Scaling-limit conjecture for ancestral lineages in ranked tree-child networks

Let Xk()X^{(\ell)}_k denote the number of lineages in the ancestry of a leaf after moving kk steps away from that leaf in a uniformly sampled ranked tree-child network with \ell leaves. For fixed MM, consider the rescaled random variable at time M\lfloor \ell-M\sqrt{\ell}\rfloor. Scaling-limit conjecture. The sequence of random variables

1XM()\frac{1}{\sqrt{\ell}}X^{(\ell)}_{\lfloor\ell-M\sqrt{\ell}\rfloor}

converges in distribution to a positive random variable WMW_M. This conjecture gives a precise version of the paper's broader prediction that the lineage-counting Markov chain, suitably rescaled as the number of leaves tends to infinity, converges to a smooth function with a random shape parameter. The preceding proposition supplies expectation bounds, but convergence in distribution is left conjectural.

Sources & referencesView supporting material

Primary source

François Bienvenu, Amaury Lambert and Mike Steel, “Combinatorial and stochastic properties of ranked tree-child networks”, arXiv:2007.09701 (2021).

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