Restricted greedy clique decompositions and greedy clique decompositions ofK 4-free graphs

A greedy clique decomposition of a graph is obtained by removing maximal cliques from a graph one by one until the graph is empty. It has recently been shown that any greedy clique decomposition of a graph of ordern has at mostn ²/4 cliques. In this paper, we extend this result by showing that for any positive integerp, 3≤p any clique decomposisitioof a graph of ordern obtained by removing maximal cliques of order at leastp one by one until none remain, in which case the remaining edges are removed one by one, has at mostt _p-1( ⁿ ) cliques. Heret _p-1( ⁿ ) is the number of edges in the Turán graph of ordern, which has no complete subgraphs of orderp. In connection with greedy clique decompositions, P. Winkler conjectured that for any greedy clique decompositionC of a graphG of ordern the sum over the number of vertices in each clique ofC is at mostn ²/2. We prove this conjecture forK ₄-free graphs and show that in the case of equality forC andG there are only two possibilities:

1. G?K _n/2,n/2
2. G is complete 3-partite, where each part hasn/3 vertices.

We show that in either caseC is completely determined.     

Connected graphs with a minimal number of spanning trees

The problem studied is the following: Find a simple connected graph G with given numbers of vertices and edges which minimizes the number t_μ(G), the number of spanning trees of the multigraph obtained from G by adding μ parallel edges between every pair of distinct vertices. If G is nearly complete (the number of edges qis ≥(₂^P)?p+2 where p is the number of vertices), then the solution to the minimization problem is unique (up to isomorphism) and the same for all values of μ. The present paper investigates the case whereq<(₂^P)?p+2. In this case the solution is not always unique and there does not always exist a common solution for all values of μ. A (small) class of graphs is given such that for any μ there exists a solution to the problem which is contained in this class. For μ = 0 there is only one graph in the class which solves the problem. This graph is described and the minimum value of t₀(G) is found. In order to derive these results a representation theorem is proved for the cofactors of a special class of matrices which contains the tree matrices associated with graphs.     

Some Algebraic Methods for Calculating the Number of Colorings of a Graph

With an arbitrary graph G having n vertices and m edges, and with an arbitrary natural number p, we associate in a natural way a polynomial R(x ₁,...,x _n) with integer coefficients such that the number of colorings of the vertices of the graph G in p colors is equal to p ^m-n R(0,...,0). Also with an arbitrary maximal planar graph G, we associate several polynomials with integer coefficients such that the number of colorings of the edges of the graph G in 3 colors can be calculated in several ways via the coefficients of each of these polynomials. Bibliography: 2 titles.     

On the maximal order of cyclicity of antisymmetric directed graphs

A directed graph G without loops or multiple edges is said to be antisymmetric if for each pair of distinct vertices of G (say u and v), G contains at most one of the two possible directed edges with end-vertices u and v. In this paper we study edge-sets M of an antisymmetric graph G with the following extremal property: By deleting all edges of M from G we obtain an acyclic graph, but by deleting from G all edges of M except one arbitrary edge, we always obtain a graph containing a cycle. It is proved (in Theorem 1) that if M has the above mentioned property, then the replacing of each edge of M in G by an edge with the opposite direction has the same effect as deletion: the graph obtained is acyclic. Further we study the order of cyclicity of G (= theminimalnumberofedgesinsuchasetM) and the maximal order of cyclicity in an antisymmetric graph with given number n of vertices. It is shown that for n < 10 this number is equal to the maximal number of edge-disjoint circuits in the complete (undirected) graph with n vertices and for n = 10 (and for an infinite set of n's) the first number is greater than the latter.     

On vertex symmetric digraphs

The problem of how “near” we can come to a n-coloring of a given graph is investigated. I.e., what is the minimum possible number of edges joining equicolored vertices if we color the vertices of a given graph with n colors. In its generality the problem of finding such an optimal color assignment to the vertices (given the graph and the number of colors) is NP-complete. For each graph G, however, colors can be assigned to the vertices in such a way that the number of offending edges is less than the total number of edges divided by the number of colors. Furthermore, an Ω(epn) deterministic algorithm for finding such an n-color assignment is exhibited where e is the number of edges and p is the number of vertices of the graph (e?p?n). A priori solutions for the minimal number of offending edges are given for complete graphs; similarly for equicolored K_m in K_p and equicolored graphs in K_p.     

Optimal covers with Hamilton cycles in random graphs

A packing of a graph G with Hamilton cycles is a set of edge-disjoint Hamilton cycles in G. Such packings have been studied intensively and recent results imply that a largest packing of Hamilton cycles in G _n,p a.a.s. has size ?δ(G _n,p )/2?. Glebov, Krivelevich and Szabó recently initiated research on the ‘dual’ problem, where one asks for a set of Hamilton cycles covering all edges of G. Our main result states that for \(\tfrac{{log^{117} n}} {n} \leqslant p \leqslant 1 - n^{ - 1/8}\) , a.a.s. the edges of G _n,p can be covered by ?Δ (G _n,p )/2? Hamilton cycles. This is clearly optimal and improves an approximate result of Glebov, Krivelevich and Szabó, which holds for p ≥ n ^?1+?. Our proof is based on a result of Knox, Kühn and Osthus on packing Hamilton cycles in pseudorandom graphs.     

Sphericity, cubicity, and edge clique covers of graphs

The sphericity sph(G) of a graph G is the minimum dimension d for which G is the intersection graph of a family of congruent spheres in R^d. The edge clique cover number θ(G) is the minimum cardinality of a set of cliques (complete subgraphs) that covers all edges of G. We prove that if G has at least one edge, then sph(G)?θ(G). Our upper bound remains valid for intersection graphs defined by balls in the L_p-norm for 1?p?∞.     

A note on acyclic edge coloring of complete bipartite graphs

An acyclic edge coloring of a graph is a proper edge coloring such that there are no bichromatic (2-colored) cycles. The acyclic chromatic index of a graph is the minimum number k such that there is an acyclic edge coloring using k colors and is denoted by a^′(G). Let Δ=Δ(G) denote the maximum degree of a vertex in a graph G. A complete bipartite graph with n vertices on each side is denoted by K_n,n. Alon, McDiarmid and Reed observed that a^′(K_p−1,p−1)=p for every prime p. In this paper we prove that a^′(K_p,p)≤p+2=Δ+2 when p is prime. Basavaraju, Chandran and Kummini proved that a^′(K_n,n)≥n+2=Δ+2 when n is odd, which combined with our result implies that a^′(K_p,p)=p+2=Δ+2 when p is an odd prime. Moreover we show that if we remove any edge from K_p,p, the resulting graph is acyclically Δ+1=p+1-edge-colorable.     

Random maximal H‐free graphs*

Given a graph H, a random maximal H‐free graph is constructed by the following random greedy process. First assign to each edge of the complete graph on n vertices a birthtime which is uniformly distributed in [0, 1]. At time p=0 start with the empty graph and increase p gradually. Each time a new edge is born, it is included in the graph if this does not create a copy of H. The question is then how many edges such a graph will have when p=1. Here we give asymptotically almost sure bounds on the number of edges if H is a strictly 2‐balanced graph, which includes the case when H is a complete graph or a cycle. Furthermore, we prove the existence of graphs with girth greater than 𝓁 and chromatic number n*y1/(𝓁‐1)+o(1), which improves on previous bounds for 𝓁>3. ©2001 John Wiley & Sons, Inc. Random Struct. Alg., 18: 61–82, 2001     

The number of edge 3-colorings of a planar cubic graph as a permanent

In this paper, we establish that the number of edge 3-colorings of a finite planar cubic graph G, i.e., 3-colorings of its interchange graph H, is equal to 2^?N|Permanent(A)|, where N is the number of edges of G, and A is the 2N × 2N square matrix formed by repeating each row of the N × 2N vertex-directed edge incidence matrix of H (with an arbitrary orientation). As the number of 4-colorings of a finite maximal (fully triangulated) planar graph is equal to four times the number of edge 3-colorings of its planar cubic dual, this result gives a formula for the number of 4-colorings of a finite maximal planar graph.     

On the chromatic forcing number of a random graph

When we wish to compute lower bounds for the chromatic number χ(G) of a graph G, it is of interest to know something about the ‘chromatic forcing number’ f_χ(G), which is defined to be the least number of vertices in a subgraph H of G such that χ(H) = χ(G). We show here that for random graphs G_n,p with n vertices, f_χ(G_n,p) is almost surely at least ($\text{1}\text{2}$?ε)n, despite say the fact that the largest complete subgraph of G_n,p has only about log n vertices.     

A functional limit theorem for random graphs with applications to subgraph count statistics

We consider a random graph that evolves in time by adding new edges at random times (different edges being added at independent and identically distributed times). A functional limit theorem is proved for a class of statistics of the random graph, considered as stochastic processes. the proof is based on a martingale convergence theorem. the evolving random graph allows us to study both the random graph model K_{n, p}, by fixing attention to a fixed time, and the model K_{n, N}, by studying it at the random time it contains exactly N edges. in particular, we obtain the asymptotic distribution as n → ∞ of the number of subgraphs isomorphic to a given graph G, both for K_{n, p} (p fixed) and K_{n, N} (N/(ⁿ₂)→ p). the results are strikingly different; both models yield asymptotically normal distributions, but the variances grow as different powers of n (the variance grows slower for K_n, N; the powers of n usually differ by 1, but sometimes by 3). We also study the number of induced subgraphs of a given type and obtain similar, but more complicated, results. in some exceptional cases, the limit distribution is not normal.     

A Class of Edge Critical 4-Chromatic Graphs

We consider several constructions of edge critical 4-chromatic graphs which can be written as the union of a bipartite graph and a matching. In particular we construct such a graph G with each of the following properties: G can be contracted to a given critical 4-chromatic graph; for each n ≥ 7, G has n vertices and three matching edges (it is also shown that such graphs must have at least \({{8n} \over 5}\) edges); G has arbitrary large girth.     

Adjacency matrices of polarity graphs and of other C 4-free graphs of large size

In this paper we give a method for obtaining the adjacency matrix of a simple polarity graph G _q from a projective plane PG(2, q), where q is a prime power. Denote by ex(n; C ₄) the maximum number of edges of a graph on n vertices and free of squares C ₄. We use the constructed graphs G _q to obtain lower bounds on the extremal function ex(n; C ₄), for some n < q ² + q + 1. In particular, we construct a C ₄-free graph on ${n=q^2 -\sqrt{q}}$ vertices and ${\frac{1}{2} q(q^2-1)-\frac{1}{2}\sqrt{q} (q-1) }$ edges, for a square prime power q.     

Random regular graphs of non-constant degree: Concentration of the chromatic number

In this work we show that with high probability the chromatic number of a graph sampled from the random regular graph model G_n,d for d=o(n^1/5) is concentrated in two consecutive values, thus extending a previous result of Achlioptas and Moore. This concentration phenomena is very similar to that of the binomial random graph model G(n,p) with . Our proof is largely based on ideas of Alon and Krivelevich who proved this two-point concentration result for G(n,p) for p=n^−δ where δ>1/2. The main tool used to derive such a result is a careful analysis of the distribution of edges in G_n,d, relying both on the switching technique and on bounding the probability of exponentially small events in the configuration model.     

Edge search in graphs with restricted test sets

Suppose a graph G(V,E) contains one defective edge e. We search for the endpoints of e by asking questions of the form “Is at least one of the vertices of X an endpoint of e?”, where X is a subset of V with cardinality at most p. Then what is the minimum number c_p(G) of questions, which are needed in the worst case to find e?We solve this search problem suggested by M. Aigner in [M. Aigner, Combinatorial Search, Teubner, 1988] by deriving lower and sharp upper bounds for c_p(G). For the case that G is the complete graph K_n the problem described above is equivalent to the (2,n) group testing problem with test sets of cardinality at most p. We present sharp upper and lower bounds for the worst case number c_p of tests for this group testing problem and show that the maximum difference between the upper and the lower bounds is 3.     

On several sorts of connectivity

For a graph G, we can consider the minimum number of vertices (resp. edges) whose deletion disconnects the graph and such that two of the components created by teh removal of the vertices (resp. the edges, satisfy no additional condition (usual connectivities) or must contain: at least one edge (^#connectivities) or at least one cycle (cyclic connectivities). Thus, we can define six sorts of connectivity for a given graph. In this paper, we give upper bounds for the different types of connectivity and results about the graphs reaching these upper bounds or having connectivity 0 and we investigate relations between these six sorts of connectivity.     

Spanning maximal planar subgraphs of random graphs

We study the threshold for the existence of a spanning maximal planar subgraph in the random graph G_{n, p} . We show that it is very near p = 1/n^? We also discuss the threshold for the existence of a spanning maximal outerplanar subgraph. This is very near p = 1/n^½.     

Heterochromatic tree partition numbers for complete bipartite graphs

An r-edge-coloring of a graph G is a surjective assignment of r colors to the edges of G. A heterochromatic tree is an edge-colored tree in which any two edges have different colors. The heterochromatic tree partition number of an r-edge-colored graph G, denoted by t_r(G), is the minimum positive integer p such that whenever the edges of the graph G are colored with r colors, the vertices of G can be covered by at most p vertex-disjoint heterochromatic trees. In this paper we give an explicit formula for the heterochromatic tree partition number of an r-edge-colored complete bipartite graph K_m,n.     

What is the furthest graph from a hereditary property?

For a graph property P, the edit distance of a graph G from P, denoted E_P(G), is the minimum number of edge modifications (additions or deletions) one needs to apply to G to turn it into a graph satisfying P. What is the furthest graph on n vertices from P and what is the largest possible edit distance from P? Denote this maximal distance by ed(n,P). This question is motivated by algorithmic edge‐modification problems, in which one wishes to find or approximate the value of E_P(G) given an input graph G. A monotone graph property is closed under removal of edges and vertices. Trivially, for any monotone property, the largest edit distance is attained by a complete graph. We show that this is a simple instance of a much broader phenomenon. A hereditary graph property is closed under removal of vertices. We prove that for any hereditary graph property P, a random graph with an edge density that depends on P essentially achieves the maximal distance from P, that is: ed(n,P) = E_P(G(n,p(P))) + o(n²) with high probability. The proofs combine several tools, including strengthened versions of the Szemerédi regularity lemma, properties of random graphs and probabilistic arguments. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008