Section 21.1

Chapter Problems

[10/100%]
Show
LaTeX
Problem 21.1.1

A walk of length kk in a digraph is a succession of kk arcs joining two vertices. A trail is a walk in which all the arcs (but not necessarily all the vertices) are distinct. A path is a walk in which all the arcs and all the vertices are distinct. Show that the number of walks of length kk from vertex ii to vertex jj in a digraph DD with nn vertices is given by the ijij-th element of the matrix AkA^{k}, where AA is the adjacency matrix of the digraph.

?
Problem 21.1.2

Consider a digraph. The out-degree of a vertex vv is the number of arcs incident from vv and the in-degree of a vertex VV is the number of arcs incident to vv. Loops count as one of each.

Determine the in-degree and the out-degree of each vertex in the digraph given by the adjacency matrix

A=(0100000100100010010000010) A = \begin{pmatrix} 0 & 1 & 0 & 0 & 0 \\ 0 & 0 & 1 & 0 & 0 \\ 1 & 0 & 0 & 0 & 1 \\ 0 & 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 & 0 \end{pmatrix}

and hence determine if it is an Eulerian graph. Display the digraph and determine an Eulerian trail.

?
Problem 21.1.3

A digraph is strongly connected if there is a path between every pair of vertices. Show that if AA is the adjacency matrix of a digraph DD with nn vertices and BB is the matrix

B=A+A2+A3+⋯+An−1 B = A + A^{2} + A^{3} + \cdots + A^{n-1}

then DD is strongly connected iff each non-diagonal element of BB is greater than 0.

?
Problem 21.1.4

Write down the adjacency matrix AA for the digraph shown. Calculate the matrices A2A^{2}, A3A^{3} and A4A^{4}. Consequently find the number of walks of length 1, 2, 3 and 4 from ww to uu. Is there a walk of length 1, 2, 3, or 4 from uu to ww? Find the matrix B=A+A2+A3+A4B=A+A^{2}+A^{3}+A^{4} for the digraph and hence conclude whether it is strongly connected. This means finding out whether all off diagonal elements are nonzero.

The digraph for Problem 21.1.4.The digraph for Problem 21.1.4.

?
Problem 21.1.5

A graph G(V,E)G(V,E) is a set of nodes VV (points, vertices) connected by a set of links EE (edges, lines). We assume that there are nn nodes. The adjacency (n×nn \times n) matrix A=A(G)A=A(G) takes the form with 1 in row ii, column jj if ii is connected to jj, and 0 otherwise. Thus AA is a symmetric matrix. Associated with AA is the degree distribution, a diagonal matrix with row-sums of AA along the diagonal, and 0's elsewhere. We assume that dii>0d_{ii}>0 for all i=1,2,…,ni=1,2,\ldots ,n. We define the Laplacian as L:=D−AL := D-A. Let

A=(0110000101100011010100110010000001000111010000010). A = \begin{pmatrix} 0 & 1 & 1 & 0 & 0 & 0 & 0 \\ 1 & 0 & 1 & 1 & 0 & 0 & 0 \\ 1 & 1 & 0 & 1 & 0 & 1 & 0 \\ 0 & 1 & 1 & 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 0 & 0 & 1 & 0 \\ 0 & 0 & 1 & 1 & 1 & 0 & 1 \\ 0 & 0 & 0 & 0 & 0 & 1 & 0 \end{pmatrix} .
?
(i)

Give an interpretation of AA, A2A^{2}, A3A^{3}.

(ii)

Find DD and LL.

(iii)

Show that LL admits the eigenvalue λ0=0\lambda_{0}=0 (lowest eigenvalue) with eigenvector x→=(1,1,1,1,1,1,1)T\overrightarrow {x} = (1, 1, 1, 1, 1, 1, 1)^{T}.

Problem 21.1.6

A graph G(V,E)G(V,E) is a set of nodes VV (points, vertices) connected by a set of links EE (edges, lines). We assume that there are nn nodes. The adjacency (n×nn \times n) matrix A=A(G)A=A(G) takes the form with 1 in row ii, column jj if ii is connected to jj, and 0 otherwise. Thus AA is a symmetric matrix. Associated with AA is the degree distribution DD, a diagonal matrix with row-sums of AA along the diagonal, and 0's elsewhere. DD describes how many connections each node has. We define the Laplacian as L:=D−AL := D-A. Let A=(aij)A = (a_{ij}), i.e. aija_{ij} are the entries of adjacency matrix. Find the minimum of the weighted sum

S=12∑i,j=1n(xi−xj)2aij S = \frac{1}{2} \sum _{i,j=1}^{n} (x_{i}-x_{j})^{2} a_{ij}

with the constraint x→Tx→=1\overrightarrow {x}^{T} \overrightarrow {x}=1, where x→T=(x1,x2,…,xn)\overrightarrow {x}^{T} = (x_{1}, x_{2}, \ldots , x_{n}). Use the Lagrange multiplier method. The sum is over all pairs of squared distances between nodes which are connected, and so the solution should result in nodes with large numbers of inter-connections being clustered together.

?
Problem 21.1.7

Find the eigenvalues of the three adjacent matrices

A=(101111101),B=(101010101),C=(110010011) A = \begin{pmatrix} 1 & 0 & 1 \\ 1 & 1 & 1 \\ 1 & 0 & 1 \end{pmatrix}, \quad B = \begin{pmatrix} 1 & 0 & 1 \\ 0 & 1 & 0 \\ 1 & 0 & 1 \end{pmatrix}, \quad C = \begin{pmatrix} 1 & 1 & 0 \\ 0 & 1 & 0 \\ 0 & 1 & 1 \end{pmatrix}

provided by three simple graphs. Find the ``energy'' E(G)E(G) of each graph defined by

E(G)=∑j=13∣λj∣. E(G) = \sum _{j=1}^{3} \left|\lambda _{j}\right| .
?
Problem 21.1.8

Consider the two directed graphs with the adjacency matrices

A1=(0010010010010000000110010),A2=(0000110011010000110010010), A_{1} = \begin{pmatrix} 0 & 0 & 1 & 0 & 0 \\ 1 & 0 & 0 & 1 & 0 \\ 0 & 1 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 1 \\ 1 & 0 & 0 & 1 & 0 \end{pmatrix}, \quad A_{2} = \begin{pmatrix} 0 & 0 & 0 & 0 & 1 \\ 1 & 0 & 0 & 1 & 1 \\ 0 & 1 & 0 & 0 & 0 \\ 0 & 1 & 1 & 0 & 0 \\ 1 & 0 & 0 & 1 & 0 \end{pmatrix},
?
(i)

Find the characteristic polynomials and the eigenvalues of A1A_{1} and A2A_{2}.

(ii)

Do the directed graphs admit a Hamilton cycle?

(iii)

Can one remove some of the 1's in A1A_{1} so that one has a permutation matrix?

Problem 21.1.9

Consider the directed graph GG

The directed graph G of Problem 21.1.9.The directed graph G of Problem 21.1.9.

?
(i)

Find the adjacency matrix AA.

(ii)

Calculate 12tr⁡(A2)\frac{1}{2} \operatorname {tr}(A^{2}). How many 2-vertex cycles (loops) does GG have?

(iii)

Calculate 13tr⁡(A3)\frac{1}{3} \operatorname {tr}(A^{3}). How many 3-vertex cycles (triangles) does GG have?

Problem 21.1.10

Let GG be a graph with vertices VV and edges EE. The graph GG is transitive if (v1,v2),(v2,v3)∈E(v_{1},v_{2}), (v_{2},v_{3}) \in E implies that (v1,v3)∈E(v_{1},v_{3}) \in E. The transitive closure G~\widetilde{G} of GG, is the smallest transitive graph G~\widetilde{G} which has GG as a subgraph. Let HH be the adjacency matrix for GG and H~\widetilde{H} be the adjacency matrix for G~\widetilde{G}. If (H)ij=1(H)_{ij}=1 and (H)jk=1(H)_{jk}=1 then (H~)ij=(H~)jk=(H~)ik=1(\widetilde{H})_{ij} = (\widetilde{H})_{jk} = (\widetilde{H})_{ik} = 1. Write a C++ program which finds H~\widetilde{H} for any given adjacency matrix HH. Find the adjacency matrix for the transitive closure of the graph given by the adjacency matrix

H=(0100010001000000001101010). H = \begin{pmatrix} 0 & 1 & 0 & 0 & 0 \\ 1 & 0 & 0 & 0 & 1 \\ 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 1 & 1 \\ 0 & 1 & 0 & 1 & 0 \end{pmatrix} .
?