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Faster Groebner bases for Lie derivatives of ODE systems via monomial orderings

Title: Faster Groebner bases for Lie derivatives of ODE systems via monomial orderings
Authors: Bessonov, Mariya; Ilmer, Ilia; Konstantinova, Tatiana; Ovchinnikov, Alexey; Pogudin, Gleb; Soto, Pedro
Publisher Information: ACM
Publication Year: 2024
Collection: VTechWorks (VirginiaTech)
Description: Symbolic computation for systems of differential equations is often computationally expensive. Many practical differential models have a form of polynomial or rational ODE system with specified outputs. A basic symbolic approach to analyze these models is to compute and then symbolically process the polynomial system obtained by sufficiently many Lie derivatives of the output functions with respect to the vector field given by the ODE system. In this paper, we present a method for speeding up Grbner basis computation for such a class of polynomial systems by using specific monomial ordering, including weights for the variables, coming from the structure of the ODE model.We provide empirical results that showimprovement across different symbolic computing frameworks and apply the method to speed up structural identifiability analysis of ODE models. ; Published version
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: ISSAC '24: Proceedings of the 2024 International Symposium on Symbolic and Algebraic Computation; https://hdl.handle.net/10919/120868; https://doi.org/10.1145/3666000.3669695
DOI: 10.1145/3666000.3669695
Availability: https://hdl.handle.net/10919/120868; https://doi.org/10.1145/3666000.3669695
Rights: In Copyright ; http://rightsstatements.org/vocab/InC/1.0/ ; The author(s)
Accession Number: edsbas.442C1634
Database: BASE