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Ruinan Li

Publications and source records attributed to Ruinan Li.

8 recordsLinked to original sources

Convergence rate of randomized midpoint Langevin Monte Carlo

The randomized midpoint Langevin Monte Carlo (RLMC), introduced by Shen and Lee (2019), is a variant of classical Unadjusted Langevin Algorithm. It was shown in the literature that the RLMC is an efficient algorithm for approximating high-dimensional probability distribution $\pi$. In this paper, we establish the exponential ergodicity of RLMC with constant step-size. Moreover, we design a dereasing-step size RLMC and provide its convergence rate in terms of a functional class distance.

math.ST

Talagrand's transportation inequality for SPDEs with locally monotone drifts

The purpose of this paper is twofold. Firstly, we prove transportation inequalities ${\bf T_2}(C)$ on the space of continuous paths with respect to the uniform metric for the law of the solution to a class of non-linear monotone stochastic partial differential equations (SPDEs) driven by the Wiener noise. Furthermore, we also establish the ${\bf T_1}(C)$ property for such SPDEs but with merely locally monotone coefficients, including the stochastic Burgers type equation and stochastic $2$-D Navier-Stokes equation.

math.PR

A large deviation principle for the stochastic heat equation with general rough noise

We study Freidlin-Wentzell's large deviation principle for one dimensional nonlinear stochastic heat equation driven by a Gaussian noise: $$\frac{\partial u^\varepsilon(t,x)}{\partial t} = \frac{\partial^2 u^\varepsilon(t,x)}{\partial x^2}+\sqrt{\varepsilon} σ(t, x, u^\varepsilon(t,x))\dot{W}(t,x),\quad t> 0,\, x\in\mathbb{R},$$ where $\dot W$ is white in time and fractional in space with Hurst parameter $H\in(\frac 14,\frac 12)$. Recently, Hu and Wang ({\it Ann. Inst. Henri Poincaré Probab. Stat.} {\bf 58} (2022) 379-423) studied the well-posedness of this equation without the technical condition of $σ(0)=0$ which was previously assumed in Hu et al. ({\it Ann. Probab}. {\bf 45} (2017) 4561-4616). We adopt a new sufficient condition proposed by Matoussi et al. ({\it Appl. Math. Optim.} \textbf{83} (2021) 849-879) for the weak convergence criterion of the large deviation principle.

math.PR

Ricci curvature and $W_1$-exponential convergence of Markov processes on graphs

In this paper, we show that the Ricci curvature lower bound in Ollivier's Wasserstein metric sense of a continuous time jumping Markov process on a graph can be characterized by some optimal coupling generator and provide the construction of this latter. Some previous results of Ollivier for discrete time Markov chains are generalized to the actual continuous time case. We propose a comparison technique with some death-birth process on $\mathbb N$ to obtain some explicit exponential convergence rate, by modifying the metric. A counterpart of Zhong-Yang's estimate is established in the case where the Ricci curvature with repsect to the graph metric is nonnegative. Moreover we show that the Lyapunov function method for the exponential convergence works with some explicit quantitative estimates, once if the Ricci curvature is bounded from below by a negative constant. Finally we present applications to Glauder dynamics under some dynamical versions of the Dobrushin uniqueness condition or of the Dobrushin-Shlosman analyticity condition.

math.PR

Exponential convergence in the Wasserstein metric $W_1$ for one dimensional diffusions

In this paper, we find some general and efficient sufficient conditions for the exponential convergence $W_{1,d}(P_t(x,\cdot), P_t(y,\cdot) )\le Ke^{-δt}d(x,y)$ for the semigroup $(P_t)$ of one-dimensional diffusion. Moreover some sharp estimates of the involved constants $K\ge 1, δ>0$ are provided. Those general results are illustrated by a series of examples.

math.PR