Sampling triangulations of manifolds using Monte Carlo methods
Eduardo G. Altmann, Jonathan Spreer

TL;DR
This paper introduces a Monte Carlo approach using biased random walks to efficiently sample and analyze triangulations of manifolds, enabling estimation of rare configurations and growth rates.
Contribution
It presents a novel Monte Carlo method combining Pachner moves with Metropolis-Hastings to sample manifold triangulations uniformly or with bias, applicable to surfaces and 3-manifolds.
Findings
Recovered asymptotic growth rates for sphere triangulations
Observed exponential growth in 3-sphere triangulation types
Provided evidence of fixed edge-degree distributions in large 3-sphere triangulations
Abstract
We propose a Monte Carlo method to efficiently find, count, and sample abstract triangulations of a given manifold M. The method is based on a biased random walk through all possible triangulations of M (in the Pachner graph), constructed by combining (bi-stellar) moves with suitable chosen accept/reject probabilities (Metropolis-Hastings). Asymptotically, the method guarantees that samples of triangulations are drawn at random from a chosen probability. This enables us not only to sample (rare) triangulations of particular interest but also to estimate the (extremely small) probability of obtaining them when isomorphism types of triangulations are sampled uniformly at random. We implement our general method for surface triangulations and 1-vertex triangulations of 3-manifolds. To showcase its usefulness, we present a number of experiments: (a) we recover asymptotic growth rates for the…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Topological and Geometric Data Analysis · Computational Geometry and Mesh Generation
