Tóth's buses and the "detachment process''

Fuente: arXiv
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Main Author: Engländer, János
Format: Preprint
Published: 2025
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author Engländer, János
author_facet Engländer, János
contents This paper introduces the \textbf{detachment process}, a novel, time-inhomogeneous Markov process inspired by I. P. Tóth's problem \cite{Toth} concerning the number of ``lonely passengers'' (those without companions) when $n$ passengers are seated independently and uniformly in $k$ initially empty buses. Tóth showed that this number is stochastically non-decreasing in $k$ for fixed $n$ (see also Haslegrave's work \cite{Haslegrave}). We extend Tóth's model by treating the number of buses $k$ as a time parameter. Specifically, for a fixed number of passengers $n$, the state of our Markov process at time $k \ge 1$ is exactly Tóth's configuration $(n, k)$. (We formally extend the process definition for all $t \in [1, \infty)$.) These processes can be coupled for all $n \ge 1$, and this larger coupled process is what we dub the \textbf{detachment process}. Our investigation focuses on properties related to detachment, clumping, the number of lonely passengers and of non-empty buses. The central notion is \textbf{detachment}, which occurs at time $k$ if every passenger occupies a distinct bus; we say the process is \textbf{in a state of detachment} at $k$. A \textbf{detachment time} $k$ is when the process transitions from a non-detached state at $k-1$ to a detached state at $k$. \textbf{Four critical time scales} are idetified -- linear, quadratic, and log-corrected linear or quadratic in the number of passengers, $n$ -- that govern the process's properties. We investigate (relative) clumping. We also explore why modeling the number of passengers with a Poisson distribution simplifies the analysis of Tóth's original model. To aid this derivation, we introduce a comparison theorem for binomial distributions, originally obtained by J. Najnudel \cite{Najnudel}, along with a novel proof.
format Preprint
id arxiv_https___arxiv_org_abs_2512_05896
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Tóth's buses and the "detachment process''
Engländer, János
Probability
Primary: 60J10, Secondary: 60C05
This paper introduces the \textbf{detachment process}, a novel, time-inhomogeneous Markov process inspired by I. P. Tóth's problem \cite{Toth} concerning the number of ``lonely passengers'' (those without companions) when $n$ passengers are seated independently and uniformly in $k$ initially empty buses. Tóth showed that this number is stochastically non-decreasing in $k$ for fixed $n$ (see also Haslegrave's work \cite{Haslegrave}). We extend Tóth's model by treating the number of buses $k$ as a time parameter. Specifically, for a fixed number of passengers $n$, the state of our Markov process at time $k \ge 1$ is exactly Tóth's configuration $(n, k)$. (We formally extend the process definition for all $t \in [1, \infty)$.) These processes can be coupled for all $n \ge 1$, and this larger coupled process is what we dub the \textbf{detachment process}. Our investigation focuses on properties related to detachment, clumping, the number of lonely passengers and of non-empty buses. The central notion is \textbf{detachment}, which occurs at time $k$ if every passenger occupies a distinct bus; we say the process is \textbf{in a state of detachment} at $k$. A \textbf{detachment time} $k$ is when the process transitions from a non-detached state at $k-1$ to a detached state at $k$. \textbf{Four critical time scales} are idetified -- linear, quadratic, and log-corrected linear or quadratic in the number of passengers, $n$ -- that govern the process's properties. We investigate (relative) clumping. We also explore why modeling the number of passengers with a Poisson distribution simplifies the analysis of Tóth's original model. To aid this derivation, we introduce a comparison theorem for binomial distributions, originally obtained by J. Najnudel \cite{Najnudel}, along with a novel proof.
title Tóth's buses and the "detachment process''
topic Probability
Primary: 60J10, Secondary: 60C05
url https://arxiv.org/abs/2512.05896