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On Hamilton cycles in Erdos-Renyi subgraphsof large graphs

机译:在大型图形埃尔多斯 - 仁义子画面的汉密尔顿周期

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Given a graph Gamma(n)=(V,E) on n vertices and m edges, we define the Erdos-Renyi graph process with host Gamma(n) as follows. A permutation e(1), horizontal ellipsis ,e(m) of E is chosen uniformly at random, and for t <= m we let Gamma(n,t)=(V,{e(1), horizontal ellipsis ,e(t)}). Suppose the minimum degree of Gamma(n) is delta(Gamma(n)) >= (1/2+epsilon)n for some constant epsilon>0. Then with high probability (An event & x2130;n holds with high probability (whp) if Pr & x2130;n -> 1 as n ->infinity.), Gamma(n,t) becomes Hamiltonian at the same moment that its minimum degree reaches 2. Given 0 <= p <= 1 let Gamma(n,p) be the Erdos-Renyi subgraph of Gamma(n), obtained by retaining each edge independently with probability p. When delta(Gamma(n)) >= (1/2+epsilon)n, we provide a threshold for Hamiltonicity in Gamma(n,p).
机译:给定N个顶点和M边缘的图形伽马(n)=(v,e),我们将Erdos-renyi图形过程定义为主机伽马(n)如下。 随机均匀地选择e(1),e的水平椭圆,e(m),并且对于t <= m,我们让伽马(n,t)=(v,{e(1),水平省略号,e (t)})。 假设γ(n)的最小程度是δ(γ(n))> =(1/2 +ε)n,用于一些恒定的ε0> 0。 然后具有高概率(事件&x2130; n,如果pr&x2130为n - >无穷大,则用高概率(whp)保持高概率(whp)。),伽玛(n,t)在其最小的同时变成哈密尔顿人 程度达到2.给出0 <= P <= 1让γ(n,p)是γ(n)的ERDOS-renyi子图,通过与概率p独立地保持每个边缘而获得。 当δ(γ(n))> =(1/2 + epsilon)n时,我们在γ(n,p)中提供哈密尼的阈值。

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