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We prove a general inequality on $\beta$-mixing coefficients of point processes depending uniquely on their $n$-th order intensity functions. We apply this inequality in the case of determinantal point processes and show that the rate of…

Statistics Theory · Mathematics 2020-09-01 Arnaud Poinas

Fleming's inequality is generalized to the decay function of mixed states. We show that for any symmetric hamiltonian $h$ and for any density operator $\rho$ on a finite dimensional Hilbert space with the orthogonal projection $\Pi$ onto…

Quantum Physics · Physics 2010-11-15 Florian Fröwis , Gebhard Grübl , Markus Penz

Over the past decades, a fascinating computational phase transition has been identified in sampling from Gibbs distributions. Though, the computational complexity at the critical point remains poorly understood, as previous algorithmic and…

Data Structures and Algorithms · Computer Science 2026-01-08 Xiaoyu Chen , Zongchen Chen , Yitong Yin , Xinyuan Zhang

Gibbs random fields corresponding to systems of real-valued spins (e.g. systems of interacting anharmonic oscillators) indexed by the vertices of unbounded degree graphs with a certain summability property are constructed. It is proven that…

Probability · Mathematics 2009-04-22 Yuri Kondratiev , Yuri Kozitsky , Tanja Pasurek

The influence of the tail features of the local magnetic field probability density function (PDF) on the ferromagnetic Ising model is studied in the limit of infinite range interactions. Specifically, we assign a quenched random field whose…

Statistical Mechanics · Physics 2009-07-30 Silvio M. Duarte Queiros , Nuno Crokidakis , Diogo O. Soares-Pinto

We show a strict hierarchy among various edge and vertex expansion properties of Markov chains. This gives easy proofs of a range of bounds, both classical and new, on chi-square distance, spectral gap and mixing time. The 2-gradient is…

Probability · Mathematics 2009-04-03 Ravi Montenegro

For a general attractive Probabilistic Cellular Automata on S Z d , we prove that the (time-) convergence towards equilibrium of this Markovian parallel dynamics, exponentially fast in the uniform norm, is equivalent to a condition (A).…

Probability · Mathematics 2016-04-27 Pierre-Yves Louis

We study the metastable states in Ising spin models with orthogonal interaction matrices. We focus on three realizations of this model, the random case and two non-random cases, i.e.\ the fully-frustrated model on an infinite dimensional…

Condensed Matter · Physics 2009-10-28 Giorgio Parisi , Marc Potters

We study the ferromagnetic random field Ising model (RFIM) on a graph $G=(V,E)$ having maximal degree $\Delta$, where the external field at each vertex is an i.i.d. random variable. When the random field distribution is sufficiently…

Probability · Mathematics 2026-05-05 Yi Han

In this paper we consider the problem of sampling from the low-temperature exponential random graph model (ERGM). The usual approach is via Markov chain Monte Carlo, but Bhamidi et al. showed that any local Markov chain suffers from an…

Probability · Mathematics 2022-10-05 Guy Bresler , Dheeraj Nagaraj , Eshaan Nichani

We study stochastic partial differential equations of the reaction-diffusion type. We show that, even if the forcing is very degenerate (i.e. has not full rank), one has exponential convergence towards the invariant measure. The convergence…

Mathematical Physics · Physics 2009-11-07 Martin Hairer

In this work we prove sufficient conditions for the Glauber dynamics corresponding to a sequence of (non-product) measures on finite product spaces to be rapidly mixing, i.e. that the mixing time with respect to the total variation distance…

Probability · Mathematics 2019-02-27 Arthur Sinulis

We prove that a sum of random matrices generated by a $\psi$-mixing Markov chain has similar spectral properties to a Gaussian matrix with the same mean and covariance structure. This nonasymptotic universality principle enables sharp…

Probability · Mathematics 2026-04-29 Alexander Van Werde , Jaron Sanders

We present several results on the mixing time of the Glauber dynamics for sampling from the Gibbs distribution in the ferromagnetic Potts model. At a fixed temperature and interaction strength, we study the interplay between the maximum…

Discrete Mathematics · Computer Science 2014-06-06 Magnus Bordewich , Catherine Greenhill , Viresh Patel

We prove the convergence at an exponential rate towards the invariant probability measure for a class of solutions of stochastic differential equations with finite delay. This is done, in this non-Markovian setting, using the cluster…

Probability · Mathematics 2016-07-11 Laure Pédèches

In this note we discuss limit distribution of normalized return times for shrinking targets and draw a necessary and sufficient condition using sweep-out sequence in order for the limit distribution to be exponential with parameter $1$. The…

Dynamical Systems · Mathematics 2020-10-30 Xuan Zhang

The finite lattice method of series expansion is generalised to the $q$-state Potts model on the simple cubic lattice. It is found that the computational effort grows exponentially with the square of the number of series terms obtained,…

High Energy Physics - Lattice · Physics 2011-07-19 A J Guttmann , I G Enting

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2015-11-06 Loïc Hervé , James Ledoux

We consider the Potts model with $q$ colors on a sequence of weighted graphs with adjacency matrices $A_n$, allowing for both positive and negative weights. Under a mild regularity condition the mean-field prediction for the log partition…

Probability · Mathematics 2016-05-06 Anirban Basak , Sumit Mukherjee

We prove that the marginal densities of a global probability mass function in a primal normal factor graph and the corresponding marginal densities in the dual normal factor graph are related via local mappings. The mapping depends on the…

Machine Learning · Statistics 2020-07-15 Mehdi Molkaraie
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