Local limit of Prim's algorithm

TL;DR

This paper investigates the dynamic process of Prim's algorithm on large graphs, showing how the local structure of the MST evolves from initial stages to the full limit using dynamic local convergence theory.

Contribution

It introduces a framework to analyze the local evolution of Prim's algorithm on large graphs and demonstrates the interpolation of local structures over time.

Findings

The local structure of the MST evolves smoothly from initial to full limit.

Prim's algorithm's local limit can be understood dynamically over time.

The approach applies to various graph models satisfying certain assumptions.

Abstract

We study the local evolution of Prim's algorithm on large finite weighted graphs. When performed for $n$ steps, where $n$ is the size of the graph, Prim's algorithm will construct the minimal spanning tree (MST). We assume that our graphs converge locally in probability to some limiting rooted graph. In that case, Aldous and Steele already proved that the local limit of the MST converges to a limiting object, which can be thought of as the MST on the limiting infinite rooted graph. Our aim is to investigate {\em how} the local limit of the MST is reached \textit{dynamically}. For this, we take $tn+o(n)$ steps of Prim, for $t\in[0,1]$, and, under some reasonable assumptions, show how the local structure interpolates between performing Prim's algorithm on the local limit when $t=0$, to the full local limit of the MST for $t=1$. Our proof relies on the use of the recently developed theory of {\em dynamic local convergence}. We further present several examples for which our assumptions, and thus our results, apply.