Group-Theoretic Dimension of Stationary Symmetric α-Stable Random Fields

The growth rate of the partial maximum of a stationary stable process was first studied in the works of Samorodnitsky (Ann. Probab. 32:1438–1468, 2004; Adv. Appl. Probab. 36:805–823, 2004), where it was established, based on the seminal works of Rosiński (Ann. Probab. 23:1163–1187, 1995; 28:1797–1813, 2000), that the growth rate is connected to the ergodic-theoretic properties of the flow that generates the process. The results were generalized to the case of stable random fields indexed by ? ^d in Roy and Samorodnitsky (J. Theor. Probab. 21:212–233, 2008), where properties of the group of nonsingular transformations generating the stable process were studied as an attempt to understand the growth rate of the partial maximum process. This work generalizes this connection between stable random fields and group theory to the continuous parameter case, that is, to fields indexed by ? ^d .     

Reflected and Doubly Reflected BSDEs for Levy Processes： Solutions and Comparison

In this paper we study reflected and doubly reflected backward stochastic differential equations （BSDEs, for short） driven by Teugels martingales associated with L~vy process satisfying some moment condi- tions and by an independent Brownian motion. For BSDEs with one reflecting barrier, we obtain a comparison theorem using the Tanaka-Meyer formula. For BSDEs with two reflecting barriers, we first prove the existence and uniqueness of the solutions under the Mokobodski＇s condition by using the Snell envelope theory and then we obtain a comparison result.     

Variational Formula for Dirichlet Forms and Estimates of Principal Eigenvalues for Symmetric α-stable Processes

In this paper, we prove a variational formula for Dirichlet forms generated by general symmetric Markov processes. As its applications, we obtain lower bound estimates of the bottom of spectrum for symmetric Markov processes. Moreover, for a positive measure charging no set of zero capacity, we give a new proof of an L²()-estimate of functions in Dirichlet spaces. Finally, we calculate the principal eigenvalues for absorbing and time changed -stable processes and obtain conditions for some measures being gaugeable. Mathematics Subject Classifications (2000) Primary 31C25; Secondary 34L15, 60G52.     

Pathwise Uniqueness for a Class of SPDEs Driven by Cylindrical α-Stable Processes

Potential Analysis - By studying the infinite dimensional Kolmogorov equation with non-local operator, we show the pathwise uniqueness for stochastic partial differential equation driven by...     

Ergodicity of the Finite and Infinite Dimensional α-Stable Systems

Abstract

Some finite and infinite dimensional perturbed α-stable dynamics are constructed and studied in this article. We prove that the finite dimensional system is strongly mixing, while in the infinite dimensional case that the functional coercive inequalities are not available, we develop and apply a technique to prove the point-wise ergodicity for systems with sufficiently small interaction in a large subspace of Ω = R ^{Z d} .     

Maximal Inequalities for Fractional Lévy and Related Processes

In this article we study processes that are constructed by a convolution of a deterministic kernel with a martingale. A special emphasis is put on the case where the driving martingale is a centred Lévy process, which covers the popular class of fractional Lévy processes. As a main result we show that, under appropriate assumptions on the kernel and the martingale, the maximum process of the corresponding “convoluted martingale” is p-integrable and we derive maximal inequalities in terms of the kernel and of the moments of the driving martingale.     

Multivariate Normal α-Stable Exponential Families

Mediterranean Journal of Mathematics - The normal inverse Gaussian distributions are used to introduce the class of multivariate normal α-stable distributions. Some fundamental properties of...     

Higher Order Terms of the Spectral Heat Content for Killed Subordinate and Subordinate Killed Brownian Motions Related to Symmetric α-Stable Processes in ℝ ${mathbb {R}}$

Potential Analysis - We investigate the 3rd term of the spectral heat content for killed subordinate and subordinate killed Brownian motions on a bounded open interval D = (a,b) in a real line when...     

Reflected Generalized Backward Doubly SDEs Driven by Lévy Processes and Applications

In this paper, we study reflected generalized backward doubly stochastic differential equations driven by Teugels martingales associated with Lévy process (RGBDSDELs in short) with one continuous barrier. Under uniformly Lipschitz coefficients, we prove an existence and uniqueness result by means of the penalization method and the fixed-point theorem. As an application, this study allows us to give a probabilistic representation for the solutions to a class of reflected stochastic partial differential integral equations (SPDIEs in short) with a nonlinear Neumann boundary condition.     

α-Transience and α-Recurrence of Right Processes

In this article, we mainly discuss some potential theory in the framework of right Markov processes. We introduce the concept of α-excessive function, α-recurrence and α-transience for right processes with α ≤ 0, and give a thorough investigation.     

Hitting Times of Points and Intervals for Symmetric Lévy Processes

For one-dimensional symmetric Lévy processes, which hit every point with positive probability, we give sharp bounds for the tail function P ^x (T _B >t), where T _B is the first hitting time of B which is either a single point or an interval. The estimates are obtained under some weak type scaling assumptions on the characteristic exponent of the process. We apply these results to prove sharp two-sided estimates of the transition density of the process killed after hitting B.     

Finite Variation of Fractional Lévy Processes

Various characterizations for fractional Lévy processes to be of finite variation are obtained, one of which is in terms of the characteristic triplet of the driving Lévy process, while others are in terms of differentiability properties of the sample paths. A zero-one law and a formula for the expected total variation are also given.     

Complex Dirichlet Forms: Non Symmetric Diffusion Processes and Schrödinger Operators

The concept of complex Dirichlet forms ^c resp. operators L _c in complex weighted L ²-spaces is introduced. Perturbations of classical Dirichlet forms by forms associated with complex first-order differential operators provide examples of complex Dirichlet forms.Complex Dirichlet operators L _c are unitarily equivalent with (a family of) Schrödinger operators with electromagnetic potentials.To ^c there is associated a pair of real-valued non symmetric Dirichlet forms on the corresponding real weighted L ²-spaces, which in turn are associated with (non-symmetric) diffusion processes.Results by Stannat on non symmetric Dirichlet forms and their perturbations can be used for discussing the essential self-adjointness of L _c .New closability criteria for (perturbation of) non symmetric Dirichlet forms are obtained.     

Space–Time Fractional Equations and the Related Stable Processes at Random Time

In this paper, we consider the general space–time fractional equation of the form \(\sum _{j=1}^m \lambda _j \frac{\partial ^{\nu _j}}{\partial t^{\nu _j}} w(x_1, \ldots , x_n ; t) = -c^2 \left( -\varDelta \right) ^\beta w(x_1, \ldots , x_n ; t)\), for \(\nu _j \in \left( 0,1 \right] \) and \(\beta \in \left( 0,1 \right] \) with initial condition \(w(x_1, \ldots , x_n ; 0)= \prod _{j=1}^n \delta (x_j)\). We show that the solution of the Cauchy problem above coincides with the probability density of the n-dimensional vector process \(\varvec{S}_n^{2\beta } \left( c^2 \mathcal {L}^{\nu _1, \ldots , \nu _m} (t) \right) \), \(t>0\), where \(\varvec{S}_n^{2\beta }\) is an isotropic stable process independent from \(\mathcal {L}^{\nu _1, \ldots , \nu _m}(t)\), which is the inverse of \(\mathcal {H}^{\nu _1, \ldots , \nu _m} (t) = \sum _{j=1}^m \lambda _j^{1/\nu _j} H^{\nu _j} (t)\), \(t>0\), with \(H^{\nu _j}(t)\) independent, positively skewed stable random variables of order \(\nu _j\). The problem considered includes the fractional telegraph equation as a special case as well as the governing equation of stable processes. The composition \(\varvec{S}_n^{2\beta } \left( c^2 \mathcal {L}^{\nu _1, \ldots , \nu _m} (t) \right) \), \(t>0\), supplies a probabilistic representation for the solutions of the fractional equations above and coincides for \(\beta = 1\) with the n-dimensional Brownian motion at the random time \(\mathcal {L}^{\nu _1, \ldots , \nu _m} (t)\), \(t>0\). The iterated process \(\mathfrak {L}^{\nu _1, \ldots , \nu _m}_r (t)\), \(t>0\), inverse to \(\mathfrak {H}^{\nu _1, \ldots , \nu _m}_r (t) =\sum _{j=1}^m \lambda _j^{1/\nu _j} \, _1H^{\nu _j} \left( \, _2H^{\nu _j} \left( \, _3H^{\nu _j} \left( \ldots \, _{r}H^{\nu _j} (t) \ldots \right) \right) \right) \), \(t>0\), permits us to construct the process \(\varvec{S}_n^{2\beta } \left( c^2 \mathfrak {L}^{\nu _1, \ldots , \nu _m}_r (t) \right) \), \(t>0\), the density of which solves a space-fractional equation of the form of the generalized fractional telegraph equation. For \(r \rightarrow \infty \) and \(\beta = 1\), we obtain a probability density, independent from t, which represents the multidimensional generalization of the Gauss–Laplace law and solves the equation \(\sum _{j=1}^m \lambda _j w(x_1, \ldots , x_n) = c^2 \sum _{j=1}^n \frac{\partial ^2}{\partial x_j^2} w(x_1, \ldots , x_n)\). Our analysis represents a general framework of the interplay between fractional differential equations and composition of processes of which the iterated Brownian motion is a very particular case.     

A Note on Malliavin Fractional Smoothness for Lévy Processes and Approximation

Assume a Lévy process (X _t ) _t?∈?[0,1] that is an L ₂-martingale and let Y be either its stochastic exponential or X itself. For certain integrands φ we investigate the behavior of $$ \bigg \|\int_{(0,1]} {{\varphi}}_t dX_t - \sum_{k=1}^N v_{k-1} (Y_{t_k}-Y_{t_{k-1}}) \bigg \|_{L_2}, $$ where v _k???1 is ${\mathcal{F}}_{t_{k-1}}$ -measurable, in dependence on the fractional smoothness in the Malliavin sense of $\int_{(0,1]} {{\varphi}}_t dX_t$ . A typical situation where these techniques apply occurs if the stochastic integral is obtained by the Galtchouk–Kunita–Watanabe decomposition of some f(X ₁). Moreover, using the example f(X ₁)?=?1_(K,?∞?)(X ₁) we show how fractional smoothness depends on the distribution of the Lévy process.     

Magnetic Energies and Feynman–Kac–Itô Formulas for Symmetric Markov Processes

Given a (conservative) symmetric Markov process on a metric space we consider related bilinear forms that generalize the energy form for a particle in an electromagnetic field. We obtain one bilinear form by semigroup approximation and another, closed one, by using a Feynman–Kac–Itô formula. If the given process is Feller, its energy measures have densities and its jump measure has a kernel, then the two forms agree on a core and the second is a closed extension of the first. In this case we provide the explicit form of the associated Hamiltonian.     

Estimates of Green Function for Relativistic α-Stable Process

We call an R ^d -valued stochastic process X _t with characteristic function exp{–t{(m ^2/+²)^/2–m}},R ^d ,m>0, the relativistic -stable process. In the paper we derive sharp estimates for the Green function of the relativistic -stable process on C ^1,1 domains. Using these estimates we provide lower and upper bounds for the Poisson kernel. As another application we derive 3G Theorem and Boundary Harnack Principle for C ^1,1 domains.