Contributions to the Algorithmic Foundations of Approximate Lie Symmetry Algebras of Differential Equations
Siyuan Deng, Gregory Reid

TL;DR
This paper develops a new algorithmic framework for defining and computing approximate Lie symmetry algebras of differential equations, addressing stability and reliability issues inherent in symbolic methods.
Contribution
It introduces a local, numerical approach using SVD and geometric involutive forms to identify approximate Lie symmetry algebras near exact ones, with methods to evaluate their reliability.
Findings
The algorithm effectively finds nearby symmetry algebras using SVD.
The approach can distinguish stable from unstable symmetry regions.
It provides a way to analyze the reliability of approximate symmetries.
Abstract
Lie symmetry transformations that leave a differential equation invariant play a fundamental role in science and mathematics. Such Lie symmetry groups uniquely determine their Lie symmetry algebras. Exact differential elimination algorithms have been developed to determine the dimension and structure constants of the Lie symmetry algebra of an exact polynomially nonlinear differential equation. Directly applying these symbolic algorithms to approximate models is prone to instability since these algorithms strongly depend on the orderings of the variables involved. This motivates the need to address questions at the algorithmic foundation of approximate Lie symmetry algebras of differential equations. How do we define approximate Lie symmetry? How do we compute and apply approximate Lie symmetry algebras of differential equations? How reliable are the results? To address such…
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Taxonomy
TopicsAdvanced Topics in Algebra · Nonlinear Waves and Solitons · Algebraic structures and combinatorial models
