English

T\'oth's buses and the "detachment process''

Probability 2025-12-08 v1

Abstract

This paper introduces the \textbf{detachment process}, a novel, time-inhomogeneous Markov process inspired by I. P. T\'oth's problem \cite{Toth} concerning the number of ``lonely passengers'' (those without companions) when nn passengers are seated independently and uniformly in kk initially empty buses. T\'oth showed that this number is stochastically non-decreasing in kk for fixed nn (see also Haslegrave's work \cite{Haslegrave}). We extend T\'oth's model by treating the number of buses kk as a time parameter. Specifically, for a fixed number of passengers nn, the state of our Markov process at time k1k \ge 1 is exactly T\'oth's configuration (n,k)(n, k). (We formally extend the process definition for all t[1,)t \in [1, \infty).) These processes can be coupled for all n1n \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 kk if every passenger occupies a distinct bus; we say the process is \textbf{in a state of detachment} at kk. A \textbf{detachment time} kk is when the process transitions from a non-detached state at k1k-1 to a detached state at kk. \textbf{Four critical time scales} are idetified -- linear, quadratic, and log-corrected linear or quadratic in the number of passengers, nn -- 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 T\'oth'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.

Cite

@article{arxiv.2512.05896,
  title  = {T\'oth's buses and the "detachment process''},
  author = {János Engländer},
  journal= {arXiv preprint arXiv:2512.05896},
  year   = {2025}
}
R2 v1 2026-07-01T08:11:57.117Z