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A backward particle interpretation of Feynman-Kac formulae

Pierre Del Moral, Arnaud Doucet, Sumeetpal S. Singh (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals “on-the-fly” as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We...

A dynamical system in a Hilbert space with a weakly attractive nonstationary point

Ivo Vrkoč (1993)

Mathematica Bohemica

A differential equation is a Hilbert space with all solutions bounded but with so finite nontrivial invariant measure is constructed. In fact, it is shown that all solutions to this equation converge weakly to the origin, nonetheless, there is no stationary point. Moreover, so solution has a non-empty Ω -set.

A free stochastic partial differential equation

Yoann Dabrowski (2014)

Annales de l'I.H.P. Probabilités et statistiques

We get stationary solutions of a free stochastic partial differential equation. As an application, we prove equality of non-microstate and microstate free entropy dimensions under a Lipschitz like condition on conjugate variables, assuming also the von Neumann algebra R ω embeddable. This includes an N -tuple of q -Gaussian random variables e.g. for | q | N 0 . 13 .

A growth estimate for continuous random fields

Ralf Manthey, Katrin Mittmann (1996)

Mathematica Bohemica

We prove a polynomial growth estimate for random fields satisfying the Kolmogorov continuity test. As an application we are able to estimate the growth of the solution to the Cauchy problem for a stochastic diffusion equation.

A logarithmic Sobolev form of the Li-Yau parabolic inequality.

Dominique Bakry, Michel Ledoux (2006)

Revista Matemática Iberoamericana

We present a finite dimensional version of the logarithmic Sobolev inequality for heat kernel measures of non-negatively curved diffusion operators that contains and improves upon the Li-Yau parabolic inequality. This new inequality is of interest already in Euclidean space for the standard Gaussian measure. The result may also be seen as an extended version of the semigroup commutation properties under curvature conditions. It may be applied to reach optimal Euclidean logarithmic Sobolev inequalities...

A Markov property for two parameter Gaussian processes.

David Nualart Rodón, M. Sanz (1979)


This paper deals with the relationship between two-dimensional parameter Gaussian random fields verifying a particular Markov property and the solutions of stochastic differential equations. In the non Gaussian case some diffusion conditions are introduced, obtaining a backward equation for the evolution of transition probability functions.

A multidimensional singular stochastic control problem on a finite time horizon

Marcin Boryc, Łukasz Kruk (2015)

Annales UMCS, Mathematica

A singular stochastic control problem in n dimensions with timedependent coefficients on a finite time horizon is considered. We show that the value function for this problem is a generalized solution of the corresponding HJB equation with locally bounded second derivatives with respect to the space variables and the first derivative with respect to time. Moreover, we prove that an optimal control exists and is unique

A note on maximal estimates for stochastic convolutions

Mark Veraar, Lutz Weis (2011)

Czechoslovak Mathematical Journal

In stochastic partial differential equations it is important to have pathwise regularity properties of stochastic convolutions. In this note we present a new sufficient condition for the pathwise continuity of stochastic convolutions in Banach spaces.

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