On MAXCUT in strictly supercritical random graphs,and coloring of random graphs and random tournaments

We use a theorem by Ding, Lubetzky, and Peres describing the structure of the giant component of random graphs in the strictly supercritical regime, in order to determine the typical size of MAXCUT of in terms of ɛ. We then apply this result to prove the following conjecture by Frieze and Pegden. For every , there exists such that w.h.p. is not homomorphic to the cycle on vertices. We also consider the coloring properties of biased random tournaments. A p‐random tournament on n vertices is obtained from the transitive tournament by reversing each edge independently with probability p. We show that for the chromatic number of a p‐random tournament behaves similarly to that of a random graph with the same edge probability. To treat the case we use the aforementioned result on MAXCUT and show that in fact w.h.p. one needs to reverse edges to make it 2‐colorable.     

Packing perfect matchings in random hypergraphs

We introduce a new procedure for generating the binomial random graph/hypergraph models, referred to as online sprinkling. As an illustrative application of this method, we show that for any fixed integer , the binomial ‐uniform random hypergraph contains edge‐disjoint perfect matchings, provided , where is an integer depending only on . Our result for is asymptotically optimal and for is optimal up to the factor. This significantly improves a result of Frieze and Krivelevich.     

Chromatic thresholds in sparse random graphs

The chromatic threshold of a graph H with respect to the random graph G (n, p ) is the infimum over d > 0 such that the following holds with high probability: the family of H‐free graphs with minimum degree has bounded chromatic number. The study of was initiated in 1973 by Erd?s and Simonovits. Recently was determined for all graphs H . It is known that for all fixed , but that typically if Here we study the problem for sparse random graphs. We determine for most functions when , and also for all graphs H with © 2017 Wiley Periodicals, Inc. Random Struct. Alg., 51, 215–236, 2017     

The chromatic number of dense random graphs

The chromatic number of a graph G is defined as the minimum number of colors required for a vertex coloring where no two adjacent vertices are colored the same. The chromatic number of the dense random graph where is constant has been intensively studied since the 1970s, and a landmark result by Bollobás in 1987 first established the asymptotic value of . Despite several improvements of this result, the exact value of remains open. In this paper, new upper and lower bounds for are established. These bounds are the first ones that match each other up to a term of size o(1) in the denominator: they narrow down the coloring rate of to an explicit interval of length o(1), answering a question of Kang and McDiarmid.     

The random connection model: Connectivity,edge lengths,and degree distributions

Consider the random graph whose vertex set is a Poisson point process of intensity n on . Any two vertices are connected by an edge with probability , independently of all other edges, and independent of the other points of . d is the toroidal metric, r > 0 and is non‐increasing and . Under suitable conditions on g, almost surely, the critical parameter M_n for which does not have any isolated nodes satisfies . Let , and θ be the volume of the unit ball in . Then for all , is connected with probability approaching one as . The bound can be seen to be tight for the usual random geometric graph obtained by setting . We also prove some useful results on the asymptotic behavior of the length of the edges and the degree distribution in the connectivity regime. The results in this paper work for connection functions g that are not necessarily compactly supported but satisfy .     

Interpolating between random walk and rotor walk

We introduce a family of stochastic processes on the integers, depending on a parameter and interpolating between the deterministic rotor walk () and the simple random walk (). This p‐rotor walk is not a Markov chain but it has a local Markov property: for each the sequence of successive exits from is a Markov chain. The main result of this paper identifies the scaling limit of the p‐rotor walk with two‐sided i.i.d. initial rotors. The limiting process takes the form , where is a doubly perturbed Brownian motion, that is, it satisfies the implicit equation (1) for all . Here is a standard Brownian motion and are constants depending on the marginals of the initial rotors on and respectively. Chaumont and Doney have shown that Equation 1 has a pathwise unique solution , and that the solution is almost surely continuous and adapted to the natural filtration of the Brownian motion. Moreover, and . This last result, together with the main result of this paper, implies that the p‐rotor walk is recurrent for any two‐sided i.i.d. initial rotors and any .     

Arboricity and spanning‐tree packing in random graphs

We study the arboricity and the maximum number of edge‐disjoint spanning trees of the classical random graph . For all , we show that, with high probability, is precisely the minimum of and , where is the minimum degree of the graph and denotes the number of edges. Moreover, we explicitly determine a sharp threshold value for such that the following holds. Above this threshold, equals and equals . Below this threshold, equals , and we give a two‐value concentration result for the arboricity in that range. Finally, we include a stronger version of these results in the context of the random graph process where the edges are randomly added one by one. A direct application of our result gives a sharp threshold for the maximum load being at most in the two‐choice load balancing problem, where .     

Chromatic thresholds in dense random graphs

The chromatic threshold of a graph H with respect to the random graph G (n, p ) is the infimum over d > 0 such that the following holds with high probability: the family of H‐free graphs with minimum degree has bounded chromatic number. The study of the parameter was initiated in 1973 by Erd?s and Simonovits, and was recently determined for all graphs H . In this paper we show that for all fixed , but that typically if . We also make significant progress towards determining for all graphs H in the range . In sparser random graphs the problem is somewhat more complicated, and is studied in a separate paper. © 2017 Wiley Periodicals, Inc. Random Struct. Alg., 51, 185–214, 2017     

On replica symmetry of large deviations in random graphs

The following question is due to Chatterjee and Varadhan (2011). Fix and take , the Erd?s‐Rényi random graph with edge density p, conditioned to have at least as many triangles as the typical . Is G close in cut‐distance to a typical ? Via a beautiful new framework for large deviation principles in , Chatterjee and Varadhan gave bounds on the replica symmetric phase, the region of where the answer is positive. They further showed that for any small enough p there are at least two phase transitions as r varies. We settle this question by identifying the replica symmetric phase for triangles and more generally for any fixed d‐regular graph. By analyzing the variational problem arising from the framework of Chatterjee and Varadhan we show that the replica symmetry phase consists of all such that lies on the convex minorant of where is the rate function of a binomial with parameter p. In particular, the answer for triangles involves rather than the natural guess of where symmetry was previously known. Analogous results are obtained for linear hypergraphs as well as the setting where the largest eigenvalue of is conditioned to exceed the typical value of the largest eigenvalue of . Building on the work of Chatterjee and Diaconis (2012) we obtain additional results on a class of exponential random graphs including a new range of parameters where symmetry breaking occurs. En route we give a short alternative proof of a graph homomorphism inequality due to Kahn (2001) and Galvin and Tetali (2004). © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 109–146, 2015     

Finding paths in sparse random graphs requires many queries

We discuss a new algorithmic type of problem in random graphs studying the minimum number of queries one has to ask about adjacency between pairs of vertices of a random graph in order to find a subgraph which possesses some target property with high probability. In this paper we focus on finding long paths in when for some fixed constant . This random graph is known to have typically linearly long paths. To have edges with high probability in one clearly needs to query at least pairs of vertices. Can we find a path of length economically, i.e., by querying roughly that many pairs? We argue that this is not possible and one needs to query significantly more pairs. We prove that any randomised algorithm which finds a path of length with at least constant probability in with must query at least pairs of vertices. This is tight up to the factor. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 71–85, 2017     

Decomposing a graph into expanding subgraphs

A paradigm that was successfully applied in the study of both pure and algorithmic problems in graph theory can be colloquially summarized as stating that any graph is close to being the disjoint union of expanders. Our goal in this paper is to show that in several of the instantiations of the above approach, the quantitative bounds that were obtained are essentially best possible. Three examples of our results are the following:

• A classical result of Lipton, Rose and Tarjan from 1979 states that if is a hereditary family of graphs and every graph in has a vertex separator of size , then every graph in has O(n) edges. We construct a hereditary family of graphs with vertex separators of size such that not all graphs in the family have O(n) edges.
• Trevisan and Arora‐Barak‐Steurer have recently shown that given a graph G, one can remove only 1% of its edges to obtain a graph in which each connected component has good expansion properties. We show that in both of these decomposition results, the expansion properties they guarantee are essentially best possible, even when one is allowed to remove 99% of G's edges.
• Sudakov and the second author have recently shown that every graph with average degree d contains an n‐vertex subgraph with average degree at least and vertex expansion . We show that one cannot guarantee a better vertex expansion even if allowing the average degree to be O(1).

The above results are obtained as corollaries of a new family of graphs which we construct in this paper. These graphs have a super‐linear number of edges and nearly logarithmic girth, yet each of their subgraphs has (optimally) poor expansion properties.     

On the variational problem for upper tails in sparse random graphs

What is the probability that the number of triangles in , the Erd?s‐Rényi random graph with edge density p , is at least twice its mean? Writing it as , already the order of the rate function r (n, p ) was a longstanding open problem when p = o (1), finally settled in 2012 by Chatterjee and by DeMarco and Kahn, who independently showed that for ; the exact asymptotics of r (n, p ) remained unknown. The following variational problem can be related to this large deviation question at : for δ > 0 fixed, what is the minimum asymptotic p‐relative entropy of a weighted graph on n vertices with triangle density at least (1 + δ )p ³? A beautiful large deviation framework of Chatterjee and Varadhan (2011) reduces upper tails for triangles to a limiting version of this problem for fixed p . A very recent breakthrough of Chatterjee and Dembo extended its validity to for an explicit α > 0, and plausibly it holds in all of the above sparse regime. In this note we show that the solution to the variational problem is when vs. when (the transition between these regimes is expressed in the count of triangles minus an edge in the minimizer). From the results of Chatterjee and Dembo, this shows for instance that the probability that for has twice as many triangles as its expectation is where . Our results further extend to k‐cliques for any fixed k , as well as give the order of the upper tail rate function for an arbitrary fixed subgraph when . © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 420–436, 2017     

High degrees in random recursive trees

For , let T_n be a random recursive tree (RRT) on the vertex set . Let be the degree of vertex v in T_n, that is, the number of children of v in T_n. Devroye and Lu showed that the maximum degree Δ_n of T_n satisfies almost surely; Goh and Schmutz showed distributional convergence of along suitable subsequences. In this work we show how a version of Kingman's coalescent can be used to access much finer properties of the degree distribution in T_n. For any , let . Also, let be a Poisson point process on with rate function . We show that, up to lattice effects, the vectors converge weakly in distribution to . We also prove asymptotic normality of when slowly, and obtain precise asymptotics for when and is not too large. Our results recover and extends the previous distributional convergence results on maximal and near‐maximal degrees in RRT.     

Spectra of large diluted but bushy random graphs

We compute an asymptotic expansion in of the limit in of the empirical spectral measure of the adjacency matrix of an Erd?s‐Rényi random graph with vertices and parameter . We present two different methods, one of which is valid for the more general setting of locally tree‐like graphs. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 49, 160–184, 2016     

The number of Sidon sets and the maximum size of Sidon sets contained in a sparse random set of integers

A set A of non‐negative integers is called a Sidon set if all the sums , with and a₁, , are distinct. A well‐known problem on Sidon sets is the determination of the maximum possible size F(n) of a Sidon subset of . Results of Chowla, Erd?s, Singer and Turán from the 1940s give that . We study Sidon subsets of sparse random sets of integers, replacing the ‘dense environment’ by a sparse, random subset R of , and ask how large a subset can be, if we require that S should be a Sidon set. Let be a random subset of of cardinality , with all the subsets of equiprobable. We investigate the random variable , where the maximum is taken over all Sidon subsets , and obtain quite precise information on for the whole range of m, as illustrated by the following abridged version of our results. Let be a fixed constant and suppose . We show that there is a constant such that, almost surely, we have . As it turns out, the function is a continuous, piecewise linear function of a that is non‐differentiable at two ‘critical’ points: a = 1/3 and a = 2/3. Somewhat surprisingly, between those two points, the function is constant. Our approach is based on estimating the number of Sidon sets of a given cardinality contained in [n]. Our estimates also directly address a problem raised by Cameron and Erd?s (On the number of sets of integers with various properties, Number theory (Banff, AB, 1988), de Gruyter, Berlin, 1990, pp. 61–79). © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 46, 1–25, 2015     

Cliques in dense inhomogeneous random graphs

The theory of dense graph limits comes with a natural sampling process which yields an inhomogeneous variant of the Erd?s–Rényi random graph. Here we study the clique number of these random graphs. We establish the concentration of the clique number of for each fixed n , and give examples of graphons for which exhibits wild long‐term behavior. Our main result is an asymptotic formula which gives the almost sure clique number of these random graphs. We obtain a similar result for the bipartite version of the problem. We also make an observation that might be of independent interest: Every graphon avoiding a fixed graph is countably‐partite. © The Authors Random Structures & Algorithms Published byWiley Periodicals, Inc. Random Struct. Alg., 2016 © 2017 The Authors Random Structures & Algorithms Published by Wiley Periodicals, Inc. Random Struct. Alg., 51, 275–314, 2017     

A phase transition in the evolution of bootstrap percolation processes on preferential attachment graphs

The theme of this paper is the analysis of bootstrap percolation processes on random graphs generated by preferential attachment. This is a class of infection processes where vertices have two states: they are either infected or susceptible. At each round every susceptible vertex which has at least infected neighbours becomes infected and remains so forever. Assume that initially vertices are randomly infected, where is the total number of vertices of the graph. Suppose also that , where is the average degree. We determine a critical function such that when , complete infection occurs with high probability as , but when , then with high probability the process evolves only for a bounded number of rounds and the final set of infected vertices is asymptotically equal to .     

Coloring graphs of various maximum degree from random lists

Let G = G(n) be a graph on n vertices with maximum degree Δ =Δ (n). Assign to each vertex v of G a list L(v) of colors by choosing each list independently and uniformly at random from all k‐subsets of a color set of size . Such a list assignment is called a random ‐list assignment. In this paper, we are interested in determining the asymptotic probability (as n →∞) of the existence of a proper coloring φ of G, such that for every vertex v of G, a so‐called L‐coloring. We give various lower bounds on σ, in terms of n, k, and Δ, which ensures that with probability tending to 1 as n →∞ there is an L‐coloring of G. In particular, we show, for all fixed k and growing n, that if and , then the probability that G has an L‐coloring tends to 1 as . If and , then the same conclusion holds provided that . We also give related results for other bounds on Δ, when k is constant or a strictly increasing function of n.     

Biased games on random boards

In this paper we analyze biased Maker‐Breaker games and Avoider‐Enforcer games, both played on the edge set of a random board . In Maker‐Breaker games there are two players, denoted by Maker and Breaker. In each round, Maker claims one previously unclaimed edge of G and Breaker responds by claiming b previously unclaimed edges. We consider the Hamiltonicity game, the perfect matching game and the k‐vertex‐connectivity game, where Maker's goal is to build a graph which possesses the relevant property. Avoider‐Enforcer games are the reverse analogue of Maker‐Breaker games with a slight modification, where the two players claim at least 1 and at least b previously unclaimed edges per move, respectively, and Avoider aims to avoid building a graph which possesses the relevant property. Maker‐Breaker games are known to be “bias‐monotone”, that is, if Maker wins the (1,b) game, he also wins the game. Therefore, it makes sense to define the critical bias of a game, b ^*, to be the “breaking point” of the game. That is, Maker wins the (1,b) game whenever and loses otherwise. An analogous definition of the critical bias exists for Avoider‐Enforcer games: here, the critical bias of a game b ^* is such that Avoider wins the (1,b) game for every , and loses otherwise. We prove that, for every is typically such that the critical bias for all the aforementioned Maker‐Breaker games is asymptotically . We also prove that in the case , the critical bias is . These results settle a conjecture of Stojakovi? and Szabó. For Avoider‐Enforcer games, we prove that for , the critical bias for all the aforementioned games is . © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 46,651–676, 2015     

Counting dense connected hypergraphs via the probabilistic method

In 1990 Bender, Canfield, and McKay gave an asymptotic formula for the number of connected graphs on with m edges, whenever and . We give an asymptotic formula for the number of connected r‐uniform hypergraphs on with m edges, whenever is fixed and with , that is, the average degree tends to infinity. This complements recent results of Behrisch, Coja‐Oghlan, and Kang (the case ) and the present authors (the case , ie, “nullity” or “excess” o(n)). The proof is based on probabilistic methods, and in particular on a bivariate local limit theorem for the number of vertices and edges in the largest component of a certain random hypergraph. The arguments are much simpler than in the sparse case; in particular, we can use “smoothing” techniques to directly prove the local limit theorem, without needing to first prove a central limit theorem.