{"title":"与投影几何 Bq(n) 相关的加权邻接矩阵的特征基础","authors":"Murali K. Srinivasan","doi":"10.1016/j.laa.2024.09.007","DOIUrl":null,"url":null,"abstract":"<div><p>In a recent article <em>Projective geometries, Q-polynomial structures, and quantum groups</em> Terwilliger (arXiv:2407.14964) defined a certain weighted adjacency matrix, depending on a free (positive real) parameter, associated with the projective geometry, and showed (among many other results) that it is diagonalizable, with the eigenvalues and their multiplicities explicitly written down, and that it satisfies the <em>Q</em>-polynomial property (with respect to the zero subspace).</p><p>In this note we</p><ul><li><span>•</span><span><p>Write down an explicit eigenbasis for this matrix.</p></span></li><li><span>•</span><span><p>Evaluate the adjacency matrix-eigenvector products, yielding a new proof for the eigenvalues and their multiplicities.</p></span></li><li><span>•</span><span><p>Evaluate the dual adjacency matrix-eigenvector products and directly show that the action of the dual adjacency matrix on the eigenspaces of the adjacency matrix is block-tridiagonal, yielding a new proof of the <em>Q</em>-polynomial property.</p></span></li></ul></div>","PeriodicalId":18043,"journal":{"name":"Linear Algebra and its Applications","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Eigenbasis for a weighted adjacency matrix associated with the projective geometry Bq(n)\",\"authors\":\"Murali K. Srinivasan\",\"doi\":\"10.1016/j.laa.2024.09.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In a recent article <em>Projective geometries, Q-polynomial structures, and quantum groups</em> Terwilliger (arXiv:2407.14964) defined a certain weighted adjacency matrix, depending on a free (positive real) parameter, associated with the projective geometry, and showed (among many other results) that it is diagonalizable, with the eigenvalues and their multiplicities explicitly written down, and that it satisfies the <em>Q</em>-polynomial property (with respect to the zero subspace).</p><p>In this note we</p><ul><li><span>•</span><span><p>Write down an explicit eigenbasis for this matrix.</p></span></li><li><span>•</span><span><p>Evaluate the adjacency matrix-eigenvector products, yielding a new proof for the eigenvalues and their multiplicities.</p></span></li><li><span>•</span><span><p>Evaluate the dual adjacency matrix-eigenvector products and directly show that the action of the dual adjacency matrix on the eigenspaces of the adjacency matrix is block-tridiagonal, yielding a new proof of the <em>Q</em>-polynomial property.</p></span></li></ul></div>\",\"PeriodicalId\":18043,\"journal\":{\"name\":\"Linear Algebra and its Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Linear Algebra and its Applications\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0024379524003690\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Linear Algebra and its Applications","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0024379524003690","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
摘要
在最近的一篇文章《投影几何、Q-多项式结构和量子群》(Projective geometries, Q-polynomial structures, and quantum groups)中,Terwilliger(arXiv:2407.14964)定义了一个与投影几何相关的、取决于自由(正实数)参数的加权邻接矩阵,并证明(除其他许多结果外)它是可对角的,特征值及其乘数被明确写出,而且它满足 Q-多项式性质(关于零子空间)。在本注释中,我们--为这个矩阵写下了一个明确的特征基础。--评估了邻接矩阵-特征向量乘积,得出了特征值及其乘积的新证明。--评估了对偶邻接矩阵-特征向量乘积,并直接证明了对偶邻接矩阵对邻接矩阵特征空间的作用是块对角的,得出了 Q 多项式性质的新证明。
Eigenbasis for a weighted adjacency matrix associated with the projective geometry Bq(n)
In a recent article Projective geometries, Q-polynomial structures, and quantum groups Terwilliger (arXiv:2407.14964) defined a certain weighted adjacency matrix, depending on a free (positive real) parameter, associated with the projective geometry, and showed (among many other results) that it is diagonalizable, with the eigenvalues and their multiplicities explicitly written down, and that it satisfies the Q-polynomial property (with respect to the zero subspace).
In this note we
•
Write down an explicit eigenbasis for this matrix.
•
Evaluate the adjacency matrix-eigenvector products, yielding a new proof for the eigenvalues and their multiplicities.
•
Evaluate the dual adjacency matrix-eigenvector products and directly show that the action of the dual adjacency matrix on the eigenspaces of the adjacency matrix is block-tridiagonal, yielding a new proof of the Q-polynomial property.
期刊介绍:
Linear Algebra and its Applications publishes articles that contribute new information or new insights to matrix theory and finite dimensional linear algebra in their algebraic, arithmetic, combinatorial, geometric, or numerical aspects. It also publishes articles that give significant applications of matrix theory or linear algebra to other branches of mathematics and to other sciences. Articles that provide new information or perspectives on the historical development of matrix theory and linear algebra are also welcome. Expository articles which can serve as an introduction to a subject for workers in related areas and which bring one to the frontiers of research are encouraged. Reviews of books are published occasionally as are conference reports that provide an historical record of major meetings on matrix theory and linear algebra.