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Random Structures and Algorithms
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The Moran Process on a Random Graph

The Moran process on a random graph
Authors: Alan M. Frieze; Wesley Pegden;

The Moran Process on a Random Graph

Abstract

ABSTRACTWe study the fixation probability for two versions of the Moran process on the random graph at the threshold for connectivity. The Moran process models the spread of a mutant population in a network. Throughout the process, there are vertices of two types, mutants, and non‐mutants. Mutants have fitness and non‐mutants have fitness 1. The process starts with a unique individual mutant located at the vertex . In the Birth‐Death version of the process a random vertex is chosen proportionally to its fitness and then changes the type of a random neighbor to its own. The process continues until the set of mutants is empty or . 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 is empty or . The fixation probability is the probability that the process ends with . We show that asymptotically correct estimates of the fixation probability depend only on the degree of and its neighbors. In some cases we can provide values for these estimates and in other places we can only provide non‐linear recurrences that could be used to compute values.

Related Organizations
Keywords

fixation probability, Population dynamics (general), Branching processes (Galton-Watson, birth-and-death, etc.), Probability (math.PR), Random graphs (graph-theoretic aspects), Moran process, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Mathematics - Probability, random graph

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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