17,240 research outputs found
Weak order for the discretization of the stochastic heat equation driven by impulsive noise
Considering a linear parabolic stochastic partial differential equation
driven by impulsive space time noise, dX_t+AX_t dt= Q^{1/2}dZ_t, X_0=x_0\in H,
t\in [0,T], we approximate the distribution of X_T. (Z_t)_{t\in[0,T]} is an
impulsive cylindrical process and Q describes the spatial covariance structure
of the noise; Tr(A^{-\alpha})0 and A^\beta Q is bounded
for some \beta\in(\alpha-1,\alpha]. A discretization
(X_h^n)_{n\in\{0,1,...,N\}} is defined via the finite element method in space
(parameter h>0) and a \theta-method in time (parameter \Delta t=T/N). For
\phi\in C^2_b(H;R) we show an integral representation for the error
|E\phi(X^N_h)-E\phi(X_T)| and prove that
|E\phi(X^N_h)-E\phi(X_T)|=O(h^{2\gamma}+(\Delta t)^{\gamma}) where
\gamma<1-\alpha+\beta.Comment: 29 pages; Section 1 extended, new results in Appendix
Regularity of Ornstein-Uhlenbeck processes driven by a L{\'e}vy white noise
The paper is concerned with spatial and time regularity of solutions to
linear stochastic evolution equation perturbed by L\'evy white noise "obtained
by subordination of a Gaussian white noise". Sufficient conditions for spatial
continuity are derived. It is also shown that solutions do not have in general
\cadlag modifications. General results are applied to equations with fractional
Laplacian. Applications to Burgers stochastic equations are considered as well.Comment: This is an updated version of the same paper. In fact, it has already
been publishe
Markovian nature, completeness, regularity and correlation properties of Generalized Poisson-Kac processes
We analyze some basic issues associated with Generalized Poisson-Kac (GPK)
stochastic processes, starting from the extended notion of the Markovian
condition. The extended Markovian nature of GPK processes is established, and
the implications of this property derived: the associated adjoint formalism for
GPK processes is developed essentially in an analogous way as for the
Fokker-Planck operator associated with Langevin equations driven by Wiener
processes. Subsequently, the regularity of trajectories is addressed: the
occurrence of fractality in the realizations of GPK is a long-term emergent
property, and its implication in thermodynamics is discussed. The concept of
completeness in the stochastic description of GPK is also introduced. Finally,
some observations on the role of correlation properties of noise sources and
their influence on the dynamic properties of transport phenomena are addressed,
using a Wiener model for comparison
Field-theoretic methods
Many complex systems are characterized by intriguing spatio-temporal
structures. Their mathematical description relies on the analysis of
appropriate correlation functions. Functional integral techniques provide a
unifying formalism that facilitates the computation of such correlation
functions and moments, and furthermore allows a systematic development of
perturbation expansions and other useful approximative schemes. It is explained
how nonlinear stochastic processes may be mapped onto exponential probability
distributions, whose weights are determined by continuum field theory actions.
Such mappings are madeexplicit for (1) stochastic interacting particle systems
whose kinetics is defined through a microscopic master equation; and (2)
nonlinear Langevin stochastic differential equations which provide a mesoscopic
description wherein a separation of time scales between the relevant degrees of
freedom and background statistical noise is assumed. Several well-studied
examples are introduced to illustrate the general methodology.Comment: Article for the Encyclopedia of Complexity and System Science, B.
Meyers (Ed.), Springer-Verlag Berlin, 200
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