Continuous-time Mallows processes

TL;DR

This paper introduces continuous-time Mallows processes, establishing their existence, properties, and uniqueness, and explores their structural and probabilistic characteristics, including hypercube-like graph structures and Poisson convergence of jump times.

Contribution

It defines and constructs regular Mallows processes, proves their uniqueness as Markov processes, and analyzes their structural and probabilistic properties.

Findings

Existence of continuous-time Mallows processes with specific properties.

Unique Markov regular Mallows process identified.

Graph structure resembles an expanded hypercube; jump times converge to Poisson process.

Abstract

In this article, we introduce \textit{Mallows processes}, defined to be continuous-time c\`adl\`ag processes with Mallows distributed marginals. We show that such processes exist and that they can be restricted to have certain natural properties. In particular, we prove that there exists \textit{regular} Mallows processes, defined to have their inversions numbers $\mathrm{Inv}_j(\sigma)=|\{i\in[j-1]:\sigma(i)>\sigma(j)\}|$ be independent increasing stochastic processes with jumps of size $1$. We further show that there exists a unique Markov process which is a regular Mallows process. Finally, we study properties of regular Mallows processes and show various results on the structure of these objects. Among others, we prove that the graph structure related to regular Mallows processes looks like an \textit{expanded hypercube} where we stacked $k$ hypercubes on the dimension $k\in[n]$; we also prove that the first jumping times of regular Mallows processes converge to a Poisson point process.