Clique coverings of the edges of a random graph

The edges of the random graph (with the edge probabilityp=1/2) can be covered usingO(n ²lnlnn/(lnn)²) cliques. Hence this is an upper bound on the intersection number (also called clique cover number) of the random graph. A lower bound, obtained by counting arguments, is (1–)n ²/(2lgn)².Research supported in part by ONR Grant N00014-85K0570 and by NSA/MSP Grant MDA904-90-H-4011.     

On a random graph evolving by degrees

We consider a random (multi)graph growth process {Gm} on a vertex set [n], which is a special case of a more general process proposed by Laci Lovász in 2002. G₀ is empty, and Gm+1 is obtained from Gm by inserting a new edge e at random. Specifically, the conditional probability that e joins two currently disjoint vertices, i and j, is proportional to (di+α)(dj+α), where di, dj are the degrees of i, j in Gm, and α>0 is a fixed parameter. The limiting case α=∞ is the Erd?s-Rényi graph process. We show that whp Gm contains a unique giant component iff c:=2m/n>cα=α/(1+α), and the size of this giant is asymptotic to , where c^∗<cα is the root of . A phase transition window is proved to be contained, essentially, in [cα−An−1/3,cα+Bn−1/4], and we conjecture that 1/4 may be replaced with 1/3. For the multigraph version, {MGm}, we show that MGm is connected whp iff m?mn:=n1+α−1. We conjecture that, for α>1, mn is the threshold for connectedness of Gm itself.     

How many random edges make a graph hamiltonian?

A threshold for a graph propertyQ in the scale of random graph spacesG _n,p is ap-band across which the asymptotic probability ofQ jumps from 0 to 1. We locate a sharp threshold for the property of having a hamiltonian path.     

Hitting time fork edge-disjoint spanning trees in a random graph

We show that in almost every random graph process, the hitting time for havingk edge-disjoint spanning trees equals the hitting time for having minimum degreek.     

The longest path in a random graph

A random graph with (1+ε)n/2 edges contains a path of lengthcn. A random directed graph with (1+ε)n edges contains a directed path of lengthcn. This settles a conjecture of Erdõs.     

Sandwiching random graphs: universality between random graph models

The goal of this paper is to establish a connection between two classical models of random graphs: the random graph G(n,p) and the random regular graph G_d(n). This connection appears to be very useful in deriving properties of one model from the other and explains why many graph invariants are universal. In particular, one obtains one-line proofs of several highly non-trivial and recent results on G_d(n).     

On the minimal number of edges in color-critical graphs

A graphG isk-critical if it has chromatic numberk, but every proper subgraph of it is (k?1)-colorable. This paper is devoted to investigating the following question: for givenk andn, what is the minimal number of edges in ak-critical graph onn vertices, with possibly some additional restrictions imposed? Our main result is that for everyk≥4 andn>k this number is at least $\left( {\frac{{k - 1}}{2} + \frac{{k - 3}}{{2(k^2 - 2k - 1)}}} \right)n$ , thus improving a result of Gallai from 1963. We discuss also the upper bounds on the minimal number of edges ink-critical graphs and provide some constructions of sparsek-critical graphs. A few applications of the results to Ramsey-type problems and problems about random graphs are described.     

The pebbling threshold of the square of cliques

Given an initial configuration of pebbles on a graph, one can move pebbles in pairs along edges, at the cost of one of the pebbles moved, with the objective of reaching a specified target vertex. The pebbling number of a graph is the minimum number of pebbles so that every configuration of that many pebbles can reach any chosen target. The pebbling threshold of a sequence of graphs is roughly the number of pebbles so that almost every (resp. almost no) configuration of asymptotically more (resp. fewer) pebbles can reach any chosen target. In this paper we find the pebbling threshold of the sequence of squares of cliques, improving upon an earlier result of Boyle and verifying an important instance of a probabilistic version of Graham's product conjecture.     

The effect on the Laplacian spectral radius of a graph by adding or grafting edges

This paper investigates how the Laplacian spectral radius behaves when the graph is perturbed by adding or grafting edges.     

Counting canonical partitions in the random graph

Joyce trees have concrete realizations as J-trees of sequences of 0’s and 1’s. Algorithms are given for computing the number of minimal height J-trees of d-ary sequences with n leaves and the number of them with minimal parent passing numbers to obtain polynomials ρ _n (d) for the full collection and α _n (d) for the subcollection. The number of traditional Joyce trees is the tangent number α _n (1); α _n (2) is the number of cells in the canonical partition by Laflamme, Sauer and Vuksanovic of n-element subsets of the infinite random (Rado) graph; and ρ _n (2) is the number of weak embedding types of rooted n-leaf J-trees of sequences of 0’s and 1’s. The author thanks the University of Tel Aviv for hospitality in April 2004 when much of this work was done.     

Survival time of a random graph

LetV _n ={1, 2, ...,n} ande ₁,e ₂, ...,e _N ,N= be a random permutation ofV _n ⁽²⁾. LetE _t={e ₁,e ₂, ...,e _t} andG _t=(V _n ,E _t ). If is a monotone graph property then the hitting time() for is defined by=()=min {t:G _t }. Suppose now thatG starts to deteriorate i.e. loses edges in order ofage, e ₁,e ₂, .... We introduce the idea of thesurvival time =() defined by t = max {u:(V _n, {e _u,e _u+1, ...,e _T }) }. We study in particular the case where isk-connectivity. We show that

The concentration of the chromatic number of random graphs

We prove that for every constant >0 the chromatic number of the random graphG(n, p) withp=n ^–1/2– is asymptotically almost surely concentrated in two consecutive values. This implies that for any <1/2 and any integer valued functionr(n)O(n ) there exists a functionp(n) such that the chromatic number ofG(n,p(n)) is preciselyr(n) asymptotically almost surely.Research supported in part by a USA Israeli BSF grant and by a grant from the Israel Science Foundation.Research supported in part by a Charles Clore Fellowship.     

Expected values of parameters associated with the minimum rank of a graph

We investigate the expected value of various graph parameters associated with the minimum rank of a graph, including minimum rank/maximum nullity and related Colin de Verdière-type parameters. Let G(v,p) denote the usual Erd?s-Rényi random graph on v vertices with edge probability p. We obtain bounds for the expected value of the random variables mr(G(v,p)), M(G(v,p)), ν(G(v,p)) and ξ(G(v,p)), which yield bounds on the average values of these parameters over all labeled graphs of order v.     

On the number of vertices and edges of the Buneman graph

In 1971, Peter Buneman proposed a way to construct a tree from a collection of pairwise compatible splits. This construction immediately generalizes to arbitrary collections of splits, and yields a connected median graph, called the Buneman graph. In this paper, we prove that the vertices and the edges of this graph can be described in a very simple way: given a collection of splitsS, the vertices of the Buneman graph correspond precisely to the subsetsS′ ofS such that the splits inS′ are pairwise incompatible and the edges correspond to pairs (S′, S) withS′ as above andS∈S′. Using this characterization, it is much more straightforward to construct the vertices of the Buneman graph than using prior constructions. We also recover as an immediate consequence of this enumeration that the Buneman graph is a tree, that is, that the number of vertices exceeds the number of edges (by one), if and only if any two distinct splits inS are compatible.     

Asymptotic theory for the multidimensional random on-line nearest-neighbour graph

The on-line nearest-neighbour graph on a sequence of n$n$ uniform random points in (0,1)^d${(0,1)}^d$ (d∈N$d\in \mathbb{N}$) joins each point after the first to its nearest neighbour amongst its predecessors. For the total power-weighted edge-length of this graph, with weight exponent α∈(0,d/2]$\alpha \in (0,d/2]$, we prove O(max{n^1−(2α/d),logn})$O(max\{n^{1-(2\alpha /d)},logn\})$ upper bounds on the variance. On the other hand, we give an n→∞$n\to \infty$ large-sample convergence result for the total power-weighted edge-length when α>d/2$\alpha >d/2$. We prove corresponding results when the underlying point set is a Poisson process of intensity n$n$.     

On random minimum length spanning trees

We extend and strengthen the result that, in the complete graphK _n with independent random edge-lengths uniformly distributed on [0, 1], the expected length of the minimum spanning tree tends to(3) asn. In particular, ifK _n is replaced by the complete bipartite graphK _{n, n} then there is a corresponding limit of 2 (3).     

Covering the edges of a graph by three odd subgraphs

We prove that any finite simple graph can be covered by three of its odd subgraphs, and we construct an infinite sequence of graphs where an edge‐disjoint covering by three odd subgraphs is not possible. © 2006 Wiley Periodicals, Inc. J Graph Theory 53: 77–82, 2006     

Edges not contained in triangles and the distribution of contractible edges in a 4-connected graph

We prove results concerning the distribution of 4-contractible edges in a 4-connected graph G in connection with the edges of G not contained in a triangle. As a corollary, we show that if G is 4-regular 4-connected graph, then the number of 4-contractible edges of G is at least one half of the number of edges of G not contained in a triangle.