Martingales and the fixation time of evolutionary graphs with arbitrary dimensionality

Author:

Monk Travis1ORCID,van Schaik André1

Affiliation:

1. International Centre for Neuromorphic Systems, The MARCS Institute, Western Sydney University, Sydney, Australia

Abstract

Evolutionary graph theory (EGT) investigates the Moran birth–death process constrained by graphs. Its two principal goals are to find the fixation probability and time for some initial population of mutants on the graph. The fixation probability of graphs has received considerable attention. Less is known about the distribution of fixation time. We derive clean, exact expressions for the full conditional characteristic functions (CCFs) of a close proxy to fixation and extinction times. That proxy is the number of times that the mutant population size changes before fixation or extinction. We derive these CCFs from a product martingale that we identify for an evolutionary graph with any number of partitions. The existence of that martingale only requires that the connections between those partitions are of a certain type. Our results are the first expressions for the CCFs of any proxy to fixation time on a graph with any number of partitions. The parameter dependence of our CCFs is explicit, so we can explore how they depend on graph structure. Martingales are a powerful approach to study principal problems of EGT. Their applicability is invariant to the number of partitions in a graph, so we can study entire families of graphs simultaneously.

Publisher

The Royal Society

Subject

Multidisciplinary

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fixation times on directed graphs;PLOS Computational Biology;2024-07-18

2. The speed of neutral evolution on graphs;Journal of The Royal Society Interface;2024-05

3. Theoretical understanding of evolutionary dynamics on inhomogeneous networks;Physical Biology;2023-04-21

4. Suppressors of fixation can increase average fitness beyond amplifiers of selection;Proceedings of the National Academy of Sciences;2022-09-06

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