/DE.aspx (дата обращения: 30.05.2022).


Creative Commons License
Бұл мақала лицензия бойынша қолжетімді Creative Commons Attribution 4.0 International License.

Осы сайт cookie-файлдарды пайдаланады

Біздің сайтты пайдалануды жалғастыра отырып, сіз сайттың дұрыс жұмыс істеуін қамтамасыз ететін cookie файлдарын өңдеуге келісім бересіз.< / br>< / br>cookie файлдары туралы< / a>