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The chain rule lies at the heart of the powerful Gamma calculus for Markov diffusions on manifolds, providing remarkable connections between several fundamental notions such as Bakry-\'Emery curvature, entropy decay, and hypercontractivity.…

Probability · Mathematics 2025-03-05 Justin Salez , Pierre Youssef

We prove an invariance principle for non-stationary random processes and establish a rate of convergence under a new type of mixing condition. The dependence is exponentially decaying in the gap between the past and the future and is…

Probability · Mathematics 2024-12-23 Ion Grama , Émile Le Page , Marc Peigné

We consider a new functional inequality controlling the rate of relative entropy decay for random walks, the interchange process and more general block-type dynamics for permutations. The inequality lies between the classical logarithmic…

Probability · Mathematics 2022-05-12 Alexandre Bristiel , Pietro Caputo

We focus on the log-Sobolev inequality for spin systems on the lattice with interactions of higher order than quadratic. We show that if the one-dimensional single-site measure with boundaries satisfies the log-Sobolev inequality uniformly…

Functional Analysis · Mathematics 2020-01-24 James Inglis , Ioannis Papageorgiou

The existence and uniqueness of the numerical invariant measure of the backward Euler-Maruyama method for stochastic differential equations with Markovian switching is yielded, and it is revealed that the numerical invariant measure…

Probability · Mathematics 2022-11-04 Xiaoyue Li , Qianlin Ma , Hongfu Yang , Chenggui Yuan

This note, mostly expository, is devoted to Poincar{\'e} and log-Sobolev inequalities for a class of Boltzmann-Gibbs measures with singular interaction. Such measures allow to model one-dimensional particles with confinement and singular…

Probability · Mathematics 2020-09-02 Djalil Chafai , Joseph Lehec

This article develops general conditions for weak convergence of adaptive Markov chain Monte Carlo processes and is shown to imply a weak law of large numbers for bounded Lipschitz continuous functions. This allows an estimation theory for…

Statistics Theory · Mathematics 2026-01-14 Austin Brown , Jeffrey S. Rosenthal

We obtain moment and Gaussian bounds for general Lipschitz functions evaluated along the sample path of a Markov chain. We treat Markov chains on general (possibly unbounded) state spaces via a coupling method. If the first moment of the…

Probability · Mathematics 2010-12-08 J. -R. Chazottes , F. Redig

We study the mixing time of two popular discrete-time Markov chains in continuous space, the Unadjusted Langevin Algorithm and the Proximal Sampler, which are discretizations of the Langevin dynamics. We extend mixing time analyses for…

Statistics Theory · Mathematics 2025-02-13 Siddharth Mitra , Andre Wibisono

Extending a result of Caffarelli, we provide global Lipschitz changes of variables between compactly supported perturbations of log-concave measures. The result is based on a combination of ideas from optimal transportation theory and a new…

Analysis of PDEs · Mathematics 2015-10-14 Maria Colombo , Alessio Figalli , Yash Jhaveri

The mixing time of Markovian dissipative evolutions of open quantum many-body systems can be bounded using optimal constants of certain quantum functional inequalities, such as the modified logarithmic Sobolev constant. For classical spin…

Quantum Physics · Physics 2021-08-03 Ivan Bardet , Angela Capel , Angelo Lucia , David Pérez-García , Cambyse Rouzé

Through a Metropolis-like algorithm with single step computational cost of order one, we build a Markov chain that relaxes to the canonical Fermi statistics for k non-interacting particles among m energy levels. Uniformly over the…

Probability · Mathematics 2015-05-14 Alexandre Gaudilliere , Julien Reygner

A key task in Bayesian statistics is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). However, without any assumptions, sampling (even approximately) can be #P-hard, and few…

Machine Learning · Computer Science 2018-12-03 Rong Ge , Holden Lee , Andrej Risteski

We prove strong hypercontractivity (SHC) inequalities for logarithmically subharmonic functions on $\RR^n$ and different classes of measures: Gaussian measures on $\RR^n$, symmetric Bernoulli and symmetric uniform probability measures on…

Functional Analysis · Mathematics 2008-10-20 Piotr Graczyk , Todd Kemp , Jean-Jacques Loeb , Tomasz Zak

We analyze the global convergence of the power iterates for the computation of a general mixed-subordinate matrix norm. We prove a new global convergence theorem for a class of entrywise nonnegative matrices that generalizes and improves a…

Numerical Analysis · Mathematics 2020-02-07 Antoine Gautier , Matthias Hein , Francesco Tudisco

This paper is devoted to various applications of Hardy-Sobolev type inequalities. We derive a new $L^2$ estimate for the $\bar{\partial}-$equation on ${\mathbb C}^n$ which yields a quantitative generalization of the Hartogs extension…

Complex Variables · Mathematics 2018-02-01 Bo-Yong Chen

Using a non-negative curvature condition, we prove the complete version of modified log-Sobolev inequalities for central Markov semigroups on various compact quantum groups, including group von Neumann algebras, free orthogonal group and…

Operator Algebras · Mathematics 2020-08-28 Michael Brannan , Li Gao , Marius Junge

We introduce a variational first-order Sobolev calculus on metric measure spacetimes. The key object is the maximal weak subslope of an arbitrary causal function, which plays the role of the (Lorentzian) modulus of its differential. It is…

Differential Geometry · Mathematics 2025-03-21 Tobias Beran , Mathias Braun , Matteo Calisti , Nicola Gigli , Robert J. McCann , Argam Ohanyan , Felix Rott , Clemens Sämann

In this article, we close a gap in the literature by proving existence of invariant measures for reflected SPDEs with only one reflecting barrier. This is done by arguing that the sequence (u(t, .)) is tight in the space of probability…

Probability · Mathematics 2019-04-15 Jasdeep Kalsi

We consider the problem of sampling a multimodal distribution with a Markov chain given a small number of samples from the stationary measure. Although mixing can be arbitrarily slow, we show that if the Markov chain has a $k$th order…

Machine Learning · Computer Science 2024-11-15 Frederic Koehler , Holden Lee , Thuy-Duong Vuong