Centralities of a network and its line graph: an analytical comparison by means of their irregularity

Given a network G, it is known that the Bonacich centrality of the bipartite graph B(G) associated with G can be obtained in terms of the centralities of the line graph L(G) associated with G and the centrality of the network G+gr (whose adjacency matrix is obtained by adding to the adjacency matrix A(G) the diagonal matrix D=b_ij, where b_ii is the degree of node i in G) and conversely. In this contribution, we use the centrality of G to estimate the centrality of G+gr and show that the error committed is bounded by some measure of the irregularity of G. This estimate gives an analytical comparison of the eigenvector centrality of G with the centrality of L(G) in terms of some irregularity measure of G.     

Embedding meshes in Boolean cubes by graph decomposition

This paper explores the embeddings of multidimensional meshes into minimal Boolean cubes by graph decomposition. The dilation and the congestion of the product graph (G₁ × G₂) → (H₁ × H₂) is the maximum of the dilation and congestion for the two embeddings G₁ → H₁ and G₂ → H₂. The graph decomposition technique can be used to improve the average dilation and average congestion. The graph decomposition technique combined with some particular two-dimensional embeddings allows for minimal-expansion, dilation-two, congestion-two embeddings of about 87% of all two-dimensional meshes, with a significantly lower average dilation and congestion than by modified line compression. For three-dimensional meshes we show that the graph decomposition technique, together with two three-dimensional mesh embeddings presented in this paper and modified line compression, yields dilation-two embeddings of more than 96% of all three-dimensional meshes contained in a 512 × 512 × 512 mesh. The graph decomposition technique is also used to generalize the embeddings to meshes with wrap-around. The dilation increases by at most one compared to a mesh without wraparound. The expansion is preserved for the majority of meshes, if a wraparound feature is added to the mesh.     

The super spanning connectivity and super spanning laceability of the enhanced hypercubes

A k -container C(u,v) of a graph G is a set of k disjoint paths between u and v. A k-container C(u,v) of G is a k ^* -container if it contains all vertices of G. A graph G is k ^* -connected if there exists a k ^*-container between any two distinct vertices of G. Therefore, a graph is 1^*-connected (respectively, 2^*-connected) if and only if it is Hamiltonian connected (respectively, Hamiltonian). A graph G is super spanning connected if there exists a k ^*-container between any two distinct vertices of G for every k with 1≤k≤κ(G) where κ(G) is the connectivity of G. A bipartite graph G is k ^* -laceable if there exists a k ^*-container between any two vertices from different partite set of G. A bipartite graph G is super spanning laceable if there exists a k ^*-container between any two vertices from different partite set of G for every k with 1≤k≤κ(G). In this paper, we prove that the enhanced hypercube Q _n,m is super spanning laceable if m is an odd integer and super spanning connected if otherwise.

Minor-embedding in adiabatic quantum computation: I. The parameter setting problem

We show that the NP-hard quadratic unconstrained binary optimization (QUBO) problem on a graph G can be solved using an adiabatic quantum computer that implements an Ising spin-1/2 Hamiltonian, by reduction through minor-embedding of G in the quantum hardware graph U. There are two components to this reduction: embedding and parameter setting. The embedding problem is to find a minor-embedding G _emb of a graph G in U, which is a subgraph of U such that G can be obtained from G _emb by contracting edges. The parameter setting problem is to determine the corresponding parameters, qubit biases and coupler strengths, of the embedded Ising Hamiltonian. In this paper, we focus on the parameter setting problem. As an example, we demonstrate the embedded Ising Hamiltonian for solving the maximum independent set (MIS) problem via adiabatic quantum computation (AQC) using an Ising spin-1/2 system. We close by discussing several related algorithmic problems that need to be investigated in order to facilitate the design of adiabatic algorithms and AQC architectures.     

Computing the hyperbolicity constant of a cubic graph

In this paper we obtain information about the hyperbolicity constant of cubic graphs. They are a very interesting class of graphs with many applications; furthermore, they are also very important in the study of Gromov hyperbolicity, since for any graph G with bounded maximum degree there exists a cubic graph G* such that G is hyperbolic if and only if G* is hyperbolic. We find some characterizations for the cubic graphs which have small hyperbolicity constants, i.e. the graphs which are like trees (in the Gromov sense). Besides, we obtain bounds for the hyperbolicity constant of the complement graph of a cubic graph; our main result of this kind says that for any finite cubic graph G which is not isomorphic either to K₄ or to K_{3, 3}, the inequalities 5k/4≤δ (?)≤3k/2 hold, if k is the length of every edge in G.     

Minor-embedding in adiabatic quantum computation: II. Minor-universal graph design

In Choi (Quantum Inf Process, 7:193–209, 2008), we introduced the notion of minor-embedding in adiabatic quantum optimization. A minor-embedding of a graph G in a quantum hardware graph U is a subgraph of U such that G can be obtained from it by contracting edges. In this paper, we describe the intertwined adiabatic quantum architecture design problem, which is to construct a hardware graph U that satisfies all known physical constraints and, at the same time, permits an efficient minor-embedding algorithm. We illustrate an optimal complete-graph-minor hardware graph. Given a family F{\mathcal{F}} of graphs, a (host) graph U is called F{\mathcal{F}}-minor-universal if for each graph G in F, U{\mathcal{F}, U} contains a minor-embedding of G. The problem for designing a F{{\mathcal{F}}}-minor-universal hardware graph U _sparse in which F{{\mathcal{F}}} consists of a family of sparse graphs (e.g., bounded degree graphs) is open.     

On the edge-tenacity of the middle graph of a graph

We consider the problem of efficiently breaking a graph into small components by removing edges. One measure of how easily this can be done is the edge-tenacity. Given a set of edges of G, the score of S is defined as sc(S)=[| S|+τ (G?S)]/[w(G?S)]. Formally, the edge-tenacity of a graph G is defined as T′(G)=min sc(S), where the minimum is taken over all edge-sets S of G. A subset S of E(G) is said to be a T′-set of G if T′(G)=sc(S). Note that if G is disconnected, the set S may be empty. For any graph G, τ(G?S) is the number of vertices in the largest component of G?S and w(G?S) is the number of components of G?S. The middle graph M(G) of a graph G is the graph obtained from G by inserting a new vertex into every edge of G and by joining by edges those pairs of these new vertices which lie on adjacent edges of G. In this paper, we give the edge-tenacity of the middle graph of specific families of graphs and its relationships with other parameters.     

On the adjacent vertex distinguishing edge colourings of graphs

A k-adjacent vertex distinguishing edge colouring or a k-avd-colouring of a graph G is a proper k-edge colouring of G such that no pair of adjacent vertices meets the same set of colours. The avd-chromatic number, denoted by χ′_a(G), is the minimum number of colours needed in an avd-colouring of G. It is proved that for any connected 3-colourable Hamiltonian graph G, we have χ′_a(G)≤Δ+3.     

Comparing Universal Covers in Polynomial Time

The universal cover T _G of a connected graph G is the unique (possibly infinite) tree covering G, i.e., that allows a locally bijective homomorphism from T _G to G. It is well-known that if a graph G covers a graph H, then their universal covers are isomorphic, and that the latter can be tested in polynomial time by checking if G and H share the same degree refinement matrix. We extend this result to locally injective and locally surjective homomorphisms by following a very different approach. Using linear programming techniques we design two polynomial time algorithms that check if there exists a locally injective or a locally surjective homomorphism, respectively, from a universal cover T _G to a universal cover T _H (both given by their degree matrices). This way we obtain two heuristics for testing the corresponding locally constrained graph homomorphisms. Our algorithm can also be used for testing (subgraph) isomorphism between universal covers, and for checking if there exists a locally injective or locally surjective homomorphism (role assignment) from a given tree to an arbitrary graph H.     

Length two path-centred surface areas for the arrangement graph

We suggest the notion of H-centred surface area of a graph G, where H is a subgraph of G, i.e. the number of vertices in G at a certain distance from H, and focus on the special case when H is a length two path to derive an explicit formula for the length two path-centred surface areas of the general and scalable arrangement graph.     

Maximal matching and edge domination in complete multipartite graphs

For any graph G, let α′(G) and α′_min(G) be the maximum cardinality and minimum cardinality among all maximal matchings in G, respectively, and let γ′(G) and γ_t ′(G) be the edge domination number and edge total domination number of G, respectively. In this paper, we first show some properties of maximal matchings and further determine the exact values of α′(G) and α′_min(G) for a complete multipartite graph G. Then, we disclose relationships between maximal matchings and minimal edge dominating sets, and thus obtain the exact values of γ′(G) and γ_t′(G) for a complete multipartite graph G.     

A sufficient condition for a graph to be an (a,b, k)-critical graph

Let G be a graph, and let a, b, k be integers with 0≤a≤b, k≥0. An [a, b]-factor of graph G is defined as a spanning subgraph F of G such that a≤d _F (x)≤b for each x∈V(G). Then a graph G is called an (a, b, k)-critical graph if after deleting any k vertices of G the remaining graph of G has an [a, b]-factor. In this article, a sufficient condition is given, which is a neighborhood condition for a graph G to be an (a, b, k)-critical graph.     

On general ℋ2 control: from frequency to time domain

This article presents a general formula for discrete-time ?₂ control. It works with the regular and singular case of ?₂ control, i.e. in the case of possibly non-left-invertible matrices G ₁₂ and non-right-invertible matrices G ₂₁, with possible unit circle invariant zeros. In the generic case, it can be simplified and adapted to work with the plant transfer matrix directly, without invoking the matrices of the parameterisation of stabilising controllers. A further result of this article is the presented necessary and sufficient conditions for state-space ?₂ control, under only stabilisability and detectability assumptions. If the conditions are satisfied, an observer-based ?₂ controller is constructed. The corresponding numerical algorithm consists of solving two discrete-time algebraic Riccati systems (DARSs) and two eigen-problems.     

Component connectivity of the hypercubes

The r-component connectivity κ _r (G) of the non-complete graph G is the minimum number of vertices whose deletion results in a graph with at least r components. So, κ₂ is the usual connectivity. In this paper, we determine the r-component connectivity of the hypercube Q _n for r=2, 3, …, n+1, and we classify all the corresponding optimal solutions.     

The rupture degree of trees

For the complete graph K _n , its rupture degree is defined as 1?n; and for a noncomplete connected graph G, its rupture degree is defined by r(G)=max{ω(G ? X)?|X|?m(G ? X):X ? V(G), ω(G ? X) > 1 }, where ω(G ? X) is the number of components of G ? X and m(G ? X) is the order of a largest component of G ? X. It is shown that this parameter can be well used to measure the vulnerability of networks. Li and Li proved in 2004 that computing the rupture degree for a general graph is NP-complete. In this paper, we give a recursive algorithm for computing the rupture degree of trees, and determine the maximum and minimum rupture degree of trees with given order and maximum degree.     

Finding Maximum Induced Matchings in Subclasses of Claw-Free and <Emphasis Type="Italic">P</Emphasis><Subscript>5</Subscript>-Free Graphs,and in Graphs with Matching and Induced Matching of Equal Maximum Size

In a graph G a matching is a set of edges in which no two edges have a common endpoint. An induced matching is a matching in which no two edges are linked by an edge of G. The maximum induced matching (abbreviated MIM) problem is to find the maximum size of an induced matching for a given graph G. This problem is known to be NP-hard even on bipartite graphs or on planar graphs. We present a polynomial time algorithm which given a graph G either finds a maximum induced matching in G, or claims that the size of a maximum induced matching in G is strictly less than the size of a maximum matching in G. We show that the MIM problem is NP-hard on line-graphs, claw-free graphs, chair-free graphs, Hamiltonian graphs and r-regular graphs for r \geq 5. On the other hand, we present polynomial time algorithms for the MIM problem on (P ₅,D _m )-free graphs, on (bull, chair)-free graphs and on line-graphs of Hamiltonian graphs.     

Bounds for the 2-domination number of toroidal grid graphs

A k-dominating set for a graph G(V, E) is a set of vertices D? V such that every vertex v∈V\ D is adjacent to at least k vertices in D. The k-domination number of G, denoted by γ _k (G), is the cardinality of a smallest k-dominating set of G. Here we establish lower and upper bounds of γ _k (C _m ×C _n ) for k=2. In some cases, these bounds agree so that the exact 2-domination number is obtained.     

Some consequences on the planar three-index transportation problem

In this study, some algebraic characterizations of the coefficient matrix A of the planar three-index transportation problem are derived and the equivalent formulation of this problem is obtained using the Kronecker product. It is shown that eigenvectors of the matrix G ⁺ G are characterized in terms of eigenvectors of the matrix A ⁺ A , where G ⁺ is the Moore–Penrose inverse of the coefficient matrix G of the equivalent problem.     

On the pseudoachromatic number of join of graphs

Given an undirected graph G = (V, E), with vertex set V and edge set E, the pseudoachromatic number ψ(G) of the graph G is the maximum number of colors used to color the vertices in such a way that, for any given pair of colors i, j there exists an edge e = (u, v) ∈ E(G) such that u is colored i and v is colored j. In this paper we give a complete characterization of when the ψ of the join of any two graphs is the sum of the ψ of the two graphs.     

Toughness of the corona of two graphs

The toughness of a non-complete graph G=(V, E) is defined as τ(G)=min{|S|/ω(G?S)}, where the minimum is taken over all cutsets S of vertices of G and ω(G?S) denotes the number of components of the resultant graph G?S by deletion of S. The corona of two graphs G and H, written as G° H, is the graph obtained by taking one copy of G and |V(G)| copies of H, and then joining the ith vertex of G to every vertex in the ith copy of H. In this paper, we investigate the toughness of this kind of graphs and obtain the exact value for the corona of two graphs belonging to some families as paths, cycles, stars, wheels or complete graphs.