随机图上的莫兰过程

Alan Frieze, Wesley Pegden
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引用次数: 0

摘要

我们研究了随机图 $G_{n,p}$ 上两个版本的莫兰过程在连通性阈值处的固定概率。莫兰过程模拟了突变种群在网络中的传播。在整个过程中,有突变体和非突变体两种顶点。突变体的适应度为 s$,非突变体的适应度为 1。该过程从位于顶点 $v_0$ 的唯一变异个体开始。在该过程的 "出生-死亡 "版本中,随机选择一个顶点,该顶点的适合度与其适合度成正比,然后将随机邻居的类型更改为自己的类型。这个过程一直持续到突变体集合$X$为空或$[n]$为止。在 "死亡-出生 "版本中,会选择一个统一的随机顶点,然后根据适合度选择一个随机邻居的类型。这个过程一直持续到突变体集合 $X$ 为空或 $[n]$。突变固定概率{em fixation probability}是指该过程以$X=\emptyset$结束的概率。我们给出了固定概率的渐近正确估计值,它取决于 $v_0$ 及其相邻变量的程度、
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Moran process on a random graph
We study the fixation probability for two versions of the Moran process on the random graph $G_{n,p}$ at the threshold for connectivity. The Moran process models the spread of a mutant population in a network. Throughtout the process there are vertices of two types, mutants and non-mutants. Mutants have fitness $s$ and non-mutants have fitness 1. The process starts with a unique individual mutant located at the vertex $v_0$. In the Birth-Death version of the process a random vertex is chosen proportional to its fitness and then changes the type of a random neighbor to its own. The process continues until the set of mutants $X$ is empty or $[n]$. In the Death-Birth version a uniform random vertex is chosen and then takes the type of a random neighbor, chosen according to fitness. The process again continues until the set of mutants $X$ is empty or $[n]$. The {\em fixation probability} is the probability that the process ends with $X=\emptyset$. We give asymptotically correct estimates of the fixation probability that depend on degree of $v_0$ and its neighbors.,
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