Systems of equations driven by stable processes

Let Z^j_t, j = 1, . . . , d, be independent one-dimensional symmetric stable processes of index α ∈ (0,2). We consider the system of stochastic differential equations where the matrix A(x)=(A_ij(x))1≤ i, j ≤ d is continuous and bounded in x and nondegenerate for each x. We prove existence and uniqueness of a weak solution to this system. The approach of this paper uses the martingale problem method. For this, we establish some estimates for pseudodifferential operators with singular state-dependent symbols. Let λ₂ > λ₁ > 0. We show that for any two vectors a, b∈ ℝ_d with |a|, |b| ∈ (λ₁, λ₂) and p sufficiently large, the L^p-norm of the operator whose Fourier multiplier is (|u · a|^α - |u · b|^α) / ∑_j=1^d |u_i|^α is bounded by a constant multiple of |a−b|^θ for some θ > 0, where u=(u₁ , . . . , u_d) ∈ ℝ^d. We deduce from this the L^p-boundedness of pseudodifferential operators with symbols of the form ψ(x,u)=|u · a(x)|^α / ∑_j=1^d |u_i|^α, where u=(u₁,...,u_d) and a is a continuous function on ℝ^d with |a(x)|∈ (λ₁, λ₂) for all x∈ ℝ^d. Research partially supported by NSF grant DMS-0244737. Research partially supported by NSF grant DMS-0303310.     

Gradient estimates and coupling property for semilinear SDEs driven by jump processes

Let L be a L′evy process with characteristic measureν,which has an absolutely continuous lower bound w.r.t.the Lebesgue measure on Rn.By using Malliavin calculus for jump processes,we investigate Bismut formula,gradient estimates and coupling property for the semigroups associated to semilinear SDEs forced by L′evy process L.     

On one-dimensional stochastic differential equations driven by stable processes

We consider the one-dimensional stochastic differential equation dX _t=b(t, X_t−) dZ _t, whereZ is a symmetric α-stable Lévy process with α ε (1, 2] andb is a Borel function. We give sufficient conditions under which the equation has a weak nonexploding solution. Partially supported by Programma Professori Visitatori of G. N. A. F. A. (Italy). Partially supported by MURST (Italy). The present research was completed while the second author was visiting the Institute of Mathematics and Informatics (Vilnius, Lithuania) in spring of 1999. Translated from Lietuvos Matematikos Rinkinys, Vol. 40, No. 3, pp. 361–385, July–September, 2000. Translated by H. Pragarauskas     

The high-order SPDEs driven by multi-parameter fractional noises

The existence and uniqueness of the solutions are proved for a class of fourth-order stochastic heat equations driven by multi-parameter fractional noises. Furthermore the regularity of the solutions is studied for the stochastic equations and the existence of the density of the law of the solution is obtained.     

Strong convergence of a stochastic Rosenbrock-type scheme for the finite element discretization of semilinear SPDEs driven by multiplicative and additive noise

This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the nonlinear part is stronger than the linear part, usually called stochastic dominated transport equations. Most standard numerical schemes lose their good stability properties on such equations, including the current linear implicit Euler method. We discretize the SPDE in space by the finite element method and propose a novel scheme called stochastic Rosenbrock-type scheme for temporal discretization. Our scheme is based on the local linearization of the semi-discrete problem obtained after space discretization and is more appropriate for such equations. We provide a strong convergence of the new fully discrete scheme toward the exact solution for multiplicative and additive noise and obtain optimal rates of convergence. Numerical experiments to sustain our theoretical results are provided.     

Trajectory fitting estimators for SPDEs driven by additive noise

In this paper we study the problem of estimating the drift/viscosity coefficient for a large class of linear, parabolic stochastic partial differential equations (SPDEs) driven by an additive space-time noise. We propose a new class of estimators, called trajectory fitting estimators (TFEs). The estimators are constructed by fitting the observed trajectory with an artificial one, and can be viewed as an analog to the classical least squares estimators from the time-series analysis. As in the existing literature on statistical inference for SPDEs, we take a spectral approach, and assume that we observe the first N Fourier modes of the solution, and we study the consistency and the asymptotic normality of the TFE, as \(N\rightarrow \infty \).     

Ergodic properties of stationary stable processes

We derive spectral necessary and sufficient conditions for stationary symmetric stable processes to be metrically transitive and mixing. We then consider some important classes of stationary stable processes: Sub-Gaussian stationary processes and stationary stable processes with a harmonic spectral representation are never metrically transitive, the latter in sharp contrast with the Gaussian case. Stable processes with a harmonic spectral representation satisfy a strong law of large numbers even though they are not generally stationary. For doubly stationary stable processes, sufficient conditions are derived for metric transitivity and mixing, and necessary and sufficient conditions for a strong law of large numbers.     

Asymptotic properties of solutions of semilinear second-order elliptic equations in cylindrical domains

The equations under consideration have the following structure:

Estimates of blow‐up times of a system of semilinear SPDEs

In this paper, blow‐up property to a system of nonlinear stochastic PDEs driven by two‐dimensional Brownian motions is investigated. The lower and upper bounds for blow‐up times are obtained. When the system parameters satisfy certain conditions, the explicit solutions of a related system of random PDEs are deduced, which allows us to use Yor's formula to obtain the distribution functions of several blow‐up times. Particularly, the impact of noises on the life span of solutions is studied as the system parameters satisfy different conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

Sample function properties of multi-parameter stable processes

Summary The almost sure behaviour of the sample functions of the vectorvalued N-parameter Wiener process and its stable analogues is investigated, especially their small fluctuations. In particular, laws of the simple and of the iterated logarithm are established for the supremum of the local time increments or sojourn times. These results give precise information about the minimum oscillation of the sample functions. In addition, the Hausdorff measure problem for the graph and the range of these processes is solved.The preparation of this work was supported by the Deutsche Forschungsgemeinschaft.     

SPDEs driven by Poisson random measure with non Lipschitz coefficients: existence results

The article deals with SPDEs driven by Poisson random measure with non Lipschitz coefficients. Let A:E→E be a generator of an analytic semigroup on E, E being a certain Banach space. Let be a stochastic basis carrying an E-valued Poisson random measure η with characteristic measure ν and compensator γ. Let 1≤p≤2. Our point of interest is the existence of solutions to SPDE's of e.g.the following type where g:E→L(E,E ₀) is some mapping satisfying ∫ _E |g(x,z)−g(y,z)| ^p ν(dz)≤C|x−y| ^rp , x,y ∈ E, where 0<r<1 satisfy certain condition specified later and is again a certain Banach space. This work was supported by the Austrian Academy of Science, APART 700 and FWF-Project P17273-N12     

Equivalence of laws and null controllability for SPDEs driven by a fractional Brownian motion

We obtain necessary and sufficient conditions for equivalence of law for linear stochastic evolution equations driven by a general Gaussian noise by identifying the suitable space of controls for the corresponding deterministic control problem. This result is applied to semilinear (reaction-diffusion) equations driven by a fractional Brownian motion. We establish the equivalence of continuous dependence of laws of solutions to semilinear equations on the initial datum in the topology of pointwise convergence of measures and null controllability for the corresponding deterministic control problem.     

Structural properties of periodic stochastic processes

We study imbeddings of spaces of periodic stochastic processes Lpr. This permits us to obtain conditions for smoothness of trajectories of a process in terms of the modulus of continuity.Translated from Statisticheskie Metody Otsenivaniya i Proverki Gipotez, pp. 154–159, 1988.     

Approximate controllability of semilinear measure driven systems

This paper investigates approximate controllability of semilinear measure driven equations in Hilbert spaces. By using the semigroup theory and Schauder fixed point theorem, sufficient conditions for approximate controllability of measure driven equations are established. The obtained results are a generalization and continuation of the recent results on this issue. Finally, an example is provided to illustrate the application of the obtained results.     

Sample path properties of processes with stable components

Summary In this paper, processes in R ^d of the form X(t)=(X ₁ (t), X ₂ (t), , X _N (t), where X _i (t) is a stable process of index _i in Euclidean space of dimension d _i and d=d ₁ + + d _N , are considered. The asymptotic behaviour of the first passage time out of a sphere, and of the sojourn time in a sphere is established. Properties of the space-time process (X ₁ (t), t) in R ^d+1 are obtained when X ₁ (t) is a stable process in R ^d . For each of these processes, a Hausdorff measure function (h) is found such that the range set R(s) of the sample path on [0, s] has Hausdorff -measure c s for a suitable finite positive c.During the preparation of this paper, the first author was supported in part by N. S. F. Grant No GP-3906.     

Stochastic Volterra equations driven by cylindrical Wiener process

In this paper, stochastic Volterra equations driven by cylindrical Wiener process in Hilbert space are investigated. Sufficient conditions for existence of strong solutions are given. The key role is played by convergence of α-times resolvent families. Both authors are supported partially by project “Proyecto Anillo: Laboratorio de Analisis Estocastico; ANESTOC”.     

Backward SDEs driven by Gaussian processes

In this paper we discuss existence and uniqueness results for BSDEs driven by centered Gaussian processes. Compared to the existing literature on Gaussian BSDEs, which mainly treats fractional Brownian motion with Hurst parameter H>1/2$H>1/2$, our main contributions are: (i) Our results cover a wide class of Gaussian processes as driving processes including fractional Brownian motion with arbitrary Hurst parameter H∈(0,1)$H\in (0,1)$; (ii) the assumptions on the generator f$f$ are mild and include e.g. the case when f$f$ has (super-)quadratic growth in z$z$; (iii) the proofs are based on transferring the problem to an auxiliary BSDE driven by a Brownian motion.     

Delay differential equations driven by Lévy processes: Stationarity and Feller properties

We consider a stochastic delay differential equation driven by a general Lévy process. Both the drift and the noise term may depend on the past, but only the drift term is assumed to be linear. We show that the segment process is eventually Feller, but in general not eventually strong Feller on the Skorokhod space. The existence of an invariant measure is shown by proving tightness of the segments using semimartingale characteristics and the Krylov–Bogoliubov method. A counterexample shows that the stationary solution in completely general situations may not be unique, but in more specific cases uniqueness is established.     

On a semilinear double fractional heat equation driven by fractional Brownian sheet

In this paper, we consider the stochastic heat equation of the form $$\frac{\partial u}{\partial t}=(\Delta_\alpha+\Delta_\beta)u+\frac{\partial f}{\partial x}(t,x,u)+\frac{\partial^2W}{\partial t\partial x},$$ where $1<\beta<\alpha< 2$, $W(t,x)$ is a fractional Brownian sheet, $\Delta_\theta:=-(-\Delta)^{\theta/2}$ denotes the fractional Lapalacian operator and $f:[0,T]\times \mathbb{R}\times \mathbb{R}\rightarrow\mathbb{R}$ is a nonlinear measurable function. We introduce the existence, uniqueness and H\"older regularity of the solution. As a related question, we consider also a large deviation principle associated with the above equation with a small perturbation via an equivalence relationship between Laplace principle and large deviation principle.