scholarly journals A completion of the proof of the Edge-statistics Conjecture

2004 ◽  
Author(s):  
Lisa Sauerman ◽  
Jacob Fox
Keyword(s):  
Asymptotic Behavior ◽  
Complete Graph ◽  
Extremal Combinatorics ◽  
Single Edge ◽  
Expected Number ◽  
Induced Subgraphs ◽  
Large Graphs ◽  
The Family ◽  
Vertex Graph ◽  
Discrete Structures

Extremal combinatorics often deals with problems of maximizing a specific quantity related to substructures in large discrete structures. The first question of this kind that comes to one's mind is perhaps determining the maximum possible number of induced subgraphs isomorphic to a fixed graph $H$ in an $n$-vertex graph. The asymptotic behavior of this number is captured by the limit of the ratio of the maximum number of induced subgraphs isomorphic to $H$ and the number of all subgraphs with the same number vertices as $H$; this quantity is known as the _inducibility_ of $H$. More generally, one can define the inducibility of a family of graphs in the analogous way. Among all graphs with $k$ vertices, the only two graphs with inducibility equal to one are the empty graph and the complete graph. However, how large can the inducibility of other graphs with $k$ vertices be? Fix $k$, consider a graph with $n$ vertices join each pair of vertices independently by an edge with probability $\binom{k}{2}^{-1}$. The expected number of $k$-vertex induced subgraphs with exactly one edge is $e^{-1}+o(1)$. So, the inducibility of large graphs with a single edge is at least $e^{-1}+o(1)$. This article establishes that this bound is the best possible in the following stronger form, which proves a conjecture of Alon, Hefetz, Krivelevich and Tyomkyn: the inducibility of the family of $k$-vertex graphs with exactly $l$ edges where $0<l<\binom{k}{2}$ is at most $e^{-1}+o(1)$. The example above shows that this is tight for $l=1$ and it can be also shown to be tight for $l=k-1$. The conjecture was known to be true in the regime where $l$ is superlinearly bounded away from $0$ and $\binom{k}{2}$, for which the sum of the inducibilities goes to zero, and also in the regime where $l$ is bounded away from $0$ and $\binom{k}{2}$ by a sufficiently large linear function. The article resolves the hardest cases where $l$ is linearly close to $0$ or close to $\binom{k}{2}$, and provides generalizations to hypergraphs.

Tiered Sampling

2021 ◽  
Vol 15 (5) ◽  
pp. 1-52
Author(s):  
Lorenzo De Stefani ◽  
Erisa Terolli ◽  
Eli Upfal
Keyword(s):  
Large Scale ◽  
Analysis Of Algorithms ◽  
Base Layer ◽  
Single Edge ◽  
Real World Data ◽  
High Quality ◽  
Large Graphs ◽  
Massive Graphs ◽  
Variance Estimate ◽  
Low Probability

We introduce Tiered Sampling , a novel technique for estimating the count of sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size M , which can be magnitudes smaller than the number of edges. Our methods address the challenging task of counting sparse motifs—sub-graph patterns—that have a low probability of appearing in a sample of M edges in the graph, which is the maximum amount of data available to the algorithms in each step. To obtain an unbiased and low variance estimate of the count, we partition the available memory into tiers (layers) of reservoir samples. While the base layer is a standard reservoir sample of edges, other layers are reservoir samples of sub-structures of the desired motif. By storing more frequent sub-structures of the motif, we increase the probability of detecting an occurrence of the sparse motif we are counting, thus decreasing the variance and error of the estimate. While we focus on the designing and analysis of algorithms for counting 4-cliques, we present a method which allows generalizing Tiered Sampling to obtain high-quality estimates for the number of occurrence of any sub-graph of interest, while reducing the analysis effort due to specific properties of the pattern of interest. We present a complete analytical analysis and extensive experimental evaluation of our proposed method using both synthetic and real-world data. Our results demonstrate the advantage of our method in obtaining high-quality approximations for the number of 4 and 5-cliques for large graphs using a very limited amount of memory, significantly outperforming the single edge sample approach for counting sparse motifs in large scale graphs.

scholarly journals An Ordered Turán Problem for Bipartite Graphs

10.37236/2471 ◽  
2012 ◽  
Vol 19 (4) ◽  
Author(s):  
Craig Timmons
Keyword(s):  
Complete Bipartite Graph ◽  
Bipartite Graphs ◽  
Free Graph ◽  
The Family ◽  
Turan Problem ◽  
Vertex Graph ◽  
Turán Number ◽  
Turán Problem ◽  
Natural Way

Let $F$ be a graph.  A graph $G$ is $F$-free if it does not contain $F$ as a subgraph.  The Turán number of $F$, written $\textrm{ex}(n,F)$, is the maximum number of edges in an $F$-free graph with $n$ vertices.  The determination of Turán numbers of bipartite graphs is a challenging and widely investigated problem.  In this paper we introduce an ordered version of the Turán problem for bipartite graphs.  Let $G$ be a graph with $V(G) = \{1, 2, \dots , n \}$ and view the vertices of $G$ as being ordered in the natural way.  A zig-zag $K_{s,t}$, denoted $Z_{s,t}$, is a complete bipartite graph $K_{s,t}$ whose parts $A = \{n_1 < n_2 < \dots < n_s \}$ and $B = \{m_1 < m_2 < \dots < m_t \}$ satisfy the condition $n_s < m_1$.  A zig-zag $C_{2k}$ is an even cycle $C_{2k}$ whose vertices in one part precede all of those in the other part.  Write $\mathcal{Z}_{2k}$ for the family of zig-zag $2k$-cycles.  We investigate the Turán numbers $\textrm{ex}(n,Z_{s,t})$ and $\textrm{ex}(n,\mathcal{Z}_{2k})$.  In particular we show $\textrm{ex}(n, Z_{2,2}) \leq \frac{2}{3}n^{3/2} + O(n^{5/4})$.  For infinitely many $n$ we construct a $Z_{2,2}$-free $n$-vertex graph with more than $(n - \sqrt{n} - 1) + \textrm{ex} (n,K_{2,2})$ edges.

scholarly journals Lower Bounds for the Size of Random Maximal $H$-Free Graphs

10.37236/93 ◽  
2009 ◽  
Vol 16 (1) ◽  
Author(s):  
Guy Wolfovitz
Keyword(s):  
Lower Bound ◽  
Random Process ◽  
Lower Bounds ◽  
Random Permutation ◽  
Bipartite Graphs ◽  
Expected Number ◽  
Free Graph ◽  
Vertex Graph

We consider the next random process for generating a maximal $H$-free graph: Given a fixed graph $H$ and an integer $n$, start by taking a uniformly random permutation of the edges of the complete $n$-vertex graph $K_n$. Then, traverse the edges of $K_n$ according to the order imposed by the permutation and add each traversed edge to an (initially empty) evolving $n$-vertex graph - unless its addition creates a copy of $H$. The result of this process is a maximal $H$-free graph ${\Bbb M}_n(H)$. Our main result is a new lower bound on the expected number of edges in ${\Bbb M}_n(H)$, for $H$ that is regular, strictly $2$-balanced. As a corollary, we obtain new lower bounds for Turán numbers of complete, balanced bipartite graphs. Namely, for fixed $r \ge 5$, we show that ex$(n, K_{r,r}) = \Omega(n^{2-2/(r+1)}(\ln\ln n)^{1/(r^2-1)})$. This improves an old lower bound of Erdős and Spencer. Our result relies on giving a non-trivial lower bound on the probability that a given edge is included in ${\Bbb M}_n(H)$, conditioned on the event that the edge is traversed relatively (but not trivially) early during the process.

Transversals with Residue in Moderately Overlapping T(k)-Families of Translates

2009 ◽  
Vol 52 (3) ◽  
pp. 388-402
Author(s):  
Aladár Heppes
Keyword(s):  
Asymptotic Behavior ◽  
Compact Convex ◽  
Line Transversal ◽  
Type Result ◽  
Empty Interior ◽  
Disjoint Family ◽  
Straight Line ◽  
The Family ◽  
Centrally Symmetric ◽  
Line Meeting

AbstractLet K denote an oval, a centrally symmetric compact convex domain with non-empty interior. A family of translates of K is said to have property T(k) if for every subset of at most k translates there exists a common line transversal intersecting all of them. The integer k is the stabbing level of the family. Two translates Ki = K + ci and Kj = K + cj are said to be σ-disjoint if σK + ci and σK + cj are disjoint. A recent Helly-type result claims that for every σ > 0 there exists an integer k(σ) such that if a family of σ-disjoint unit diameter discs has property T(k)|k ≥ k(σ), then there exists a straight line meeting all members of the family. In the first part of the paper we give the extension of this theorem to translates of an oval K. The asymptotic behavior of k(σ) for σ → 0 is considered as well.Katchalski and Lewis proved the existence of a constant r such that for every pairwise disjoint family of translates of an oval K with property T(3) a straight line can be found meeting all but at most r members of the family. In the second part of the paper σ-disjoint families of translates of K are considered and the relation of σ and the residue r is investigated. The asymptotic behavior of r(σ) for σ → 0 is also discussed.

Neurofibromatosis and Malignant Childhood Cancers: A Survey in Italy, 1970–83

1987 ◽  
Vol 73 (3) ◽  
pp. 209-212 ◽  
Author(s):  
Maria Luisa Mosso ◽  
Manuel Castello ◽  
Franca Fossati Bellani ◽  
Maria Teresa Di Tullio ◽  
Franco Loiacono ◽  
...  
Keyword(s):  
Family History ◽  
General Population ◽  
Wilms Tumor ◽  
Soft Tissue Sarcomas ◽  
Childhood Cancers ◽  
Expected Number ◽  
Number Of Children ◽  
The Family ◽  
Neural Crest Origin ◽  
Tumor Types

Neural tumors, Wilms’ tumor, rhabdomyosarcoma and several types of leukemia have been previously described in association with neurofibromatosis (NF). In a nation-wide collection of cases in Italy, 15 children (0–14 years of age) with NF and cancer or leukemia were identified; 13 of them had been diagnosed with cancer between 1976–83. The expected number of children with cancer and NF in 1976–83 was 4.48. The distribution of tumor types was different from that found in the general population, with a higher proportion of tumors of neural crest origin as well as soft tissue sarcomas. In 7/15 the family history was positive for NF; in 5/7 the individuals affected included the mother and/or a maternal relative.

Waiting times for multiple occurrences of several events

1988 ◽  
Vol 25 (03) ◽  
pp. 624-629
Author(s):  
Stephen Scheinberg
Keyword(s):  
Asymptotic Behavior ◽  
Finite Number ◽  
Waiting Times ◽  
Expected Number

Consider an ‘experiment' which can be repeated indefinitely often resulting in independent random outcomes. Fix attention on a finite number of possible (sets of) outcomes E 1, E 2, … and define W = W(N 1, N 2, …) to be the expected number of repetitions needed to ensure that E 1 has occurred (at least) N 1 times, E 2 has occurred (at least) N 2 times, etc. This article examines the asymptotic behavior of W as a function of the sum Σ j N j, as the latter grows without bound.

Analysis of the Luria–Delbrück distribution using discrete convolution powers

1992 ◽  
Vol 29 (02) ◽  
pp. 255-267 ◽  
Author(s):  
W. T. Ma ◽  
G. vH. Sandri ◽  
S. Sarkar
Keyword(s):  
Population Genetics ◽  
Asymptotic Behavior ◽  
Computational Efficiency ◽  
Recursion Relation ◽  
Expected Number ◽  
Discrete Convolution ◽  
Convolution Powers ◽  
Central Result

The Luria–Delbrück distribution arises in birth-and-mutation processes in population genetics that have been systematically studied for the last fifty years. The central result reported in this paper is a new recursion relation for computing this distribution which supersedes all past results in simplicity and computational efficiency: p 0 = e–m ; where m is the expected number of mutations. A new relation for the asymptotic behavior of pn (≈ c/n 2) is also derived. This corresponds to the probability of finding a very large number of mutants. A formula for the z-transform of the distribution is also reported.

Asymptotic behavior of a generalization of Bailey's simple epidemic

1971 ◽  
Vol 3 (02) ◽  
pp. 220-221
Author(s):  
George H. Weiss ◽  
Menachem Dishon
Keyword(s):  
Asymptotic Behavior ◽  
Differential Equations ◽  
Rate Constants ◽  
Deterministic Model ◽  
Stochastic Theory ◽  
Expected Number ◽  
Deterministic Theory ◽  
Mean Values ◽  
Image Position ◽  
Fixed Population

It has been shown that for many epidemic models, the stochastic theory leads to essentially the same results as the deterministic theory provided that one identifies mean values with the functions calculated from the deterministic differential equations (cf. [1]). If one considers a generalization of Bailey's simple epidemic for a fixed population of size N, represented schematically by where I refers to an infected, S refers to a susceptible, and α and β are appropriate rate constants, then it is evident that at time t = ∞, the expected number of infected individuals must be zero provided that β &gt; 0. If x(t) denotes the number of infected at time t, then the deterministic model is summarized by

scholarly journals Smaller Extended Formulations for Spanning Tree Polytopes in Minor-closed Classes and Beyond

2021 ◽  
Vol 28 (4) ◽  
Author(s):  
Manuel Aprile ◽  
Samuel Fiorini ◽  
Tony Huynh ◽  
Gwenaël Joret ◽  
David R. Wood
Keyword(s):  
Spanning Tree ◽  
Short Proof ◽  
Induced Subgraphs ◽  
Direct Construction ◽  
Extension Complexity ◽  
Graph Classes ◽  
Closed Class ◽  
Vertex Graph ◽  
Graph Class ◽  
Strongly Sublinear

Let $G$ be a connected $n$-vertex graph in a proper minor-closed class $\mathcal G$. We prove that the extension complexity of the spanning tree polytope of $G$ is $O(n^{3/2})$. This improves on the $O(n^2)$ bounds following from the work of Wong (1980) and Martin (1991). It also extends a result of Fiorini, Huynh, Joret, and Pashkovich (2017), who obtained a $O(n^{3/2})$ bound for graphs embedded in a fixed surface. Our proof works more generally for all graph classes admitting strongly sublinear balanced separators: We prove that for every constant $\beta$ with $0<\beta<1$, if $\mathcal G$ is a graph class closed under induced subgraphs such that all $n$-vertex graphs in $\mathcal G$ have balanced separators of size $O(n^\beta)$, then the extension complexity of the spanning tree polytope of every connected $n$-vertex graph in $\mathcal{G}$ is $O(n^{1+\beta})$. We in fact give two proofs of this result, one is a direct construction of the extended formulation, the other is via communication protocols. Using the latter approach we also give a short proof of the $O(n)$ bound for planar graphs due to Williams (2002).

scholarly journals Quasirandomness in Hypergraphs

10.37236/7537 ◽  
2018 ◽  
Vol 25 (3) ◽  
Author(s):  
Elad Aigner-Horev ◽  
David Conlon ◽  
Hiệp Hàn ◽  
Yury Person ◽  
Mathias Schacht
Keyword(s):  
Random Graph ◽  
Edge Density ◽  
Analytic Framework ◽  
Graph Properties ◽  
Vertex Graph ◽  
Discrete Structures

An $n$-vertex graph $G$ of edge density $p$ is considered to be quasirandom if it shares several important properties with the random graph $G(n,p)$. 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.

Sign in / Sign up

Export Citation Format

Share Document