2015
DOI: 10.1002/rsa.20597
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On giant components and treewidth in the layers model

Abstract: ABSTRACT:Given an undirected n-vertex graph G(V , E) and an integer k, let T k (G) denote the random vertex induced subgraph of G generated by ordering V according to a random permutation π and including in T k (G) those vertices with at most k −1 of their neighbors preceding them in this order. The distribution of subgraphs sampled in this manner is called the layers model with parameter k. The layers model has found applications in studying -degenerate subgraphs, the design of algorithms for the maximum inde… Show more

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Cited by 2 publications
(14 citation statements)
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“…Construct now an auxiliary (random) multigraph H with two sets of vertices, U 1 and U 2 . Every component in L serves as a vertex in U 1 , and the number of good D vertices in a component serves as the number of half-edges of the corresponding U 1 -vertex (to avoid confusion we shall refer to the vertices in U 1 as super-vertices (following the terminology of [4]). Hence, on D(c ′ n) ∩ F , we have that c ′ n/a k ≤ |U 1 | ≤ n/a k and as every good vertex in D within a component in L contributes one edge to the degree of the super-vertex of H corresponding to its component in T 3 (G ′ ), we get that u∈U 1 d u ≥ c ′ n.…”
Section: Proof Of Theoremmentioning
confidence: 99%
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“…Construct now an auxiliary (random) multigraph H with two sets of vertices, U 1 and U 2 . Every component in L serves as a vertex in U 1 , and the number of good D vertices in a component serves as the number of half-edges of the corresponding U 1 -vertex (to avoid confusion we shall refer to the vertices in U 1 as super-vertices (following the terminology of [4]). Hence, on D(c ′ n) ∩ F , we have that c ′ n/a k ≤ |U 1 | ≤ n/a k and as every good vertex in D within a component in L contributes one edge to the degree of the super-vertex of H corresponding to its component in T 3 (G ′ ), we get that u∈U 1 d u ≥ c ′ n.…”
Section: Proof Of Theoremmentioning
confidence: 99%
“…To determine that H is likely to have a giant component we use Theorem 5.1. We first need the following proposition taken from [4]. Proposition 5.3.…”
Section: Proof Of Theoremmentioning
confidence: 99%
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