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Olga Aryasova

Publications and source records attributed to Olga Aryasova.

12 recordsLinked to original sources

Diffusion limits of cyclic finite-velocity random motions along vector fields

We investigate diffusion approximations for a class of multivariate inhomogeneous finite-velocity random motions motivated by models of active particles. A particle alternates cyclically among prescribed velocity fields $V_1,\dots,V_p$ with random run times and evolves according to either a \emph{flight} dynamics, consisting of piecewise-linear motion, or a \emph{gliding} dynamics, in which the particle follows the corresponding velocity flow. Under a Kac-type scaling that couples vanishing run times with diverging particle speed, we prove weak convergence of both processes to multidimensional diffusions. It turns out that the order of successive cyclic motions affects the diffusion limit. In addition to the second-order term generated by fluctuations of the random run times, the limiting drift contains directional derivatives $DV_i[V_j]$ of the underlying vector fields. In Stratonovich form, part of this drift is expressed through their Lie brackets $[V_i,V_j]$. Thus, the generic non-commutativity of the microscopic motions survives the diffusive scaling and generates a macroscopic drift which depends on the cyclic order. The limiting drift also distinguishes the flight and gliding dynamics, despite their being driven by the same vector fields and run times. Several examples, including run-and-reverse motion and cyclic dynamics generated by multiple vector fields, illustrate how the cyclic switching protocol and the geometry of the underlying velocity fields shape the limiting diffusions.

math.PR

A Tail-Respecting Splitting Numerical Scheme for Lévy-Driven SDEs With Superlinear Drifts

We present an explicit numerical approximation scheme, denoted by $\{X^n\}$, for the effective simulation of solutions $X$ to a multivariate stochastic differential equation (SDE) with a superlinearly growing $κ$-dissipative drift, where $κ>1$, driven by a multiplicative heavy-tailed Lévy process that has a finite $p$-th moment, with $p>0$. We show that the strong $L^{p_X}$-convergence $\sup_{t\in[0,T]}\mathbf E \|X^n_t-X_t\|^{p_X}=\mathcal O (h_n^γ)$ holds for any $p_X\in (0,p+κ-1)$, which is exactly the range where the $p_X$-moment of the solution is known to be finite. Additionally, for any $p_X\in (0,p)$ we establish strong uniform convergence: $\mathbf E\sup_{t\in[0,T]} \|X^n_t-X_t\|^{p_X}=\mathcal{O} ( h_n^δ )$. In both cases we determine the convergence rates $γ$ and $δ$. In the special case of SDEs driven solely by a Brownian motion, our numerical scheme preserves super-exponential moments of the solution. The scheme $\{X^n\}$ is realized as a combination of a well-known Euler method with a Lie-Trotter type splitting technique.

math.PR

Limit theorems for sticky SDEs with local times and applications to stochastic homogenization

In this paper, we establish a general convergence theorem for solutions of multivariate stochastic differential equations with countably many singular terms expressed as integrals with respect to local times. The processes under consideration describe diffusions in the presence of semipermeable hyperplane interfaces. These interfaces may become sticky after applying a random time change that depends on the amount of local time accumulated on each interface. We show that, as the distance between the interfaces tends to zero, the local-time terms converge to a limiting homogenized drift term. When the interfaces are sticky, the limiting diffusion also decelerates, meaning that its diffusion coefficient is effectively reduced. Such limit theorems illustrate a form of stochastic homogenization for diffusions evolving in a heterogeneous medium interleaved with semipermeable, sticky interfaces.

math.PR

How to simulate Lévy flights in a steep potential: An explicit splitting numerical scheme

We propose an effective explicit numerical scheme for simulating solutions of stochastic differential equations with confining superlinear drift terms, driven by multiplicative heavy-tailed Lévy noise. The scheme is designed to prevent explosion and accurately capture all finite moments of the solutions. In the purely Gaussian case, it correctly reproduces moments of sub-Gaussian tails of the solutions. This method is particularly well-suited for approximating statistical moments and other probabilistic characteristics of Lévy flights in steep potential landscapes.

physics.comp-ph

The hard membrane process and transport barriers of turbulent flows

Motivated by the phenomenon of transport barriers in fusion plasma devices, we write a mathematical model of heat dispersion in a turbulent fluid with a transport barrier, properly idealized; in a scaling limit of the turbulence model with separation of scales we get a heat equation with space-dependent diffusion coefficient, poorly diffusing near the barrier; then we investigate the scaling limit when the diffused barrier converges to a sharp separating surface and describe the limit by means of the stochastic process called Brownian motion with hard membrane.

math.PR

Homogenization of a multivariate diffusion with semipermeable interfaces

We study the homogenization problem for a system of stochastic differential equation with local time terms that models a multivariate diffusion in presence of semipermeable hyperplane interfaces with oblique penetration. We show that this system has a unique weak solution and determine its weak limit as the distances between the interfaces converge to zero. In the limit, the singular local times terms vanish and give rise to an additional regular interface-induced drift.

math.PR

On exponential decay of a distance between solutions of an SDE with non-regular drift

We consider a multidimensional stochastic differential equation with a Gaussian noise and a drift vector having a jump discontinuity along a hyperplane. The large time behavior of the distance between two solutions starting from different points is studied.We consider a multidimensional stochastic differential equation with a Gaussian noise and a drift vector having a jump discontinuity along a hyperplane. The large time behavior of the distance between two solutions starting from different points is studied.

math.PR

A representation for the derivative with respect to the initial data of the solution of an SDE with a non-regular drift and a Gaussian noise

We consider a multidimensional SDE with a Gaussian noise and a drift vector being a vector function of bounded variation. We prove the existence of generalized derivative of the solution with respect to the initial conditions and represent the derivative as a solution of a linear SDE with coefficients depending on the initial process. The representation obtained is a natural generalization of the expression for the derivative in the smooth case. The theory of continuous additive functionals is used.

math.PR

Reflecting diffusions and hyperbolic Brownian motions in multidimensional spheres

Diffusion processes $(\underline{\bf X}_d(t))_{t\geq 0}$ moving inside spheres $S_R^d \subset\mathbb{R}^d$ and reflecting orthogonally on their surfaces $\partial S_R^d$ are considered. The stochastic differential equations governing the reflecting diffusions are presented and their kernels and distributions explicitly derived. Reflection is obtained by means of the inversion with respect to the sphere $S_R^d$. The particular cases of Ornstein-Uhlenbeck process and Brownian motion are examined in detail. The hyperbolic Brownian motion on the Poincarè half-space $\mathbb{H}_d$ is examined in the last part of the paper and its reflecting counterpart within hyperbolic spheres is studied. Finally a section is devoted to reflecting hyperbolic Brownian motion in the Poincarè disc $D$ within spheres concentric with $D$.

math.PR

On simultaneous hitting of membranes by two skew Brownian motions

We consider two depending Wiener processes which have membranes at zero with different permeability coefficients. Starting from different points, the processes almost surely do not meet at any fixed point except that where membranes are situated. The necessary and sufficient conditions for the meeting of the processes are found. It is shown that the probability of meeting is equal to zero or one.

math.PR