An Evolutionary Approach to the Automatic Classification of Automorphisms of Lower-Dimensional Lie Algebras

被引:0
作者
Soh, Celestin Wafo [1 ,2 ]
机构
[1] Jackson State Univ, Dept Math & Stat Sci, JSU Box 17610,1400 JR Lynch St, Jackson, MS 39217 USA
[2] Univ Witwatersrand, DST NRF Ctr Excellence Math & Stat Sci, Sch Comp Sci & Appl Math, Johannesburg, South Africa
基金
新加坡国家研究基金会;
关键词
Lie algebra; automorphisms of a Lie algebra; discrete symmetries; dependency relation; genetic algorithm; DISCRETE SYMMETRIES; DIFFEOMORPHISMS;
D O I
10.1080/10586458.2018.1516582
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We implement two algorithms in MATHEMATICA for classifying automorphisms of lower-dimensional non-Abelian Lie algebras. The first algorithm is a brute-force approach whereas the second is an evolutionary strategy. These algorithms are delivered as the MATHEMATICA package cwsAutoClass. In order to facilitate the application of this package to symmetry Lie algebras of differential equations, we also provide a package, cwsLieSymTools, for manipulating finite-dimensional Lie algebras of vector fields. In particular, this package allows the computations of Lie brackets, structure constants, and the visualization of commutator tables. Several examples are provided to illustrate the pertinence of our approach. These computational experiments show that the evolutionary strategy outperformed consistently the brute-force method.
引用
收藏
页码:191 / 199
页数:9
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