Conversion of Unweighted Graphs to Weighted Graphs Satisfying Properties R and −SR

IF 1.9 3区 数学 Q1 MATHEMATICS, APPLIED Axioms Pub Date : 2023-11-09 DOI:10.3390/axioms12111043
Xiaolong Shi, Saira Hameed, Sadia Akhter, Aysha Khan, Maryam Akhoundi
{"title":"Conversion of Unweighted Graphs to Weighted Graphs Satisfying Properties R and −SR","authors":"Xiaolong Shi, Saira Hameed, Sadia Akhter, Aysha Khan, Maryam Akhoundi","doi":"10.3390/axioms12111043","DOIUrl":null,"url":null,"abstract":"Spectral graph theory is like a special tool for understanding graphs. It helps us find patterns and connections in complex networks, using the magic of eigenvalues. Let G be the graph and A(G) be its adjacency matrix, then G is singular if the determinant of the adjacency matrix A(G) is 0, otherwise it is nonsingular. Within the realm of nonsingular graphs, there is the concept of property R, where each eigenvalue’s reciprocal is also an eigenvalue of G. By introducing multiplicity constraints on both eigenvalues and their reciprocals, it becomes property SR. Similarly, the world of nonsingular graphs reveals property −R, where the negative reciprocal of each eigenvalue also finds a place within the spectrum of G. Moreover, when the multiplicity of each eigenvalue and its negative reciprocal is equal, this results in a graph with a property of −SR. Some classes of unweighted nonbipartite graphs are already constructed in the literature with the help of the complete graph Kn and a copy of the path graph P4 satisfying property R but not SR. This article takes this a step further. The main aim is to construct several weighted classes of graphs which satisfy property R but not SR. For this purpose, the weight functions are determined that enable these nonbipartite graph classes to satisfy the −SR and R properties, even if the unweighted graph does not satisfy these properties. Some examples are presented to support the investigated results. These examples explain how certain weight functions make these special types of graphs meet the properties R or −SR, even when the original graphs without weights do not meet these properties.","PeriodicalId":53148,"journal":{"name":"Axioms","volume":" 11","pages":"0"},"PeriodicalIF":1.9000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Axioms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/axioms12111043","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

Spectral graph theory is like a special tool for understanding graphs. It helps us find patterns and connections in complex networks, using the magic of eigenvalues. Let G be the graph and A(G) be its adjacency matrix, then G is singular if the determinant of the adjacency matrix A(G) is 0, otherwise it is nonsingular. Within the realm of nonsingular graphs, there is the concept of property R, where each eigenvalue’s reciprocal is also an eigenvalue of G. By introducing multiplicity constraints on both eigenvalues and their reciprocals, it becomes property SR. Similarly, the world of nonsingular graphs reveals property −R, where the negative reciprocal of each eigenvalue also finds a place within the spectrum of G. Moreover, when the multiplicity of each eigenvalue and its negative reciprocal is equal, this results in a graph with a property of −SR. Some classes of unweighted nonbipartite graphs are already constructed in the literature with the help of the complete graph Kn and a copy of the path graph P4 satisfying property R but not SR. This article takes this a step further. The main aim is to construct several weighted classes of graphs which satisfy property R but not SR. For this purpose, the weight functions are determined that enable these nonbipartite graph classes to satisfy the −SR and R properties, even if the unweighted graph does not satisfy these properties. Some examples are presented to support the investigated results. These examples explain how certain weight functions make these special types of graphs meet the properties R or −SR, even when the original graphs without weights do not meet these properties.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
非加权图到满足属性R和- SR的加权图的转换
谱图理论就像一个理解图的特殊工具。它利用特征值的魔力,帮助我们在复杂的网络中找到模式和联系。设G为图,A(G)为它的邻接矩阵,若邻接矩阵A(G)的行列式为0,则G为奇异,否则为非奇异。在非奇异图的领域中,有性质R的概念,其中每个特征值的倒数也是g的特征值。通过对特征值及其倒数引入多重性约束,它成为性质sr。类似地,非奇异图的世界揭示了性质- R,其中每个特征值的负倒数也在g的谱中找到一个位置。此外,当每个特征值及其负倒数的多重性相等时,这就得到了一个性质为- SR的图。文献中已经利用完全图Kn和满足性质R但不满足sr的路径图P4的副本构造了若干类无权非二部图。本文在此基础上更进一步。主要目的是构造几个满足R而不满足SR性质的图的加权类。为此,确定了使这些非二部图类满足- SR和R性质的权函数,即使未加权图不满足这些性质。给出了一些实例来支持研究结果。这些例子解释了某些权重函数如何使这些特殊类型的图满足属性R或- SR,即使没有权重的原始图不满足这些属性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Axioms
Axioms Mathematics-Algebra and Number Theory
自引率
10.00%
发文量
604
审稿时长
11 weeks
期刊介绍: Axiomatic theories in physics and in mathematics (for example, axiomatic theory of thermodynamics, and also either the axiomatic classical set theory or the axiomatic fuzzy set theory) Axiomatization, axiomatic methods, theorems, mathematical proofs Algebraic structures, field theory, group theory, topology, vector spaces Mathematical analysis Mathematical physics Mathematical logic, and non-classical logics, such as fuzzy logic, modal logic, non-monotonic logic. etc. Classical and fuzzy set theories Number theory Systems theory Classical measures, fuzzy measures, representation theory, and probability theory Graph theory Information theory Entropy Symmetry Differential equations and dynamical systems Relativity and quantum theories Mathematical chemistry Automata theory Mathematical problems of artificial intelligence Complex networks from a mathematical viewpoint Reasoning under uncertainty Interdisciplinary applications of mathematical theory.
期刊最新文献
Modified Two-Parameter Liu Estimator for Addressing Multicollinearity in the Poisson Regression Model Results of Third-Order Strong Differential Subordinations A Probabilistic Physico-Chemical Diffusion Model of the Key Drifting Parameter of Measuring Equipment Finite-Time Passivity and Synchronization for a Class of Fuzzy Inertial Complex-Valued Neural Networks with Time-Varying Delays Integer-Valued Split-BREAK Process with a General Family of Innovations and Application to Accident Count Data Modeling
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1