Algorithmic framework for group analysis of differential equations and its application to generalized Zakharov--Kuznetsov equations

TL;DR

This paper presents an algorithmic approach to classify symmetries of differential equations, demonstrated on generalized Zakharov--Kuznetsov equations, resulting in new invariant models and exact solutions.

Contribution

It introduces a comprehensive algorithmic framework for group classification and reduction of PDEs, applied to GZK equations, yielding new models and solutions.

Findings

Complete group classification of GZK equations achieved

New nonlinear invariant models identified

Exact solutions for classical and modified GZK equations constructed

Abstract

In this paper, we explain in more details the modern treatment of the problem of group classification of (systems of) partial differential equations (PDEs) from the algorithmic point of view. More precisely, we revise the classical Lie--Ovsiannikov algorithm of construction of symmetries of differential equations, describe the group classification algorithm and discuss the process of reduction of (systems of) PDEs to (systems of) equations with smaller number of independent variables in order to construct invariant solutions. The group classification algorithm and reduction process are illustrated by the example of the generalized Zakharov--Kuznetsov (GZK) equations of form $u_t+(F(u))_{xxx}+(G(u))_{xyy}+(H(u))_x=0$. As a result, a complete group classification of the GZK equations is performed and a number of new interesting nonlinear invariant models which have non-trivial invariance algebras are obtained. Lie symmetry reductions and exact solutions for two important invariant models, i.e., the classical and modified Zakharov--Kuznetsov equations, are constructed. The algorithmic framework for group analysis of differential equations presented in this paper can also be applied to other nonlinear PDEs.