{"title":"Rowmotion Markov chains","authors":"Colin Defant , Rupert Li , Evita Nestoridi","doi":"10.1016/j.aam.2023.102666","DOIUrl":null,"url":null,"abstract":"<div><p><em>Rowmotion</em><span> is a certain well-studied bijective operator on the distributive lattice </span><span><math><mi>J</mi><mo>(</mo><mi>P</mi><mo>)</mo></math></span><span> of order ideals<span> of a finite poset </span></span><em>P</em>. We introduce the <span><em>rowmotion </em><em>Markov chain</em></span> <span><math><msub><mrow><mi>M</mi></mrow><mrow><mi>J</mi><mo>(</mo><mi>P</mi><mo>)</mo></mrow></msub></math></span><span> by assigning a probability </span><span><math><msub><mrow><mi>p</mi></mrow><mrow><mi>x</mi></mrow></msub></math></span> to each <span><math><mi>x</mi><mo>∈</mo><mi>P</mi></math></span> and using these probabilities to insert randomness into the original definition of rowmotion. More generally, we introduce a very broad family of <em>toggle Markov chains</em> inspired by Striker's notion of generalized toggling. We characterize when toggle Markov chains are irreducible, and we show that each toggle Markov chain has a remarkably simple stationary distribution.</p><p><span>We also provide a second generalization of rowmotion Markov chains to the context of semidistrim lattices. Given a semidistrim lattice </span><em>L</em>, we assign a probability <span><math><msub><mrow><mi>p</mi></mrow><mrow><mi>j</mi></mrow></msub></math></span> to each join-irreducible element <em>j</em> of <em>L</em> and use these probabilities to construct a rowmotion Markov chain <span><math><msub><mrow><mi>M</mi></mrow><mrow><mi>L</mi></mrow></msub></math></span>. Under the assumption that each probability <span><math><msub><mrow><mi>p</mi></mrow><mrow><mi>j</mi></mrow></msub></math></span> is strictly between 0 and 1, we prove that <span><math><msub><mrow><mi>M</mi></mrow><mrow><mi>L</mi></mrow></msub></math></span><span> is irreducible. We also compute the stationary distribution of the rowmotion Markov chain of a lattice obtained by adding a minimal element and a maximal element to a disjoint union of two chains.</span></p><p>We bound the mixing time of <span><math><msub><mrow><mi>M</mi></mrow><mrow><mi>L</mi></mrow></msub></math></span> for an arbitrary semidistrim lattice <em>L</em>. In the special case when <em>L</em><span><span> is a Boolean lattice, we use </span>spectral methods to obtain much stronger estimates on the mixing time, showing that rowmotion Markov chains of Boolean lattices exhibit the cutoff phenomenon.</span></p></div>","PeriodicalId":50877,"journal":{"name":"Advances in Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0196885823001847","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Rowmotion is a certain well-studied bijective operator on the distributive lattice of order ideals of a finite poset P. We introduce the rowmotion Markov chain by assigning a probability to each and using these probabilities to insert randomness into the original definition of rowmotion. More generally, we introduce a very broad family of toggle Markov chains inspired by Striker's notion of generalized toggling. We characterize when toggle Markov chains are irreducible, and we show that each toggle Markov chain has a remarkably simple stationary distribution.
We also provide a second generalization of rowmotion Markov chains to the context of semidistrim lattices. Given a semidistrim lattice L, we assign a probability to each join-irreducible element j of L and use these probabilities to construct a rowmotion Markov chain . Under the assumption that each probability is strictly between 0 and 1, we prove that is irreducible. We also compute the stationary distribution of the rowmotion Markov chain of a lattice obtained by adding a minimal element and a maximal element to a disjoint union of two chains.
We bound the mixing time of for an arbitrary semidistrim lattice L. In the special case when L is a Boolean lattice, we use spectral methods to obtain much stronger estimates on the mixing time, showing that rowmotion Markov chains of Boolean lattices exhibit the cutoff phenomenon.
期刊介绍:
Interdisciplinary in its coverage, Advances in Applied Mathematics is dedicated to the publication of original and survey articles on rigorous methods and results in applied mathematics. The journal features articles on discrete mathematics, discrete probability theory, theoretical statistics, mathematical biology and bioinformatics, applied commutative algebra and algebraic geometry, convexity theory, experimental mathematics, theoretical computer science, and other areas.
Emphasizing papers that represent a substantial mathematical advance in their field, the journal is an excellent source of current information for mathematicians, computer scientists, applied mathematicians, physicists, statisticians, and biologists. Over the past ten years, Advances in Applied Mathematics has published research papers written by many of the foremost mathematicians of our time.