Scaling limits for exploration algorithms

Abstract

We consider an exploration algorithm where at each step, a random number of items become active while related items get explored. Given an initial number of items $N$ growing to infinity and building on a strong homogeneity assumption, we study using scaling limits of Markovian processes statistical properties of the proportion of active nodes in time. This is a companion paper that rigorously establishes the claims and heuristics presented in [5]. [5] Jaron Sanders, Matthieu Jonckheere, and Servaas Kokkelmans. Sub-Poissonian statistics of jamming limits in Rydberg gases. 2015. To appear.