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Related papers: Cutoff for product replacement on finite groups

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We show that for any semi-random transposition shuffle on $n$ cards, the mixing time of any given $k$ cards is at most $n\log k$, provided $k=o((n/\log n)^{1/2})$. In the case of the top-to-random transposition shuffle we show that there is…

Probability · Mathematics 2013-02-12 Richard Pymar

Consider shuffling a deck of $n$ cards, labeled $1$ through $n$, as follows: at each time step, pick one card uniformly with your right hand and another card, independently and uniformly with your left hand; then swap the cards. How long…

Probability · Mathematics 2024-11-01 Vishesh Jain , Mehtaab Sawhney

Let $\{G_n\}_1^{\infty}$ be a sequence of non-trivial finite groups. In this paper, we study the properties of a random walk on the complete monomial group $G_n\wr S_n$ generated by the elements of the form…

Probability · Mathematics 2025-04-17 Subhajit Ghosh

In this article we study the so-called cut-off phenomenon in the total variation distance when $n\to \infty$ for the family of continuous-time stochastic processes indexed by $n\in \mathbb{N}$, \[ \left( \mathcal{Z}^{(n)}_t=…

Probability · Mathematics 2023-05-05 Gerardo Barrera

We analyze the mixing time of a popular shuffling machine known as the shelf shuffler. It is a modified version of a $2m$-handed riffle shuffle ($m=10$ in casinos) in which a deck of $n$ cards is split multinomially into $2m$ piles, the…

Probability · Mathematics 2024-10-24 Andrea Ottolini , Ray Chen

We study the lazy Markov chain on $\mathbf{F}_p$ defined as $X_{n+1}=X_n$ with probability $1/2$ and $X_{n+1}=f(X_n) \cdot \varepsilon_{n+1}$, where $\varepsilon_n$ are random variables distributed uniformly on $\{ \gamma^{},…

Combinatorics · Mathematics 2021-06-18 Ilya D. Shkredov

We provide quantitative upper bounds on the total variation mixing time of the Markov chain corresponding to the unadjusted Hamiltonian Monte Carlo (uHMC) algorithm. For two general classes of models and fixed time discretization step size…

Probability · Mathematics 2022-10-13 Nawaf Bou-Rabee , Andreas Eberle

We develop Markov chain mixing time estimates for a class of Markov chains with restricted transitions. We assume transitions may occur along a cycle of $n$ nodes and on $n^\gamma$ additional edges, where $\gamma < 1$. We find that the…

Probability · Mathematics 2015-06-26 Balázs Gerencsér

The cutoff phenomenon was recently shown to systematically follow from non-negative curvature and the product condition, for all Markov diffusions. The proof crucially relied on a classical \emph{chain rule} satisfied by the carr\'e du…

Probability · Mathematics 2025-01-23 Francesco Pedrotti , Justin Salez

Let $G$ be a finite group. The commuting chain on $G$ moves from an element $x$ to $y$ by selecting $y$ uniformly amongst those which commute with $x$. The $t$ step transition probabilities of this chain converge to a distribution uniform…

Probability · Mathematics 2020-10-19 John Rahmani

We prove that any Markov chain that performs local, reversible updates on randomly chosen vertices of a bounded-degree graph necessarily has mixing time at least $\Omega(n\log n)$, where $n$ is the number of vertices. Our bound applies to…

Probability · Mathematics 2009-09-29 Thomas P. Hayes , Alistair Sinclair

The mixer chain on a graph G is the following Markov chain. Place tiles on the vertices of G, each tile labeled by its corresponding vertex. A "mixer" moves randomly on the graph, at each step either moving to a randomly chosen neighbor, or…

Probability · Mathematics 2009-01-13 Ariel Yadin

We study the random walk on a finite dihedral group $G$ driven by the uniform measure on $k$ independently and uniformly chosen elements. We show that the walk exhibits cutoff with high probability throughout nearly the entire regime $1 \ll…

Probability · Mathematics 2025-10-24 Xiangying Huang , Renyu Rao

The spectral gap $\gamma$ of a finite, ergodic, and reversible Markov chain is an important parameter measuring the asymptotic rate of convergence. In applications, the transition matrix $P$ may be unknown, yet one sample of the chain up to…

Statistics Theory · Mathematics 2017-08-25 Daniel Hsu , Aryeh Kontorovich , David A. Levin , Yuval Peres , Csaba Szepesvári

We present a novel approach to quantizing Markov chains. The approach is based on the Markov chain coupling method, which is frequently used to prove fast mixing. Given a particular coupling, e.g., a grand coupling, we construct a…

Quantum Physics · Physics 2025-12-24 Kristan Temme , Pawel Wocjan

The hitting and mixing times are two fundamental quantities associated with Markov chains. In Peres and Sousi[PS2015] and Oliveira[Oli2012], the authors show that the mixing times and "worst-case" hitting times of reversible Markov chains…

Probability · Mathematics 2019-04-05 Robert M. Anderson , Haosui Duanmu , Aaron Smith

We study a broad class of high-dimensional mean-field exchange models, encompassing both noisy and singular dynamics, along with their dual processes. This includes a generalized version of the averaging process as well as some…

Probability · Mathematics 2025-06-17 Pietro Caputo , Matteo Quattropani , Federico Sau

Given a reversible Markov chain $P_n$ on $n$ states, and another chain $\tilde{P}_n$ obtained by perturbing each row of $P_n$ by at most $\alpha_n$ in total variation, we study the total variation distance between the two stationary…

Probability · Mathematics 2021-03-16 Daniel Vial , Vijay Subramanian

We show that the total variation mixing time of the simple random walk on the giant component of supercritical Erdos-Renyi graphs is log^2 n. This statement was only recently proved, independently, by Fountoulakis and Reed. Our proof…

Probability · Mathematics 2016-08-02 Itai Benjamini , Gady Kozma , Nicholas Wormald

Given an irreducible discrete-time Markov chain on a finite state space, we consider the largest expected hitting time $T(\alpha)$ of a set of stationary measure at least $\alpha$ for $\alpha\in(0,1)$. We obtain tight inequalities among the…

Probability · Mathematics 2015-10-29 Simon Griffiths , Ross J. Kang , Roberto Imbuzeiro Oliveira , Viresh Patel