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OP-8738Status unassessedProbability

Random walks on Dyck's paths

Markov chain mixing times · Historical workshop question

Editorial mapping of AIMPL source category: Probability. http://aimpl.org/markovmixing/ Not an author-supplied MSC code.

Historical list · status unassessedAs of 2026-09-08Source & evidence ↓

Problem statement

Consider the Markov chain on the set of Dyck's paths, which moves by choosing uniformly at random two coordinates and exchanging their value (++ or −1-1) provided the resulting path remains a Dyck's path. What is the mixing time?

Lean 4

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Background

Workshop introduction

In general, we will use the following notation in the problem list. We consider aperiodic irreducible Markov chains on a state space, Ω\Omega with unique invariant (stationary) distribution π\pi. In the discrete time setting we allow the matrix (P)x,y∈Ω(P)_{x,y\in\Omega} with Pxy=P(x,y)P_{xy}=P(x,y) to denote the transition matrix of the Markov chain.

A chain is reversible if π(x)P(x,y)=π(y)P(y,x)\pi(x)P(x,y)=\pi(y)P(y,x) for all x,y∈Ωx,y\in\Omega. Q(x,y)=π(x)P(x,y)Q(x,y)=\pi(x)P(x,y) is the edge measure on (x,y)(x,y). We denote by t\mboxmixt_{\mbox{mix}} the total variation mixing time defined as

t\mboxmix(ϵ)=inf⁡{t:sup⁡ω0∈Ω∥Pt(ω0,⋅)−π(⋅)∥TV≤ϵ} ,t_{\mbox{mix}}(\epsilon)=\inf\{t:\sup_{\omega_0\in\Omega}\|P^t(\omega_0,\cdot)-\pi(\cdot)\|_{TV}\leq \epsilon\}\,,

and set t\mboxmix=t\mboxmix(ϵ)t_{\mbox{mix}}=t_{\mbox{mix}}(\epsilon), where the total variation distance

∥μ−ν∥TV=12∥μ−ν∥ℓ1 .\|\mu-\nu\|_{TV}=\tfrac 12 \|\mu-\nu\|_{\ell^1}\,.

Progress & source assessment

Historical workshop record. Current open/solved status has not been independently reassessed.

Status note in the source

Cohen, Tetali, Yeliussizov (2015) showed a lower bound of Ω(n)\Omega(n) and an upper bound of O(n2log⁡n)O(n^2\log n).

References
  1. [1]Markov chain mixing times link

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