Random parking, Euclidean functionals, and rubber elasticity
Antoine Gloria, Mathew D. Penrose

TL;DR
This paper extends the analysis of subadditive functions in the random parking model, establishing convergence results and applying them to Euclidean optimization problems and rubber elasticity models, including stochastic networks.
Contribution
It generalizes existing results on the jamming limit to a broader class of subadditive functions, including applications to rubber elasticity and stochastic networks.
Findings
Existence of a limiting constant for subadditive functions in the random parking model.
Application of the limit result to Euclidean optimization problems.
Approximation of continuous energy density in rubber elasticity at the thermodynamic limit.
Abstract
We study subadditive functions of the random parking model previously analyzed by the second author. In particular, we consider local functions of subsets of and of point sets that are (almost) subadditive in their first variable. Denoting by the random parking measure in , and by the random parking measure in the cube , we show, under some natural assumptions on , that there exists a constant such that % % almost surely. If is the counting measure of in , then we retrieve the result by the second author on the existence of the jamming limit. The present work generalizes this result to a wide class of (almost) subadditive functions. In particular,…
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