Effect of Dimensionality on the Continuum Percolation of Overlapping Hyperspheres and Hypercubes: II. Simulation Results and Analyses

TL;DR

This paper presents advanced simulation techniques and analytical bounds for continuum percolation of overlapping hyperspheres and hypercubes across multiple dimensions, revealing high-dimensional insights and confirming previous theoretical predictions.

Contribution

It introduces an efficient rescaled-particle simulation method and provides new analytical bounds and estimates for percolation thresholds and cluster statistics in high-dimensional spaces.

Findings

Bounds on percolation thresholds converge as dimension increases

Lower bounds accurately estimate percolation properties even at low dimensions

High-dimensional percolation properties encode information about lower dimensions

Abstract

In the first paper of this series [S. Torquato, J. Chem. Phys. {\bf 136}, 054106 (2012)], analytical results concerning the continuum percolation of overlapping hyperparticles in $d$-dimensional Euclidean space $\mathbb{R}^d$ were obtained, including lower bounds on the percolation threshold. In the present investigation, we provide additional analytical results for certain cluster statistics, such as the concentration of $k$-mers and related quantities, and obtain an upper bound on the percolation threshold $\eta_c$. We utilize the tightest lower bound obtained in the first paper to formulate an efficient simulation method, called the {\it rescaled-particle} algorithm, to estimate continuum percolation properties across many space dimensions with heretofore unattained accuracy. This simulation procedure is applied to compute the threshold $\eta_c$ and associated mean number of overlaps per particle ${\cal N}_c$ for both overlapping hyperspheres and oriented hypercubes for $ 3 \le d \le 11$. These simulations results are compared to corresponding upper and lower bounds on these percolation properties. We find that the bounds converge to one another as the space dimension increases, but the lower bound provides an excellent estimate of $\eta_c$ and ${\cal N}_c$, even for relatively low dimensions. We confirm a prediction of the first paper in this series that low-dimensional percolation properties encode high-dimensional information. We also show that the concentration of monomers dominate over concentration values for higher-order clusters (dimers, trimers, etc.) as the space dimension becomes large. Finally, we provide accurate analytical estimates of the pair connectedness function and blocking function at their contact values for any $d$ as a function of density.