The coalescent structure of continuous-time Galton-Watson trees

Simon Harris, Samuel Johnston, Matthew Roberts

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Take a continuous-time Galton-Watson tree. If the system survives until a large time T , then choose k particles uniformly from those alive. What does the ancestral tree drawn out by these k particles look like? Some special cases are known but we give a more complete answer.We concentrate on near-critical cases where the mean number of offspring is 1 + μ/T for some μ ∈ R, and show that a scaling limit exists as T →∞. Viewed backwards in time, the resulting coalescent process is topologically equivalent to Kingman's coalescent, but the times of coalescence have an interesting and highly nontrivial structure. The randomly fluctuating population size, as opposed to constant size populations where the Kingman coalescent more usually arises, have a pronounced effect on both the results and the method of proof required. We give explicit formulas for the distribution of the coalescent times, as well as a construction of the genealogical tree involving a mixture of independent and identically distributed random variables. In general subcritical and supercritical cases it is not possible to give such explicit formulas, but we highlight the special case of birth-death processes.

Original languageEnglish
Pages (from-to)1368-1414
Number of pages47
JournalAnnals of Applied Probability
Issue number3
Early online date29 Jul 2020
Publication statusPublished - 2020

Bibliographical note

Funding Information:
M. I. Roberts was supported during the early stages of this work by EPSRC fellowship EP/K007440/1, and during the latter stages by a Royal Society University Research Fellowship. S. G. G. Johnston was supported during for the major part of this work by University of Bath URS funding.

Publisher Copyright:
© Institute of Mathematical Statistics, 2020.


  • Coalescent
  • Galton-Watson tree
  • Genealogy
  • Spine

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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