2006
DOI: 10.1007/978-3-540-32439-3_10
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Pseudo-random Graphs

Abstract: truly random graphs. He also supplied several examples of pseudo-random graphs and discussed many of their properties. Thomason's papers undoubtedly defined directions of future research for many years.Another cornerstone contribution belongs to Chung, Graham and Wilson [26] who in 1989 showed that many properties of different nature are in certain sense equivalent to the notion of pseudo-randomness, defined using the edge distribution. This fundamental result opened many new horizons by showing additional fa… Show more

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Cited by 245 publications
(213 citation statements)
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“…This notion was introduced by the first author in the 80's, motivated by the fact that if λ is much smaller than d, then the graph has strong pseudo-random properties. We mention a few of the properties of these graphs, and refer the readers to [11] for an extensive survey of the subject. Let G = (V, E) denote an (n, d, λ)-graph.…”
Section: Background and Definitionsmentioning
confidence: 99%
“…This notion was introduced by the first author in the 80's, motivated by the fact that if λ is much smaller than d, then the graph has strong pseudo-random properties. We mention a few of the properties of these graphs, and refer the readers to [11] for an extensive survey of the subject. Let G = (V, E) denote an (n, d, λ)-graph.…”
Section: Background and Definitionsmentioning
confidence: 99%
“…While many classes of random graphs exist (Bollobás, 2001;Krivelevich & Sudakov, 2006), we focus our study on three well-known classes of 3-colorable graphs: Uniform, equipartite, and flat.…”
Section: Random Graphsmentioning
confidence: 99%
“…For our purposes, α-jumbledness means that (as expected in G(N, p) graphs) for all vertex-sets U, V , the number of edges that pass from U to V should be p|U ||V | ± α |U ||V |. Jumbledness and quasirandomness had been studied extensively (see [31] and its many references), and serve in Graph Theory as the common notion of resemblance to random graphs. In particular, G(N, p) graphs are known to exhibit (the best possible) jumbledness parameter, α = Θ( √ pN ).…”
Section: Our Techniques and Relations To Combinatorial Pseudorandomnessmentioning
confidence: 99%