恰有两个Q-主特征值的三圈图

图G的无符号拉普拉斯矩阵定义为图G的邻接矩阵与度对角矩阵的和,其特征值称为图G的Q-特征值.图G的一个Q-特征值称为Q-主特征值,如果它有一个特征向量其分量的和不等于零.确定了所有恰有两个Q-主特征值的三圈图.     

恰有两个主特征值的图与图的剖分

大量研究表明,图的主特征值的数量与图的结构有着密切关系.通过恰有两个主特征值的图的特征定义了2-邻域k-剖分图,研究了恰有两个主特征值的图与2-邻域k-剖分图之间的关系;同时给出一个2-邻域k-剖分图在k=2,3时为等部剖分的条件.     

恰含两个圈的二部图的能量

设λ1，λ2，…，λn是n阶图G的特征值，图G的能量是E(G)=|λ1| |λ2| … |λn|，设G(n)是n个顶点n 1条边的恰有两个圈的连通二部图的集合，Z(n；4，4)是G(n)中的一个图，它的两个长为4的圈恰有一个公共点，其余n-7个点都是悬挂点且均与这个公共点相邻．文中证明了Z(n；4，4)是G(n)中具有最小能量的图。     

一类完全三部图的K1,3-因子大集

令G是一个有限图,H是G的一个子图.若V(H)=V(G),则称H为G的生成子图.图G的一个λ重F-因子,记为Sλ(F,G),是G的一个生成子图且可分拆为若干与F同构的子图(称为F-区组)的并,使得V(G)中的每一个顶点恰出现在λ个F-区组中.一个图G的λ重F-因子大集,记为LSλ(F G),是G中所有与F同构的子图的一个分拆{B_i}_i,使得每个B_i均构成一个Sλ(F,G).当λ=1时,λ可省略不写.本文中,我们证明了当v≡4 mod 24时,存在LS(K1,3,Kv,v,v).     

一类混合图的结构及其特征空间

主要讨论具有如下性质的一类连通混合图G:其所有非奇异圈恰有一条公共边,且除了该公共边的端点外,任意两个非奇异圈没有其它交点.本文给出了图G的结构性质,建立了其最小特征值λ1(G)(以及相对应的特征向量)与某个简单图的代数连通度(以及Fiedler向量)之间联系,并应用上述联系证明了λ1(■)≤α(G),其中G是由G通过对其所有无向边定向而获得,α(■)为■的代数连通度.     

关于图的规范拉普拉斯特征值和的若干结果（英文）

对任意一个连通图G,记L(G)和L(G)分别为G的拉普拉斯矩阵和规范拉普拉斯矩阵.令μ_1≥μ_2≥…≥μ_n=0和λ_1≥λ_2≥…≥λ_n=0分别为G的拉普拉斯特征值和规范拉普拉斯特征值.本文给出了λ_1的三个新的下界.前两个下界优于Das等在[Ars Cormbin.,2015,118:143-154]中给出的下界,第三个下界优于张晓东在[Ars Combin.,2004,72:191-198]中给出的下界.另一方面讨论了规范拉普拉斯特征值与G的度序列之间的关系.同时也讨论了图的拉普拉斯特征值和规范拉普拉斯特征值之间的关系.     

具有斜特征值互逆性质的单圈图

设G是一个无向图.如果对G的任一(某个)定向图G,G的斜邻接矩阵S(G)的每一个特征值λ,其倒数1/λ同样也是S(G)的特征值,且重数与λ相同,就称G是具有强迫(允许)斜特征值互逆性质.本文确定了所有具有强迫(允许)斜特征值互逆性质的单圈图.     

标准Jacobi矩阵的混合型特征反问题

0 引言 本文讨论如下标准形式的Jacobi矩阵 其中a_i>0(i=1,2,…,n),b_i>0(i=1,2,…,n-1)。 对于Jacobi矩阵(对称三对角矩阵)的特征反问题,已有的成果[1],基本上集中在由两组频谱或两个特征对(指特征值及相应的特征向量)构造Jacobi矩阵的元素这样两类问题上,习惯上称之为频谱型或特征向量型反问题。本文提出且求解了第三类型——混合型特征反问题。即由一组频谱数据和一个特征向量构造矩阵元素的问题: 问题Ⅰ 给定正数λ~(1),λ~(2),…,λ~(n)和实向量x=(x_1,x_2,…,x_n)~T,其中x_1=1。构造一个标准形式的Jacobi矩阵J,使其第k阶顺序主子阵恰以λ~(k)(k=1,2,…,n)为其特征值。且(λ~(n),x)为其特征对。 问题Ⅱ 给定正数0<λ_1~(n)<λ_1~(n-1)<…<λ_1~(1)和正向量x=(x_1,x_2,…,x_n),其中x_=,x_k>0(k=2,…,n),构造一个标准形式的Jacobi矩阵J,使其第K阶顺序主子阵恰以λ_1~(k)为其最小特征值,而(λ~(n),x)为J的特征对。 问题Ⅲ 给定n个实数0<λ_1)<λ_2<…<λ_n和m个实数λ~(1),λ~(2),…,λ~(m)及m维向量x=(x_1,…,x_m)~T。构造n阶标准形式的Jaeobi矩阵J,使其第K阶顺序主子阵恰以λ~(k)(k=1,2,…,m)为其特征值,而(λ~(m),x)为第m阶顺序主子阵的特征对,且λ_k(k=1,2,…,n)为J的特征值。这里系大于或等     

关于图的边连通度等于最小次问题的一个注记

本文举例说明了[1]中的两个结论在原有的假设条件下是不成立的,并将条件作适当修改后,重新证明了这两个结论.设 G 为简单的连通图,λ(G)为其边连通度,δ(G)为其最小次,则λ(G)≤δ(G).B.Bollobas 在[1]中讨论了上述不等式中等号成立的一些充分条件.并且断言:“如果在连通图 G 中,对每个最小次点 x,存在与 x 相邻的节点 x_1…,x_l(l 依赖于 x),使得     

K_(2,3)的多重多部图设计的构造

λKn(t)是一个λ重完全多部图,G为一个不带孤立点的简单图.所谓的图设计G-HDλ(tn)是一个序偶(X,B),其中X是Kn(t)的顶点集,B为λKn(t)的一些子图(亦称为区组)构成的集合,使得任一区组均与图G同构,且λKn(t)的任意2个不同点组成的边恰在B的λ个区组中出现.本文讨论了G=K2,3的完全多部图设计存在性问题,证明了存在G-HDλ(tn)当且仅当λn(n-1)t2≡0(mod12),n≥2,nt≥5且(n,,λt)≠(9,1,1),(12,1,1),(3,1,2),(4,1,2).     

On graphs with given main eigenvalues

An eigenvalue of a graph is main if it has an eigenvector, the sum of whose entries is not equal to zero. Extending previous results of Hagos and Hou et al. we obtain two conditions for graphs with given main eigenvalues. All trees and connected unicyclic graphs with exactly two main eigenvalues were characterized by Hou et al. Extending their results, we determine all bicyclic connected graphs with exactly two main eigenvalues.     

The integral graphs with index 3 and exactly two main eigenvalues

A graph is called integral if the spectrum of its adjacency matrix has only integral eigenvalues. An eigenvalue of a graph is called main eigenvalue if it has an eigenvector such that the sum of whose entries is not equal to zero. In this paper, we show that there are exactly 25 connected integral graphs with exactly two main eigenvalues and index 3.     

Bicyclic graphs with exactly two main eigenvalues

An eigenvalue of a graph G is called a main eigenvalue if it has an eigenvector the sum of whose entries is not equal to zero, and it is well known that a graph has exactly one main eigenvalue if and only if it is regular. In this work, all connected bicyclic graphs with exactly two main eigenvalues are determined.     

On Integral Graphs with Few Cycles

A graph is called integral if the spectrum of its adjacency matrix has only integer eigenvalues. In this paper, all integral graphs with at most two cycles (trees, unicyclic and bicyclic graphs) with no eigenvalue 0 are identified. Moreover, we give some results on unicyclic integral graphs with exactly one eigenvalue 0.     

On graphs with exactly one anti-adjacency eigenvalue and beyond

The anti-adjacency matrix of a graph is constructed from the distance matrix of a graph by keeping each row and each column only the largest distances. This matrix can be interpreted as the opposite of the adjacency matrix, which is instead constructed from the distance matrix of a graph by keeping in each row and each column only the distances equal to 1. The (anti-)adjacency eigenvalues of a graph are those of its (anti-)adjacency matrix. Employing a novel technique introduced by Haemers (2019) [9], we characterize all connected graphs with exactly one positive anti-adjacency eigenvalue, which is an analog of Smith's classical result that a connected graph has exactly one positive adjacency eigenvalue iff it is a complete multipartite graph. On this basis, we identify the connected graphs with all but at most two anti-adjacency eigenvalues equal to ?2 and 0. Moreover, for the anti-adjacency matrix we determine the HL-index of graphs with exactly one positive anti-adjacency eigenvalue, where the HL-index measures how large in absolute value may be the median eigenvalues of a graph. We finally propose some problems for further study.     

On bipartite graphs with small number of laplacian eigenvalues greater than two and three

All connected bipartite graphs with exactly two Laplacian eigenvalues greater than two are determined. Besides, all connected bipartite graphs with exactly one Laplacian eigenvalue greater than three are determined.     

On bipartite graphs with small number of laplacian eigenvalues greater than two and three

All connected bipartite graphs with exactly two Laplacian eigenvalues greater than two are determined. Besides, all connected bipartite graphs with exactly one Laplacian eigenvalue greater than three are determined.