scholarly journals Client-Waiter Games on Complete and Random Graphs

10.37236/6039 ◽  
2016 ◽  
Vol 23 (4) ◽  
Author(s):  
Oren Dean ◽  
Michael Krivelevich
Keyword(s):  
Positive Integer ◽  
Random Graph ◽  
Random Graphs ◽  
Complete Graph ◽  
Upper Bounds ◽  
Connected Component ◽  
Lower And Upper Bounds ◽  
Large Connected Component ◽  
Graph Property ◽  
Player Game

For a graph $ G $, a monotone increasing graph property $ \mathcal{P} $ and positive integer $ q $, we define the Client-Waiter game to be a two-player game which runs as follows. In each turn Waiter is offering Client a subset of at least one and at most $ q+1 $ unclaimed edges of $ G $ from which Client claims one, and the rest are claimed by Waiter. The game ends when all the edges have been claimed. If Client's graph has property $ \mathcal{P} $ by the end of the game, then he wins the game, otherwise Waiter is the winner. In this paper we study several Client-Waiter games on the edge set of the complete graph, and the $ H $-game on the edge set of the random graph. For the complete graph we consider games where Client tries to build a large star, a long path and a large connected component. We obtain lower and upper bounds on the critical bias for these games and compare them with the corresponding Waiter-Client games and with the probabilistic intuition. For the $ H $-game on the random graph we show that the known results for the corresponding Maker-Breaker game are essentially the same for the Client-Waiter game, and we extend those results for the biased games and for trees.

scholarly journals On Resilience of Connectivity in the Evolution of Random Graphs

10.37236/7885 ◽  
2019 ◽  
Vol 26 (2) ◽  
Author(s):  
Luc Haller ◽  
Miloš Trujić
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Hitting Time ◽  
Connected Component ◽  
Empty Graph ◽  
Spanning Subgraph ◽  
Time Result ◽  
Graph Property

In this note we establish a resilience version of the classical hitting time result of Bollobás and Thomason regarding connectivity. A graph $G$ is said to be $\alpha$-resilient with respect to a monotone increasing graph property $\mathcal{P}$ if for every spanning subgraph $H \subseteq G$ satisfying $\deg_H(v) \leqslant \alpha \deg_G(v)$ for all $v \in V(G)$, the graph $G - H$ still possesses $\mathcal{P}$. Let $\{G_i\}$ be the random graph process, that is a process where, starting with an empty graph on $n$ vertices $G_0$, in each step $i \geqslant 1$ an edge $e$ is chosen uniformly at random among the missing ones and added to the graph $G_{i - 1}$. We show that the random graph process is almost surely such that starting from $m \geqslant (\tfrac{1}{6} + o(1)) n \log n$, the largest connected component of $G_m$ is $(\tfrac{1}{2} - o(1))$-resilient with respect to connectivity. The result is optimal in the sense that the constants $1/6$ in the number of edges and $1/2$ in the resilience cannot be improved upon. We obtain similar results for $k$-connectivity.

Some remarks about extreme degrees in a random graph

1986 ◽  
Vol 100 (1) ◽  
pp. 167-174 ◽  
Author(s):  
Zbigniew Palka
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Complete Graph ◽  
Probability Distributions ◽  
Supplementary Information ◽  
Random Subgraph

Let Kn, p be a random subgraph of a complete graph Kn obtained by removing edges, each with the same probability q = 1 – p, independently of all other edges (i.e. each edge remains in Kn, p with probability p). Very detailed results devoted to probability distributions of the number of vertices of a given degree, as well as of the extreme degrees of Kn, p, have already been obtained by many authors (see e.g. [l]–[5], [7]–[9]). A similar subject for other models of random graphs has been investigated in [10]–[13], The aim of this note is to give some supplementary information about the distribution of the ith smallest (i ≥ 1 is fixed) and the ith largest degree in a sparse random graph Kn, p, i.e. when p = p(n) = o(1).

The Largest Component in Subcritical Inhomogeneous Random Graphs

2010 ◽  
Vol 20 (1) ◽  
pp. 131-154 ◽  
Author(s):  
TATYANA S. TUROVA
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Graph Model ◽  
Exact Formula ◽  
Connected Component ◽  
Subcritical Case ◽  
Random Graph Model ◽  
Asymptotic Size ◽  
Inhomogeneous Random Graphs ◽  
Inhomogeneous Random Graph

We study the ‘rank 1 case’ of the inhomogeneous random graph model. In the subcritical case we derive an exact formula for the asymptotic size of the largest connected component scaled to log n. This result complements the corresponding known result in the supercritical case. We provide some examples of applications of the derived formula.

scholarly journals Upper bounds on the non-3-colourability threshold of random graphs

2002 ◽  
Vol Vol. 5 ◽  
Author(s):  
Nikolaos Fountoulakis ◽  
Colin McDiarmid
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Upper Bounds ◽  
Average Degree ◽  
Expected Number ◽  
International Audience ◽  
Full Analysis ◽  
A Minor ◽  
Minor Improvement

International audience We present a full analysis of the expected number of 'rigid' 3-colourings of a sparse random graph. This shows that, if the average degree is at least 4.99, then as n → ∞ the expected number of such colourings tends to 0 and so the probability that the graph is 3-colourable tends to 0. (This result is tight, in that with average degree 4.989 the expected number tends to ∞.) This bound appears independently in Kaporis \textitet al. [Kap]. We then give a minor improvement, showing that the probability that the graph is 3-colourable tends to 0 if the average degree is at least 4.989.

scholarly journals Satisfiability and Computing van der Waerden Numbers

10.37236/1794 ◽  
2004 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael R. Dransfield ◽  
Lengning Liu ◽  
Victor W. Marek ◽  
Mirosław Truszczyński
Keyword(s):  
Positive Integer ◽  
Local Search ◽  
Ramsey Theory ◽  
Upper Bounds ◽  
General Purpose ◽  
Propositional Satisfiability ◽  
Lower And Upper Bounds ◽  
Algebraic Form ◽  
Sat Solvers ◽  
Structural Simplicity

In this paper we bring together the areas of combinatorics and propositional satisfiability. Many combinatorial theorems establish, often constructively, the existence of positive integer functions, without actually providing their closed algebraic form or tight lower and upper bounds. The area of Ramsey theory is especially rich in such results. Using the problem of computing van der Waerden numbers as an example, we show that these problems can be represented by parameterized propositional theories in such a way that decisions concerning their satisfiability determine the numbers (function) in question. We show that by using general-purpose complete and local-search techniques for testing propositional satisfiability, this approach becomes effective — competitive with specialized approaches. By following it, we were able to obtain several new results pertaining to the problem of computing van der Waerden numbers. We also note that due to their properties, especially their structural simplicity and computational hardness, propositional theories that arise in this research can be of use in development, testing and benchmarking of SAT solvers.

scholarly journals On the Growth of Some Functions Related to z(n)

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 876 ◽  
Author(s):  
Pavel Trojovský
Keyword(s):  
Positive Integer ◽  
Arithmetic Function ◽  
Fibonacci Sequence ◽  
Upper Bounds ◽  
Integer Solution ◽  
Lower And Upper Bounds ◽  
Positive Integer Solution

The order of appearance z : Z > 0 → Z > 0 is an arithmetic function related to the Fibonacci sequence ( F n ) n . This function is defined as the smallest positive integer solution of the congruence F k ≡ 0 ( mod n ) . In this paper, we shall provide lower and upper bounds for the functions ∑ n ≤ x z ( n ) / n , ∑ p ≤ x z ( p ) and ∑ p r ≤ x z ( p r ) .

scholarly journals Manipulative Waiters with Probabilistic Intuition

2015 ◽  
Vol 25 (6) ◽  
pp. 823-849 ◽  
Author(s):  
MAŁGORZATA BEDNARSKA-BZDȨGA ◽  
DAN HEFETZ ◽  
MICHAEL KRIVELEVICH ◽  
TOMASZ ŁUCZAK
Keyword(s):  
Phase Transition ◽  
Random Graphs ◽  
Complete Graph ◽  
Absolute Constant ◽  
Perfect Information ◽  
Graph Theoretic ◽  
Graph Property ◽  
Positive Integers ◽  
Monotone Graph ◽  
Transition Type

For positive integersnandqand a monotone graph property$\mathcal{A}$, we consider the two-player, perfect information game WC(n,q,$\mathcal{A}$), which is defined as follows. The game proceeds in rounds. In each round, the first player, called Waiter, offers the second player, called Client,q+ 1 edges of the complete graphKnwhich have not been offered previously. Client then chooses one of these edges which he keeps and the remainingqedges go back to Waiter. If, at the end of the game, the graph which consists of the edges chosen by Client satisfies the property$\mathcal{A}$, then Waiter is declared the winner; otherwise Client wins the game. In this paper we study such games (also known as Picker–Chooser games) for a variety of natural graph-theoretic parameters, such as the size of a largest component or the length of a longest cycle. In particular, we describe a phase transition type phenomenon which occurs when the parameterqis close tonand is reminiscent of phase transition phenomena in random graphs. Namely, we prove that ifq⩾ (1 + ϵ)n, then Client can avoid components of ordercϵ−2lnnfor some absolute constantc> 0, whereas forq⩽ (1 − ϵ)n, Waiter can force a giant, linearly sized component in Client's graph. In the second part of the paper, we prove that Waiter can force Client's graph to be pancyclic for everyq⩽cn, wherec> 0 is an appropriate constant. Note that this behaviour is in stark contrast to the threshold for pancyclicity and Hamiltonicity of random graphs.

scholarly journals Maximizing the Size of the Giant

2012 ◽  
Vol 49 (4) ◽  
pp. 1156-1165 ◽  
Author(s):  
Tom Britton ◽  
Pieter Trapman
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Related Question ◽  
Configuration Model ◽  
Connected Component ◽  
The Social ◽  
Random Weight ◽  
The Mean ◽  
Positive Integers ◽  
Outbreak Size

Consider a random graph where the mean degree is given and fixed. In this paper we derive the maximal size of the largest connected component in the graph. We also study the related question of the largest possible outbreak size of an epidemic occurring ‘on’ the random graph (the graph describing the social structure in the community). More precisely, we look at two different classes of random graphs. First, the Poissonian random graph in which each node i is given an independent and identically distributed (i.i.d.) random weight Xi with E(Xi)=µ, and where there is an edge between i and j with probability 1-e-XiXj/(µ n), independently of other edges. The second model is the thinned configuration model in which the n vertices of the ground graph have i.i.d. ground degrees, distributed as D, with E(D) = µ. The graph of interest is obtained by deleting edges independently with probability 1-p. In both models the fraction of vertices in the largest connected component converges in probability to a constant 1-q, where q depends on X or D and p. We investigate for which distributions X and D with given µ and p, 1-q is maximized. We show that in the class of Poissonian random graphs, X should have all its mass at 0 and one other real, which can be explicitly determined. For the thinned configuration model, D should have all its mass at 0 and two subsequent positive integers.

RECTANGLE AND BOX VISIBILITY GRAPHS IN 3D

1999 ◽  
Vol 09 (01) ◽  
pp. 1-27 ◽  
Author(s):  
SÁNDOR R. FEKETE ◽  
HENK MEIJER
Keyword(s):  
Complete Graph ◽  
Dimensional Space ◽  
Upper Bounds ◽  
Lower And Upper Bounds ◽  
3 Dimensional ◽  
Visibility Graphs ◽  
Axis Parallel ◽  
Parallel Direction ◽  
Visibility Representations ◽  
Special Case

We discuss rectangle and box visibility representations of graphs in 3-dimensional space. In these representations, vertices are represented by axis-aligned disjoint rectangles or boxes. Two vertices are adjacent if and only if their corresponding boxes see each other along a small axis-parallel cylinder. We concentrate on lower and upper bounds for the size of the largest complete graph that can be represented. In particular, we examine these bounds under certain restrictions: What can be said if we may only use boxes of a limited number of shapes? Some of the results presented are as follows: • There is a representation of K8 by unit boxes. • There is no representation of K10 by unit boxes. • There is a representation of K56, using 6 different box shapes. • There is no representation of K184 by general boxes. A special case arises for rectangle visibility graphs, where no two boxes can see each other in the x- or y-directions, which means that the boxes have to see each other in z-parallel direction. This special case has been considered before; we give further results, dealing with the aspects arising from limits on the number of shapes.

Maximizing the Size of the Giant

2012 ◽  
Vol 49 (04) ◽  
pp. 1156-1165
Author(s):  
Tom Britton ◽  
Pieter Trapman
Keyword(s):  
Random Graph ◽  
Random Graphs ◽  
Related Question ◽  
Configuration Model ◽  
Connected Component ◽  
The Social ◽  
Random Weight ◽  
The Mean ◽  
Positive Integers ◽  
Outbreak Size

Consider a random graph where the mean degree is given and fixed. In this paper we derive the maximal size of the largest connected component in the graph. We also study the related question of the largest possible outbreak size of an epidemic occurring ‘on’ the random graph (the graph describing the social structure in the community). More precisely, we look at two different classes of random graphs. First, the Poissonian random graph in which each node i is given an independent and identically distributed (i.i.d.) random weight X i with E(X i )=µ, and where there is an edge between i and j with probability 1-e-X i X j /(µ n), independently of other edges. The second model is the thinned configuration model in which the n vertices of the ground graph have i.i.d. ground degrees, distributed as D, with E(D) = µ. The graph of interest is obtained by deleting edges independently with probability 1-p. In both models the fraction of vertices in the largest connected component converges in probability to a constant 1-q, where q depends on X or D and p. We investigate for which distributions X and D with given µ and p, 1-q is maximized. We show that in the class of Poissonian random graphs, X should have all its mass at 0 and one other real, which can be explicitly determined. For the thinned configuration model, D should have all its mass at 0 and two subsequent positive integers.

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