First-order and monadic properties of highly sparse random graphs

A random graph is said to obey the (monadic) zero–one k-law if, for any property expressed by a first-order formula (a second-order monadic formula) with a quantifier depth of at most k, the probability of the graph having this property tends to either zero or one. It is well known that the random graph G(n, n^–α) obeys the (monadic) zero–one k-law for any k ∈ ? and any rational α > 1 other than 1 + 1/m (for any positive integer m). It is also well known that the random graph does not obey both k-laws for the other rational positive α and sufficiently large k. In this paper, we obtain lower and upper bounds on the largest at which both zero–one k-laws hold for α = 1 + 1/m.     

Bisecting sparse random graphs

Consider partitions of the vertex set of a graph G into two sets with sizes differing by at most 1: the bisection width of G is the minimum over all such partitions of the number of “cross edges” between the parts. We are interested in sparse random graphs G_{n, c/n} with edge probability c/n. We show that, if c>ln 4, then the bisection width is Ω(n) with high probability; while if c<ln 4, then it is equal to 0 with high probability. There are corresponding threshold results for partitioning into any fixed number of parts. ©2001 John Wiley & Sons, Inc. Random Struct. Alg., 18, 31–38, 2001     

Countable sparse random graphs

For each irrational a, 0<a<1, a particular countable graph G is defined which mirrors the asymptotic behavior of the random graph G(n, p) with edge probability p = n^?a.     

Right-convergence of sparse random graphs

The paper is devoted to the problem of establishing right-convergence of sparse random graphs. This concerns the convergence of the logarithm of number of homomorphisms from graphs or hyper-graphs \(\mathbb{G }_N, N\ge 1\) to some target graph \(W\) . The theory of dense graph convergence, including random dense graphs, is now well understood (Borgs et al. in Ann Math 176:151–219, 2012; Borgs et al. in Adv Math 219:1801–1851, 2008; Chatterjee and Varadhan in Eur J Comb 32:1000–1017, 2011; Lovász and Szegedy in J Comb Theory Ser B 96:933–957, 2006), but its counterpart for sparse random graphs presents some fundamental difficulties. Phrased in the statistical physics terminology, the issue is the existence of the limits of appropriately normalized log-partition functions, also known as free energy limits, for the Gibbs distribution associated with \(W\) . In this paper we prove that the sequence of sparse Erdös-Rényi graphs is right-converging when the tensor product associated with the target graph \(W\) satisfies a certain convexity property. We treat the case of discrete and continuous target graphs \(W\) . The latter case allows us to prove a special case of Talagrand’s recent conjecture [more accurately stated as level III Research Problem 6.7.2 in his recent book (Talagrand in Mean Field Models for Spin Glasses: Volume I: Basic examples. Springer, Berlin, 2010)], concerning the existence of the limit of the measure of a set obtained from \(\mathbb{R }^N\) by intersecting it with linearly in \(N\) many subsets, generated according to some common probability law. Our proof is based on the interpolation technique, introduced first by Guerra and Toninelli (Commun Math Phys 230:71–79, 2002) and developed further in (Abbe and Montanari in On the concentration of the number of solutions of random satisfiability formulas, 2013; Bayati et al. in Ann Probab Conference version in Proceedings of 42nd Ann. Symposium on the Theory of Computing (STOC), 2010; Contucci et al. in Antiferromagnetic Potts model on the Erdös-Rényi random graph, 2011; Franz and Leone in J Stat Phys 111(3/4):535–564, 2003; Franz et al. in J Phys A Math Gen 36:10967–10985, 2003; Montanari in IEEE Trans Inf Theory 51(9):3221–3246, 2005; Panchenko and Talagrand in Probab Theory Relat Fields 130:312–336, 2004). Specifically, Bayati et al. (Ann Probab Conference version in Proceedings of 42nd Ann. Symposium on the Theory of Computing (STOC), 2010) establishes the right-convergence property for Erdös-Rényi graphs for some special cases of \(W\) . In this paper most of the results in Bayati et al. (Ann Probab Conference version in Proceedings of 42nd Ann. Symposium on the Theory of Computing (STOC), 2010) follow as a special case of our main theorem.     

The diameter of sparse random graphs

We derive an expression of the form c ln n + o(ln n) for the diameter of a sparse random graph with a specified degree sequence. The result holds asymptotically almost surely, assuming that certain convergence and supercriticality conditions are met, and is applicable to the classical random graph G_n,p with np = Θ(1) + 1, as well as certain random power law graphs. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2007     

Induced trees in sparse random graphs

The random graphG(n, p) onn vertices with edge probabilityp = c/n contains an induced tree of order _c n where _c > 0 forc > 1. This proves a conjecture of Erdös and Palka.     

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     

Large holes in sparse random graphs

We show that there is a function α(r) such that for each constantr≧3, almost everyr-regular graph onn vertices has a hole (vertex induced cycle) of size at least α(r)n asn→∞. We also show that there is a function β(c) such that forc>0 large enough,G _{n, p} ,p=c/n almost surely has a hole of size at least β(c)n asn→∞.     

Long paths in sparse random graphs

We consider random graphs withn labelled vertices in which edges are chosen independently and with probabilityc/n. We prove that almost every random graph of this kind contains a path of length ≧(1 −α(c))n where α(c) is an exponentially decreasing function ofc. Dedicated to Tibor Gallai on his seventieth birthday     

A note on coloring sparse random graphs

Coja-Oghlan and Taraz [Amin Coja-Oghlan, Anusch Taraz, Exact and approximative algorithms for coloring , Random Structures and Algorithms 24 (3) (2004) 259-278] presented a graph coloring algorithm that has expected linear running time for random graphs with edge probability p satisfying np≤1.01. In this work, we develop their analysis by exploiting generating function techniques. We show that, in fact, their algorithm colors G_n,p with the minimal number of colors and has expected linear running time, provided that np≤1.33.     

Regular pairs in sparse random graphs I

We consider bipartite subgraphs of sparse random graphs that are regular in the sense of Szemerédi and, among other things, show that they must satisfy a certain local pseudorandom property. This property and its consequences turn out to be useful when considering embedding problems in subgraphs of sparse random graphs. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 22: 359–434, 2003     

Spectral techniques applied to sparse random graphs

We analyze the eigenvalue gap for the adjacency matrices of sparse random graphs. Let λ₁ ≥ … ≥ λ_n be the eigenvalues of an n‐vertex graph, and let λ = max[λ₂,|λ_n|]. Let c be a large enough constant. For graphs of average degree d = c log n it is well known that λ₁ ≥ d, and we show that . For d = c it is no longer true that , but we show that by removing a small number of vertices of highest degree in G, one gets a graph G′ for which . Our proofs are based on the techniques of Friedman Kahn and Szemeredi from STOC 1989, who proved similar results for regular graphs. Our results are useful for extending the analysis of certain heuristics to sparser instances of NP‐hard problems. We illustrate this by removing some unnecessary logarithmic factors in the density of k‐SAT formulas that are refuted by the algorithm of Goerdt and Krivelevich from STACS 2001. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2005     

Large induced trees in sparse random graphs

We consider the size of the largest induced tree in random graphs, random regular graphs and random regular digraphs where the average degree is constant. In all cases we show that with probability 1 − o(1), such graphs have induced trees of size order n. In particular, the first result confirms a conjecture of Erdos and Palka (Discrete Math. 46 (1983), 145–150).     

Some large deviation results for sparse random graphs

Summary. We obtain a large deviation principle (LDP) for the relative size of the largest connected component in a random graph with small edge probability. The rate function, which is not convex in general, is determined explicitly using a new technique. The proof yields an asymptotic formula for the probability that the random graph is connected. We also present an LDP and related result for the number of isolated vertices. Here we make use of a simple but apparently unknown characterisation, which is obtained by embedding the random graph in a random directed graph. The results demonstrate that, at this scaling, the properties `connected' and `contains no isolated vertices' are not asymptotically equivalent. (At the threshold probability they are asymptotically equivalent.) Received: 14 November 1996 / In revised form: 15 August 1997     

Dynamic choosability of triangle‐free graphs and sparse random graphs

Ther‐dynamic choosability of a graph G, written , is the least k such that whenever each vertex is assigned a list of at least k colors a proper coloring can be chosen from the lists so that every vertex v has at least neighbors of distinct colors. Let ch(G) denote the choice number of G. In this article, we prove when is bounded. We also show that there exists a constant C such that the random graph with almost surely satisfies . Also if G is a triangle‐free regular graph, then we have .     

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     

Topology discovery of sparse random graphs with few participants

We consider the task of topology discovery of sparse random graphs using end‐to‐end random measurements (e.g., delay) between a subset of nodes, referred to as the participants. The rest of the nodes are hidden, and do not provide any information for topology discovery. We consider topology discovery under two routing models: (a) the participants exchange messages along the shortest paths and obtain end‐to‐end measurements, and (b) additionally, the participants exchange messages along the second shortest path. For scenario (a), our proposed algorithm results in a sub‐linear edit‐distance guarantee using a sub‐linear number of uniformly selected participants. For scenario (b), we obtain a much stronger result, and show that we can achieve consistent reconstruction when a sub‐linear number of uniformly selected nodes participate. This implies that accurate discovery of sparse random graphs is tractable using an extremely small number of participants. We finally obtain a lower bound on the number of participants required by any algorithm to reconstruct the original random graph up to a given edit distance. We also demonstrate that while consistent discovery is tractable for sparse random graphs using a small number of participants, in general, there are graphs which cannot be discovered by any algorithm even with a significant number of participants, and with the availability of end‐to‐end information along all the paths between the participants. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2013     

Adaptable choosability of planar graphs with sparse short cycles

Given a (possibly improper) edge colouring F of a graph G, a vertex colouring of G is adapted toF if no colour appears at the same time on an edge and on its two endpoints. A graph G is called (for some positive integer k) if for any list assignment L to the vertices of G, with |L(v)|≥k for all v, and any edge colouring F of G, G admits a colouring c adapted to F where c(v)∈L(v) for all v. This paper proves that a planar graph G is adaptably 3-choosable if any two triangles in G have distance at least 2 and no triangle is adjacent to a 4-cycle.     

Turán's theorem in sparse random graphs

We prove the analogue of Turán's Theorem in random graphs with edge probability p(n) ? n^?1/(k?1.5). With probability 1 ? o(1), one needs to delete approximately ‐fraction of the edges in a random graph in order to destroy all cliques of size k. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 23: 225–234, 2003