Random convex chains through the lens of analytic combinatorics

Fuente: arXiv
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Main Authors: Besau, Florian, Thäle, Christoph
Format: Preprint
Published: 2025
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author Besau, Florian
Thäle, Christoph
author_facet Besau, Florian
Thäle, Christoph
contents Consider the triangle $T$ with vertices $(0,0)$, $(0,1)$, and $(1,0)$. The lower boundary of the convex hull of $(0,1)$, $(1,0)$, together with $n$ independent uniformly distributed random points in $T$, is called a random convex chain and denoted by $T_n$. We study the random variable $f_0(T_n)$, the number of vertices of this chain. Our first result gives an explicit expression for the bivariate generating function of the probabilities $\mathbb{P}(f_0(T_n)=k+2)$ in terms of the Gaussian hypergeometric function. Building on this analytic representation, we apply a careful singularity analysis to derive a variety of limit theorems for $f_0(T_n)$, including a quantitative central limit theorem, a large deviation principle as well as a precise asymptotics for the probabilities $\mathbb{P}(f_0(T_n)=k+2)$. Conceptually, our results establish a novel bridge between stochastic geometry and methods from analytic combinatorics.
format Preprint
id arxiv_https___arxiv_org_abs_2510_16793
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Random convex chains through the lens of analytic combinatorics
Besau, Florian
Thäle, Christoph
Probability
Combinatorics
Metric Geometry
Pirmary: 52A22 60D05, Secondary: 05A15 32A05 33C05 60F10
Consider the triangle $T$ with vertices $(0,0)$, $(0,1)$, and $(1,0)$. The lower boundary of the convex hull of $(0,1)$, $(1,0)$, together with $n$ independent uniformly distributed random points in $T$, is called a random convex chain and denoted by $T_n$. We study the random variable $f_0(T_n)$, the number of vertices of this chain. Our first result gives an explicit expression for the bivariate generating function of the probabilities $\mathbb{P}(f_0(T_n)=k+2)$ in terms of the Gaussian hypergeometric function. Building on this analytic representation, we apply a careful singularity analysis to derive a variety of limit theorems for $f_0(T_n)$, including a quantitative central limit theorem, a large deviation principle as well as a precise asymptotics for the probabilities $\mathbb{P}(f_0(T_n)=k+2)$. Conceptually, our results establish a novel bridge between stochastic geometry and methods from analytic combinatorics.
title Random convex chains through the lens of analytic combinatorics
topic Probability
Combinatorics
Metric Geometry
Pirmary: 52A22 60D05, Secondary: 05A15 32A05 33C05 60F10
url https://arxiv.org/abs/2510.16793