Reflected Backward Stochastic Differential Equation with Jumps and RCLL Obstacle

In this paper we study one-dimensional reflected backward stochastic differential equation when the noise is driven by a Brownian motion and an independent Poisson point process when the solution is forced to stay above a right continuous left-hand limited obstacle. We prove existence and uniqueness of the solution by using a penalization method combined with a monotonic limit theorem.

Stochastic differential equations with random coefficients

In this paper we establish the existence and uniqueness of a solution for different types of stochastic differential equation with random initial conditions and random coefficients. The stochastic integral is interpreted as a generalized Stratonovich integral, and the techniques used to derive these results are mainly based on the path properties of the Brownian motion, and the definition of the Stratonovich integral.

Dynamical properties of nonmarkovian stochastic differential equations

We study nonstationary non-Markovian processes defined by Langevin-type stochastic differential equations with an OrnsteinUhlenbeck driving force. We concentrate on the long time limit of the dynamical evolution. We derive an approximate equation for the correlation function of a nonlinear nonstationary non-Markovian process, and we discuss its consequences. Non-Markovicity can introduce a dependence on noise parameters in the dynamics of the correlation function in cases in which it becomes independent of these parameters in the Markovian limit. Several examples are discussed in which the relaxation time increases with respect to the Markovian limit. For a Brownian harmonic oscillator with fluctuating frequency, the non-Markovicity of the process decreases the domain of stability of the system, and it can change an infradamped evolution into an overdamped one.

Symmetries and fixed point stability of stochastic differential equations modeling self-organized criticality

A stochastic nonlinear partial differential equation is constructed for two different models exhibiting self-organized criticality: the Bak-Tang-Wiesenfeld (BTW) sandpile model [Phys. Rev. Lett. 59, 381 (1987); Phys. Rev. A 38, 364 (1988)] and the Zhang model [Phys. Rev. Lett. 63, 470 (1989)]. The dynamic renormalization group (DRG) enables one to compute the critical exponents. However, the nontrivial stable fixed point of the DRG transformation is unreachable for the original parameters of the models. We introduce an alternative regularization of the step function involved in the threshold condition, which breaks the symmetry of the BTW model. Although the symmetry properties of the two models are different, it is shown that they both belong to the same universality class. In this case the DRG procedure leads to a symmetric behavior for both models, restoring the broken symmetry, and makes accessible the nontrivial fixed point. This technique could also be applied to other problems with threshold dynamics.

Linear stochastic differential algebraic equations with constant coefficients

We consider linear stochastic differential-algebraic equations with constant coefficients and additive white noise. Due to the nature of this class of equations, the solution must be defined as a generalised process (in the sense of Dawson and Fernique). We provide sufficient conditions for the law of the variables of the solution process to be absolutely continuous with respect to Lebesgue measure.

Generalized backward doubly stochastic differential equations and SPDEs with nonlinear Neumann boundary conditions

In this paper, a new class of generalized backward doubly stochastic differential equations is investigated. This class involves an integral with respect to an adapted continuous increasing process. A probabilistic representation for viscosity solutions of semi-linear stochastic partial differential equations with a Neumann boundary condition is given.

Hopf bifurcation of a delay differential equation with two delays

We consider a delay differential equation with two delays. The Hopf bifurcation of this equation is investigated together with the stability of the bifurcated periodic solution, its period and the bifurcation direction. Finally, three applications are given.

Gaussian estimates for the density of the non-linear stochastic heat equation in any space dimension

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

Aeromonas hydrophila lateral flagella gene transcriptional hierarchy

Aeromonas hydrophila AH-3 lateral flagella are not assembled when bacteria grow in liquid media; however, lateral flagellar genes are transcribed. Our results indicate that A. hydrophila lateral flagellar genes are transcribed at three levels (class I to III genes) and share some similarities with, but have many important differences from, genes of Vibrio parahaemolyticus. A. hydrophila lateral flagellum class I gene transcription is σ70 dependent, which is consistent with the fact that lateral flagellum is constitutively transcribed, in contrast to the characteristics of V. parahaemolyticus. The fact that multiple genes are included in class I highlights that lateral flagellar genes are less hierarchically transcribed than polar flagellum genes. The A. hydrophila lafK-fliEJL gene cluster (where the subscript L distinguishes genes for lateral flagella from those for polar flagella) is exclusively from class I and is in V. parahaemolyticus class I and II. Furthermore, the A. hydrophila flgAMNL cluster is not transcribed from the σ54/LafK-dependent promoter and does not contain class II genes. Here, we propose a gene transcriptional hierarchy for the A. hydrophila lateral flagella.

Aeromonas hydrophila lateral flagella gene transcriptional hierarchy

Aeromonas hydrophila AH-3 lateral flagella are not assembled when bacteria grow in liquid media; however, lateral flagellar genes are transcribed. Our results indicate that A. hydrophila lateral flagellar genes are transcribed at three levels (class I to III genes) and share some similarities with, but have many important differences from, genes of Vibrio parahaemolyticus. A. hydrophila lateral flagellum class I gene transcription is σ(70) dependent, which is consistent with the fact that lateral flagellum is constitutively transcribed, in contrast to the characteristics of V. parahaemolyticus. The fact that multiple genes are included in class I highlights that lateral flagellar genes are less hierarchically transcribed than polar flagellum genes. The A. hydrophila lafK-fliEJL gene cluster (where the subscript L distinguishes genes for lateral flagella from those for polar flagella) is exclusively from class I and is in V. parahaemolyticus class I and II. Furthermore, the A. hydrophila flgAMNL cluster is not transcribed from the σ(54)/LafK-dependent promoter and does not contain class II genes. Here, we propose a gene transcriptional hierarchy for the A. hydrophila lateral flagella.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

Large deviation for BSDE with subdifferential operator

In this paper we prove that the solution of a backward stochastic differential equation, which involves a subdifferential operator and associated to a family of reflecting diffusion processes, converges to the solution of a deterministic backward equation and satisfes a large deviation principle.

Weak approximations. A Malliavin calculus approach

We introduce a variation of the proof for weak approximations that issuitable for studying the densities of stochastic processes which areevaluations of the flow generated by a stochastic differential equation on a random variable that maybe anticipating. Our main assumption is that the process and the initial random variable have to be smooth in the Malliavin sense. Furthermore if the inverse of the Malliavin covariance matrix associated with the process under consideration is sufficiently integrable then approximations fordensities and distributions can also be achieved. We apply theseideas to the case of stochastic differential equations with boundaryconditions and the composition of two diffusions.