Ungarian Markov Chains

Fuente: arXiv
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Autori principali: Defant, Colin, Li, Rupert
Natura: Preprint
Pubblicazione: 2023
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author Defant, Colin
Li, Rupert
author_facet Defant, Colin
Li, Rupert
contents We introduce the Ungarian Markov chain ${\bf U}_L$ associated to a finite lattice $L$. The states of this Markov chain are the elements of $L$. When the chain is in a state $x\in L$, it transitions to the meet of $\{x\}\cup T$, where $T$ is a random subset of the set of elements covered by $x$. We focus on estimating $\mathcal E(L)$, the expected number of steps of ${\bf U}_L$ needed to get from the top element of $L$ to the bottom element of $L$. Using direct combinatorial arguments, we provide asymptotic estimates when $L$ is the weak order on the symmetric group $S_n$ and when $L$ is the $n$-th Tamari lattice. When $L$ is distributive, the Markov chain ${\bf U}_L$ is equivalent to an instance of the well-studied random process known as last-passage percolation with geometric weights. One of our main results states that if $L$ is a trim lattice, then $\mathcal E(L)\leq\mathcal E(\text{spine}(L))$, where $\text{spine}(L)$ is a specific distributive sublattice of $L$ called the spine of $L$. Combining this lattice-theoretic theorem with known results about last-passage percolation yields a powerful method for proving upper bounds for $\mathcal E(L)$ when $L$ is trim. We apply this method to obtain uniform asymptotic upper bounds for the expected number of steps in the Ungarian Markov chains of Cambrian lattices of classical types and the Ungarian Markov chains of $ν$-Tamari lattices.
format Preprint
id arxiv_https___arxiv_org_abs_2301_08206
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Ungarian Markov Chains
Defant, Colin
Li, Rupert
Combinatorics
Probability
06D75, 05E16, 06B05, 60J10
We introduce the Ungarian Markov chain ${\bf U}_L$ associated to a finite lattice $L$. The states of this Markov chain are the elements of $L$. When the chain is in a state $x\in L$, it transitions to the meet of $\{x\}\cup T$, where $T$ is a random subset of the set of elements covered by $x$. We focus on estimating $\mathcal E(L)$, the expected number of steps of ${\bf U}_L$ needed to get from the top element of $L$ to the bottom element of $L$. Using direct combinatorial arguments, we provide asymptotic estimates when $L$ is the weak order on the symmetric group $S_n$ and when $L$ is the $n$-th Tamari lattice. When $L$ is distributive, the Markov chain ${\bf U}_L$ is equivalent to an instance of the well-studied random process known as last-passage percolation with geometric weights. One of our main results states that if $L$ is a trim lattice, then $\mathcal E(L)\leq\mathcal E(\text{spine}(L))$, where $\text{spine}(L)$ is a specific distributive sublattice of $L$ called the spine of $L$. Combining this lattice-theoretic theorem with known results about last-passage percolation yields a powerful method for proving upper bounds for $\mathcal E(L)$ when $L$ is trim. We apply this method to obtain uniform asymptotic upper bounds for the expected number of steps in the Ungarian Markov chains of Cambrian lattices of classical types and the Ungarian Markov chains of $ν$-Tamari lattices.
title Ungarian Markov Chains
topic Combinatorics
Probability
06D75, 05E16, 06B05, 60J10
url https://arxiv.org/abs/2301.08206