TY - JOUR
T1 - Annihilation and coalescence on binary trees
AU - Benjamini, Itai
AU - Lima, Yuri
N1 - ERC [239885]; Brin FellowshipThe authors are thankful to Cyrille Lucas for useful discussions, and to Matheus Secco for carefully reading the preliminary version of this work. I. B. is the incumbent of the Renee and Jay Weiss Professorial Chair. During the preparation of this manuscript, Y.L. was a Postdoctoral Fellow at the Weizmann Institute of Science, supported by the ERC, grant 239885. Y.L. is supported by the Brin Fellowship.
PY - 2014/9
Y1 - 2014/9
N2 - An infection spreads in a binary tree $\mathcal{T}-n$ of height n as follows: initially, each leaf is either infected by one of k states or it is not infected at all. The infection state of each leaf is independently distributed according to a probability vector p = (p1, ..., p k+1). The remaining nodes become infected or not via annihilation and coalescence: nodes whose two children have the same state (infected or not) are infected (or not) by this state; nodes whose two children have different states are not infected; nodes such that only one of the children is infected are infected by this state. In this paper we characterize, for every p, the limiting distribution at the root node of $\mathcal{T}-n$ as n goes to infinity. We also consider a variant of the model when k = 2 and a mutation can happen, with a fixed probability q, at each infection step. We characterize, in terms of p and q, the limiting distribution at the root node of $\mathcal{T}-n$ as n goes to infinity. The distribution at the root node is driven by a dynamical system, and the proofs rely on the analysis of this dynamics.
AB - An infection spreads in a binary tree $\mathcal{T}-n$ of height n as follows: initially, each leaf is either infected by one of k states or it is not infected at all. The infection state of each leaf is independently distributed according to a probability vector p = (p1, ..., p k+1). The remaining nodes become infected or not via annihilation and coalescence: nodes whose two children have the same state (infected or not) are infected (or not) by this state; nodes whose two children have different states are not infected; nodes such that only one of the children is infected are infected by this state. In this paper we characterize, for every p, the limiting distribution at the root node of $\mathcal{T}-n$ as n goes to infinity. We also consider a variant of the model when k = 2 and a mutation can happen, with a fixed probability q, at each infection step. We characterize, in terms of p and q, the limiting distribution at the root node of $\mathcal{T}-n$ as n goes to infinity. The distribution at the root node is driven by a dynamical system, and the proofs rely on the analysis of this dynamics.
UR - http://www.scopus.com/inward/record.url?scp=84901827355&partnerID=8YFLogxK
U2 - 10.1142/S0219493713500238
DO - 10.1142/S0219493713500238
M3 - مقالة
SN - 0219-4937
VL - 14
JO - Stochastics and Dynamics
JF - Stochastics and Dynamics
IS - 3
M1 - 1350023
ER -