English

Regenerative tree growth: Markovian embedding of fragmenters, bifurcators, and bead splitting processes

Probability 2015-11-18 v2

Abstract

Some, but not all processes of the form Mt=exp(ξt)M_t=\exp(-\xi_t) for a pure-jump subordinator ξ\xi with Laplace exponent Φ\Phi arise as residual mass processes of particle 1 (tagged particle) in Bertoin's partition-valued exchangeable fragmentation processes. We introduce the notion of a Markovian embedding of M=(Mt,t0)M=(M_t,t\ge 0) in a fragmentation process, and we show that for each Φ\Phi, there is a unique (in distribution) binary fragmentation process in which MM has a Markovian embedding. The identification of the Laplace exponent Φ\Phi^* of its tagged particle process MM^* gives rise to a symmetrisation operation ΦΦ\Phi\mapsto\Phi^*, which we investigate in a general study of pairs (M,M)(M,M^*) that coincide up to a random time and then evolve independently. We call MM a fragmenter and (M,M)(M,M^*) a bifurcator. For α>0\alpha>0, we equip the interval R1=[0,0Mtαdt]R_1=[0,\int_0^{\infty}M_t^{\alpha}\,dt] with a purely atomic probability measure μ1\mu_1, which captures the jump sizes of MM suitably placed on R1R_1. We study binary tree growth processes that in the nnth step sample an atom (``bead'') from μn\mu _n and build (Rn+1,μn+1)(R_{n+1},\mu_{n+1}) by replacing the atom by a rescaled independent copy of (R1,μ1)(R_1,\mu_1) that we tie to the position of the atom. We show that any such bead splitting process ((Rn,μn),n1)((R_n,\mu_n),n\ge1) converges almost surely to an α\alpha-self-similar continuum random tree of Haas and Miermont, in the Gromov-Hausdorff-Prohorov sense. This generalises Aldous's line-breaking construction of the Brownian continuum random tree.

Keywords

Cite

@article{arxiv.1304.0802,
  title  = {Regenerative tree growth: Markovian embedding of fragmenters, bifurcators, and bead splitting processes},
  author = {Jim Pitman and Matthias Winkel},
  journal= {arXiv preprint arXiv:1304.0802},
  year   = {2015}
}

Comments

Published at http://dx.doi.org/10.1214/14-AOP945 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)