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Jiaxin Zha

Publications and source records attributed to Jiaxin Zha.

2 recordsLinked to original sources

Uniform-in-Time Smoluchowski-Kramers Approximation in Total Variation for Fractional SDEs

Let $B^H$ be a one-dimensional fractional Brownian motion with Hurst index $H\in(1/2,1)$. We study the small-mass limit of the kinetic equation \[ dX_t^μ=Y_t^μ\,dt,\qquad μ\,dY_t^μ=b(X_t^μ)\,dt-Y_t^μ\,dt +σ(X_t^μ)\,dB_t^H, \] where the noise coefficient is state dependent and uniformly nondegenerate. The limiting equation is the Young differential equation \[ dX_t=b(X_t)\,dt+σ(X_t)\,dB_t^H. \] Under uniform ellipticity and strict dissipativity of the transformed drift, we prove that, for every $t_0>0$ and every $ρ<2H-1$, \[ \sup_{t\ge t_0}d_{TV}\big(X_t^μ,X_t\big) \le C_{t_0,ρ}μ^ρ. \] The estimate is uniform on the entire half-line. We also construct stationary solutions on a two-sided fractional-noise space and obtain convergence of their one-time marginals in total variation. The exponent $2H-1$ is identified as the natural endpoint: it is generated by the quadratic velocity term after the Lamperti transform, and it degenerates as $H\downarrow1/2$. A nonconstant uniformly elliptic example is included.

math.PR

Smoluchowski-Kramers Approximation for Stochastic Differential Equations driven by Fractional Brownian Motion

In this paper, we discuss the validity of an approximation inspired by the Smoluchowski-Kramers approximation for a class of stochastic differential equations driven by fractional Brownian motion with additive noise. By rewriting such equations in the form of slow-fast systems and decomposing the fast component into three parts, we investigate the small mass limit of these equations and derive the corresponding convergence rates. Furthermore, under certain regularity conditions, we study the large and moderate deviation principles for a class of stochastic differential equations driven by fractional Brownian motion with small multiplicative noise via the weak convergence approach.

math.PR