One-dimensional Multi-particle DLA -- a PDE approach
Vladas Sidoravicius, Balazs Rath

TL;DR
This paper analyzes the one-dimensional multi-particle diffusion limited aggregation model, providing heuristic predictions for growth rates in different regimes and comparing them with new simulation results.
Contribution
It offers new heuristic predictions for the growth constants in various phases of the 1D MDLA model and validates them with recent computer simulations.
Findings
Subcritical case: growth like √t with constant c(μ)
Critical case: growth like t^{2/3}
Predictions match simulation results
Abstract
In the present note we analyze the one-dimensional multi-particle diffusion limited aggregation (MDLA) model: the initial number of particles at each positive integer site has Poisson distribution with mean , independently of all other sites. Particles perform independent continuous-time simple symmetric random walks until they come to the site neighbouring the sticky aggregate, which initially consists only of the origin. If a particle tries to jump on the aggregate, the size of the aggregate increases by one, i.e., its rightmost point moves to the right by one unit. All particles which are present at the site neighbouring the aggregate at the moment when the aggregate advances, are immediately deleted. The dimensional MDLA model, , was introduced in 1980 by Rosenstock and Marquardt, and studied numerically by Voss (1984). The one dimensional model exhibits a phase…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Theoretical and Computational Physics · Complex Network Analysis Techniques
