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2017, Electronic Notes in Discrete Mathematics
An n-vertex graph G of edge density p is considered to be quasirandom if it shares several important properties with the random graph Gpn, pq. A well-known theorem of Chung, Graham and Wilson states that many such 'typical' properties are asymptotically equivalent and, thus, a graph G possessing one such property automatically satisfies the others. In recent years, work in this area has focused on uncovering more quasirandom graph properties and on extending the known results to other discrete structures. In the context of hypergraphs, however, one may consider several different notions of quasirandomness. A complete description of these notions has been provided recently by Towsner, who proved several central equivalences using an analytic framework. We give short and purely combinatorial proofs of the main equivalences in Towsner's result.
Random Structures & Algorithms, 2011
We study quasi‐random properties of k‐uniform hypergraphs. Our central notion is uniform edge distribution with respect to large vertex sets. We will find several equivalent characterisations of this property and our work can be viewed as an extension of the well known Chung‐Graham‐Wilson theorem for quasi‐random graphs.Moreover, let Kk be the complete graph on k vertices and M(k) the line graph of the graph of the k‐dimensional hypercube. We will show that the pair of graphs (Kk,M(k)) has the property that if the number of copies of both Kk and M(k) in another graph G are as expected in the random graph of density d, then G is quasi‐random (in the sense of the Chung‐Graham‐Wilson theorem) with density close to d. © 2011 Wiley Periodicals, Inc. Random Struct. Alg., 2011
Journal of Combinatorial Theory, Series A, 2002
Haviland and Thomason and Chung and Graham were the first to investigate systematically some properties of quasi-random hypergraphs. In particular, in a series of articles, Chung and Graham considered several quite disparate properties of random-like hypergraphs of density 1/2 and proved that they are in fact equivalent. The central concept in their work turned out to be the so called deviation of a hypergraph. They proved that having small deviation is equivalent to a variety of other properties that describe quasi-randomness. In this paper, we consider the concept of discrepancy for k-uniform hypergraphs with an arbitrary constant density d (0 < d < 1) and prove that the condition of having asymptotically vanishing discrepancy is equivalent to several other quasi-random properties of H, similar to the ones introduced by Chung and Graham. In particular, we prove that the correct 'spectrum' of the s-vertex subhypergraphs is equivalent to quasi-randomness for any s ≥ 2k. Our work may be viewed as a continuation of the work of Chung and Graham, although our proof techniques are different in certain important parts.
2014
This is an extended version of the thesis presented to the Programa de Pós-Graduação em Matemática of the Departamento de Matemática, PUC-Rio, in September 2013, incorporating some suggestions from the examining commission. Random graphs (and more generally hypergraphs) have been extensively studied, including their first order logic. In this work we focus on certain specific aspects of this vast theory. We consider the binomial model G^d+1(n,p) of the random (d+1)-uniform hypergraph on n vertices, where each edge is present, independently of one another, with probability p=p(n). We are particularly interested in the range p(n) ∼ C(n)/n^d, after the double jump and near connectivity. We prove several zero-one, and, more generally, convergence results and obtain combinatorial applications of some
The Annals of Applied Probability, 2005
The theme of this paper is the derivation of analytic formulae for certain large combinatorial structures. The formulae are obtained via fluid limits of pure jump-type Markov processes, established under simple conditions on the Laplace transforms of their Lévy kernels. Furthermore, a related Gaussian approximation allows us to describe the randomness which may persist in the limit when certain parameters take critical values. Our method is quite general, but is applied here to vertex identifiability in random hypergraphs. A vertex v is identifiable in n steps if there is a hyperedge containing v all of whose other vertices are identifiable in fewer steps. We say that a hyperedge is identifiable if every one of its vertices is identifiable. Our analytic formulae describe the asymptotics of the number of identifiable vertices and the number of identifiable hyperedges for a Poisson(β) random hypergraph Λ on a set V of N vertices, in the limit as N → ∞. Here β is a formal power series with nonnegative coefficients β0, β1, . . . , and (Λ(A)) A⊆V are independent Poisson random variables such that Λ(A), the number of hyperedges on A, has mean N βj / N j whenever |A| = j.
Random Structures and Algorithms, 2002
Szemerédi's Regularity Lemma is a well-known and powerful tool in modern graph theory. This result led to a number of interesting applications, particularly in extremal graph theory. A regularity lemma for 3-uniform hypergraphs developed by Frankl and Rödl [8] allows some of the Szemerédi Regularity Lemma graph applications to be extended to hypergraphs. An important development regarding Szemerédi's Lemma showed the equivalence between the property of ⑀-regularity of a bipartite graph G and an easily verifiable property concerning the neighborhoods of its vertices (Alon et al. [1]; cf. [6]). This characterization of ⑀-regularity led to an algorithmic version of Szemerédi's lemma [1]. Similar problems were also considered for hypergraphs. In [2], [9], [13], and [18], various descriptions of quasi-randomness of k-uniform hypergraphs were given. As in [1], the goal of this paper is to find easily verifiable conditions for the hypergraph regularity provided by [8]. The hypergraph regularity of [8] renders quasi-random "blocks of hyperedges" which are very sparse. This situation leads to technical difficulties in its application. Moreover, as we show in this paper, some easily verifiable conditions analogous to those considered in [2] and [18] fail to be true in the setting of [8]. However, we are able to find some necessary and sufficient
Random Structures & Algorithms, 2021
We investigate the emergence of subgraphs in sparse pseudo‐random k‐uniform hypergraphs, using the following comparatively weak notion of pseudo‐randomness. A k‐uniform hypergraph H on n vertices is called ‐pseudo‐random if for all (not necessarily disjoint) vertex subsets with we have urn:x-wiley:rsa:media:rsa21052:rsa21052-math-0004For any linear k‐uniform F, we provide a bound on in terms of and F, such that (under natural divisibility assumptions on n) any k‐uniform ‐pseudo‐random n‐vertex hypergraph H with a mild minimum vertex degree condition contains an F‐factor. The approach also enables us to establish the existence of loose Hamilton cycles in sufficiently pseudo‐random hypergraphs and, along the way, we also derive conditions which guarantee the appearance of any fixed sized subgraph. All results imply corresponding bounds for stronger notions of hypergraph pseudo‐randomness such as jumbledness or large spectral gap. As a consequence, ‐pseudo‐random k‐graphs as above cont...
The Electronic Journal of Combinatorics, 2015
We show how to adjust a very nice coupling argument due to McDiarmid in order to prove/reprove in a novel way results concerning Hamilton cycles in various models of random graph and hypergraphs. In particular, we firstly show that for $k\geq 3$, if $pn^{k-1}/\log n$ tends to infinity, then a random $k$-uniform hypergraph on $n$ vertices, with edge probability $p$, with high probability (w.h.p.) contains a loose Hamilton cycle, provided that $(k-1)|n$. This generalizes results of Frieze, Dudek and Frieze, and reproves a result of Dudek, Frieze, Loh and Speiss. Secondly, we show that there exists $K>0$ such for every $p\geq (K\log n)/n$ the following holds: Let $G_{n,p}$ be a random graph on $n$ vertices with edge probability $p$, and suppose that its edges are being colored with $n$ colors uniformly at random. Then, w.h.p. the resulting graph contains a Hamilton cycle with for which all the colors appear (a rainbow Hamilton cycle). Bal and Frieze proved the latter statement for g...
Combinatorics, Probability and Computing, 2017
We investigate the asymptotic version of the Erdős–Ko–Rado theorem for the random k-uniform hypergraph $\mathcal{H}$ k (n, p). For 2⩽k(n) ⩽ n/2, let $N=\binom{n}k$ and $D=\binom{n-k}k$ . We show that with probability tending to 1 as n → ∞, the largest intersecting subhypergraph of $\mathcal{H}$ has size $$(1+o(1))p\ffrac kn N$$ for any $$p\gg \ffrac nk\ln^2\biggl(\ffrac nk\biggr)D^{-1}.$$ This lower bound on p is asymptotically best possible for k = Θ(n). For this range of k and p, we are able to show stability as well. A different behaviour occurs when k = o(n). In this case, the lower bound on p is almost optimal. Further, for the small interval D −1 ≪ p ⩽ (n/k)1−ϵ D −1, the largest intersecting subhypergraph of $\mathcal{H}$ k (n, p) has size Θ(ln(pD)ND −1), provided that $k \gg \sqrt{n \ln n}$ . Together with previous work of Balogh, Bohman and Mubayi, these results settle the asymptotic size of the largest intersecting family in $\mathcal{H}$ k , for essentially all values of p...
Physical Review E, 2009
In the last few years we have witnessed the emergence, primarily in on-line communities, of new types of social networks that require for their representation more complex graph structures than have been employed in the past. One example is the folksonomy, a tripartite structure of users, resources, and tags -- labels collaboratively applied by the users to the resources in order to impart meaningful structure on an otherwise undifferentiated database. Here we propose a mathematical model of such tripartite structures which represents them as random hypergraphs. We show that it is possible to calculate many properties of this model exactly in the limit of large network size and we compare the results against observations of a real folksonomy, that of the on-line photography web site Flickr. We show that in some cases the model matches the properties of the observed network well, while in others there are significant differences, which we find to be attributable to the practice of multiple tagging, i.e., the application by a single user of many tags to one resource, or one tag to many resources.
European Journal of Combinatorics
A well-known theorem of Erdős and Gallai [1] asserts that a graph with no path of length k contains at most 1 2 (k−1)n edges. Recently Győri, Katona and Lemons [2] gave an extension of this result to hypergraphs by determining the maximum number of hyperedges in an r-uniform hypergraph containing no Berge path of length k for all values of r and k except for k = r + 1. We settle the remaining case by proving that an r-uniform hypergraph with more than n edges must contain a Berge path of length r + 1. Given a hypergraph H, we denote the vertex and edge sets of H by V (H) and E(H) respectively. Moreover, let e(H) = |E(H)| and n(H) = |V (H)|. A Berge path of length k is a collection of k distinct hyperedges e 1 ,. .. , e k and k + 1 distinct vertices v 1 ,. .. , v k+1 such that for each 1 ≤ i ≤ k, we have v i , v i+1 ∈ e i. A Berge cycle of length k is a collection of k distinct hyperedges e 1 ,. .. , e k and k distinct vertices v 1 ,. .. , v k such that for each 1 ≤ i ≤ k − 1, we have v i , v i+1 ∈ e i and v k , v 1 ∈ e k. The vertices v i and edges e i in the preceding definitions are called the vertices and edges of their respective Berge path (cycle). The Berge path is said to start at the vertex v 1. We also say that the edges e 1 ,. .. , e k of the Berge path (cycle) span the set ∪ k i=1 e i. A hypergraph is called r-uniform, if all of its hyperedges have size r. Győri, Katona and Lemons determined the largest number of hyperedges possible in an r-uniform hypergraph without a Berge path of length k for both the range k > r + 1 and the range k ≤ r.
Hypergraphs, the generalization of graphs in which edges become conglomerates of r nodes called hyperedges of rank r ≥ 2, are excellent models to study systems with interactions that are beyond the pairwise level. For hypergraphs, the node degree ℓ (number of hyperedges connected to a node) and the number of neighbors k of a node differ from each other in contrast to the case of graphs, where counting the number of edges is equivalent to counting the number of neighbors. In this article, I calculate the distribution of the number of node neighbors in random hypergraphs in which hyperedges of uniform rank r have a homogeneous (equal for all hyperedges) probability p to appear. This distribution is equivalent to the degree distribution of ensembles of graphs created as projections of hypergraph or bipartite network ensembles, where the projection connects any two nodes in the projected graph when they are also connected in the hypergraph or bipartite network. The calculation is non-trivial due to the possibility that neighbor nodes belong simultaneously to multiple hyperedges (node overlaps). From the exact results, the traditional asymptotic approximation to the distribution in the sparse regime (small p) where overlaps are ignored is rederived and improved; the approximation exhibits Poisson-like behavior accompanied by strong fluctuations modulated by power-law decays in the system size N with decay exponents equal to the minimum number of overlapping nodes possible for a given number of neighbors. It is shown that the dense limit cannot be explained if overlaps are ignored, and the correct asymptotic distribution is provided. The neighbor distribution requires the calculation of a new combinatorial coefficient Q r−1 (k, ℓ), which counts the number of distinct labelled hypergraphs of k nodes, ℓ hyperedges of rank r − 1, and where every node is connected to at least one hyperedge. Some identities of Q r−1 (k, ℓ) are derived and applied to the verification of normalization and the calculation of moments of the neighbor distribution.
The Electronic Journal of Combinatorics
Let $c$ be a positive constant. We show that if $r=\lfloor{cn^{1/3}}\rfloor$ and the members of ${[n]\choose r}$ are chosen sequentially at random to form an intersecting hypergraph then with limiting probability $(1+c^3)^{-1}$, as $n\to\infty$, the resulting family will be of maximum size ${n-1\choose r-1}$.
SIAM Journal on Discrete Mathematics, 2016
A hypergraph is k-irregular if there is no set of k vertices all of which have the same degree. We asymptotically determine the probability that a random uniform hypergraph is k-irregular.
European Journal of Combinatorics, 1984
Let F(n) denote the maximum number of distinct subsets of an n-element set such that there are no four distinct subsets: A, B, C, D with A v B = C v D. We prove that 2<n-Ios 3 ll 3 -2.;:; F( n).;:; 2< 3 n+Z)/ 4 • We use probability theory for the proof of both the lower and upper bounds. Some related problems are considered, too.
SIAM Journal on Computing, 2010
We deal with two intimately related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to measure how much a given graph "resembles" a random one. Moreover, a regular partition approximates a given graph by a bounded number of quasi-random graphs. Regarding quasirandomness, we present a new spectral characterization of low discrepancy, which extends to sparse graphs. Concerning regular partitions, we introduce a concept of regularity that takes into account vertex weights, and show that if G = (V, E) satisfies a certain boundedness condition, then G admits a regular partition. In addition, building on the work of Alon and Naor [4], we provide an algorithm that computes a regular partition of a given (possibly sparse) graph G in polynomial time. As an application, we present a polynomial time approximation scheme for MAX CUT on (sparse) graphs without "dense spots".
2010
We also give an absolute lower bound $\cp(n,r) \geq {n \choose r}/{q + r - 1 \choose r}$ when $n = q^2 + q + r - 1$, and for each $r$ characterize the finitely many configurations achieving equality with the lower bound. Finally we note the connection of $\cp(n,r)$ to extremal graph theory, and determine some new asymptotically sharp bounds for the Zarankiewicz problem.
SIAM Journal on Discrete Mathematics, 2013
We prove that in a random 3-uniform or 4-uniform hypergraph of order n the probability that some two vertices have the same degree tends to one as n → ∞.
The Electronic Journal of Combinatorics, 2012
We determine the probability thresholds for the existence of monotone paths, of finite and infinite length, in random oriented graphs with vertex set $\mathbb N^{[k]}$, the set of all increasing $k$-tuples in $\mathbb N$. These graphs appear as line graph of uniform hypergraphs with vertex set $\mathbb N$.
A weighting of the edges of a hypergraph is called vertex-coloring if the weighted degrees of the vertices yield a proper coloring of the graph, i.e., every edge contains at least two vertices with different weighted degrees. In this paper we show that such a weighting is possible from the weight set {1, 2, . . . , r + 1} for all linear hypergraphs with maximum edge size r ≥ 4 and not containing isolated edges. The number r + 1 is best possible for this statement.
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