Graph Theory

Matrices in combinatorics and graph theory by Bolian Liu

By Bolian Liu

The 1st bankruptcy of this publication presents a short remedy of the fundamentals of the topic. the opposite chapters take care of a few of the decompositions of non-negative matrices, Birkhoff kind theorems, the examine of the powers of non-negative matrices, functions of matrix how to different combinatorial difficulties, and purposes of combinatorial ways to matrix difficulties and linear algebra difficulties. The assurance of necessities has been saved to a minimal. however, the e-book is essentially self-contained (an Appendix presents the required history in linear algebra, graph thought and combinatorics). there are numerous routines, all of that are followed via sketched suggestions. viewers: The e-book is acceptable for a graduate path in addition to being a great reference and a useful source for mathematicians operating within the region of combinatorial matrix concept.

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4(i). 4(ii) is similar and is left as an exercise. Matrices and Graphs 24 Recall that Jm denotes the m by m square matrix each of whose entries is a one. , = Im. , ... 4(i). 5 (Schwenk, Herndon, and Ellzey [234]) H G 1 is a regular graph and if IV{Gt)l = 21Ttl 1 then B(Gt,T11G2,T2) and B(G1o V(Gt)- T1,G2,T2) have the same spectrum. 6. 5(i) by taking 11" {81 ,82 ,· .. ,S~:,S} in which Si = V(H,), 1 $; i $; k, and in which S = Uf=t V(L,). 0 = Codsil and Mckay also proved that graphs with the same spectrum may be constructed by taking graph products under certain conditions.

Fifidj. By Cauchy- lSiSn ,.. -L--d-;, which gives Part (i) . ijEE(G) Apply Part (i) to show Part (ii). It suffices to show that for each i, L d; ~ ijEE(G) L 2q(n- 1). This is true if n~ ;::: 2q, since d; n ijEE(G) Fori with ~ 2q- ~ ~ 2q(n- 1). n~ < 2q, then ii~G) d; ~~(G)~~ n 2q(nn- 1). 11. 14 LetT denote a tree on n ;::: 3 vertices. Pick a vertex v1 e V(T). H v1 is not the desired vertex, then T-v 1 has either a component with more than n-2-l(n-2)/kJ vertices, or at least two components each of which has more than L(n- 2)/kJ + 1 vertices.

18) p(A)zn::; 1. This implies that for each i, p(A)z; n E =1 - z; ~ 1 - r;xn, j=n-r;+1 and so summing up for i yields n p(A) ~ n- E r;zn = n- TZn· i=1 By p(A) > 0 and by p(A)xn ::; 1, p(A) 2 ~ p(A)(n- rzn) ~ np(A) - r. Solving this inequality for p(A) gives p(A)~n+~. 18) are equalities. n In other words, for each j with n- r 1 + 1::; j::; n, both p(A)x; = Ez 1 i=1 = 1 and r; = 0, Matrices and Graphs 38 and so there exists a permutation matrix P such that p-l AP = B with k = n - r 1 and = r1. 16).

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