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We revisit the problem of sampling from a target distribution that has a smooth strongly log-concave density everywhere in $\mathbb R^p$. In this context, if no additional density information is available, the randomized midpoint…

Statistics Theory · Mathematics 2023-06-19 Lu Yu , Avetik Karagulyan , Arnak Dalalyan

Density dependent families of Markov chains, such as the stochastic models of mass-action chemical kinetics, converge for large values of the indexing parameter $N$ to deterministic systems of differential equations (Kurtz, 1970). Moreover…

Probability · Mathematics 2017-07-11 Enrico Bibbona , Roberta Sirovich

Consider a filtering process associated to a hidden Markov model with densities for which both the state space and the observation space are complete, separable, metric spaces. If the underlying, hidden Markov chain is strongly ergodic and…

Probability · Mathematics 2016-06-03 Thomas Kaijser

We analyze circumstances under which the microscopic dynamics of particles which are driven by a forced, gradient-type flow can be consistently interpreted as a Markovian diffusion process. Special attention is paid to discriminating…

Condensed Matter · Physics 2007-05-23 P. Garbaczewski

Let $\sigma(u)$, $u\in \mathbb{R}$ be an ergodic stationary Markov chain, taking a finite number of values $a_1,...,a_m$, and $b(u)=g(\sigma(u))$, where $g$ is a bounded and measurable function. We consider the diffusion type process $$…

Probability · Mathematics 2011-08-24 P. Chigansky , R. Liptser

We study the convergence and divergence of the wavelet expansion of a function in a Sobolev or a Besov space from a multifractal point of view. In particular, we give an upper bound for the Hausdorff and for the packing dimension of the set…

Functional Analysis · Mathematics 2019-03-13 Frédéric Bayart

We consider overdamped Langevin diffusions in Euclidean space, with curvature equal to the spectral gap. This includes the Ornstein-Uhlenbeck process as well as non-Gaussian and non-product extensions with convex interaction, such as the…

Probability · Mathematics 2026-03-25 Djalil Chafaï , Max Fathi

Let $M$ be a connected compact Riemannian manifold possibly with a boundary, let $V\in C^2(M)$ such that $\mu(\d x):=\e^{V(x)}\d x$ is a probability measure, where $\d x$ is the volume measure, and let $L=\Delta+\nabla V$. The exact…

Probability · Mathematics 2021-07-27 Feng-Yu Wang , Bingyao Wu

Starting from a sequence of independent Wright-Fisher diffusion processes on $[0,1]$, we construct a class of reversible infinite dimensional diffusion processes on $\DD_\infty:= \{{\bf x}\in [0,1]^\N: \sum_{i\ge 1} x_i=1\}$ with GEM…

Probability · Mathematics 2007-11-14 Shui Feng , Feng-Yu Wang

We find explicit upper bounds for the density of marginals of continuous diffusions where we assume that the diffusion coefficient is constant and the drift is solely assumed to be progressively measurable and locally bounded. In one…

Probability · Mathematics 2024-10-16 Paul Krühner , Shijie Xu

The Lauricella theory of multiple hypergeometric functions is used to shed some light on certain distributional properties of the mean of a Dirichlet process. This approach leads to several results, which are illustrated here. Among these…

Probability · Mathematics 2016-09-07 Antonio Lijoi , Eugenio Regazzini

Density dependent Markov population processes in large populations of size $N$ were shown by Kurtz (1970, 1971) to be well approximated over finite time intervals by the solution of the differential equations that describe their average…

Probability · Mathematics 2014-10-15 A. D. Barbour , Kais Hamza , Haya Kaspi , Fima Klebaner

A superconductive model characterized by a third order parabolic operator L" is analysed. When the viscous terms, represented by higher - order deriva- tives, tend to zero, a hyperbolic operator L0 appears. Furthermore, if P" is the…

Superconductivity · Physics 2012-11-08 M. de Angelis , G. Fiore

We study the problem of exponential mixing and large deviations for discrete-time Markov processes associated with a class of random dynamical systems. Under some dissipativity and regularisation hypotheses for the underlying deterministic…

Analysis of PDEs · Mathematics 2014-10-24 Vojkan Jaksic , Vahagn Nersesyan , Claude-Alain Pillet , Armen Shirikyan

We derive the Markov process equivalent to She-Leveque scaling in homogeneous and isotropic turbulence. The Markov process is a jump process for velocity increments $u(r)$ in scale $r$ in which the jumps occur randomly but with…

Statistical Mechanics · Physics 2017-08-14 Daniel Nickelsen

We construct a new class of infinite-dimensional diffusions taking values in a generalized Kingman simplex. Our model describes the temporal evolution of the relative frequencies of infinitely-many types which are "labeled" by an arbitrary…

Probability · Mathematics 2026-02-25 Cristina Costantini , Matteo Ruggiero

We provide an explicit rigorous derivation of a diffusion limit - a stochastic differential equation with additive noise - from a deterministic skew-product flow. This flow is assumed to exhibit time-scale separation and has the form of a…

Dynamical Systems · Mathematics 2015-05-27 I. Melbourne , A. M. Stuart

We consider a two species process which evolves in a finite or infinite domain in contact with particles reservoirs at different densities, according to the superposition of a generalised contact process and a rapid-stirring dynamics in the…

Probability · Mathematics 2016-11-04 Kevin Kuoch , Mustapha Mourragui , Ellen Saada

The paper studies a higher-order diffusion model of Maxwell-Stefan kind. The model is based upon higher-order moment equations of kinetic theory of mixtures, which include viscous dissipation in the model. Governing equations are analyzed…

Analysis of PDEs · Mathematics 2023-05-16 Bérénice Grec , Srboljub Simic

Let $D\subset R^d$ be a bounded domain and denote by $\mathcal P(D)$ the space of probability measures on $D$. Let \begin{equation*} L=\frac12\nabla\cdot a\nabla +b\nabla \end{equation*} be a second order elliptic operator. Let…

Probability · Mathematics 2011-05-19 Ross G. Pinsky
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