activity
20182021
most citedMaximal Likely Phase Lines for a Reduced Ice Growth Model

1 citations · 1 across the 3 of their papers we have counts for

collaborators

9 papers

math.DS2021

Parametric resonance for enhancing the rate of metastable transition

Ying Chao, Molei Tao

This work is devoted to quantifying how periodic perturbation can change the rate of metastable transition in stochastic mechanical systems with weak noises. A closed-form explicit…

math.DS2020

Lyapunov Exponents for Hamiltonian Systems under Small Lévy Perturbations

Ying Chao, Pingyuan Wei, Jinqiao Duan

This work is to investigate the (top) Lyapunov exponent for a class of Hamiltonian systems under small non-Gaussian Lévy noise. In a suitable moving frame, the linearisation of suc…

math.DS2020

The role of slow manifolds in parameter estimation for a multiscale stochastic system with -stable Lévy noise

Ying Chao, Pingyuan Wei, Jinqiao Duan

This work is about parameter estimation for a fast-slow stochastic system with non-Gaussian -stable Lévy noise. When the observations are only available for slow components, a s…

math.DS20191 cited

Maximal Likely Phase Lines for a Reduced Ice Growth Model

Athanasios Tsiairis, Pingyuan Wei, Ying Chao +1

We study the impact of Brownian noise on transitions between metastable equilibrium states in a stochastic ice sheet model. Two methods to accomplish different objectives are emplo…

math.DS2018

Characterization of the Most Probable Transition Paths of Stochastic Dynamical Systems with Stable Lévy Noise

Yuanfei Huang, Ying Chao, Shenglan Yuan +1

This work is devoted to the investigation of the most probable transition path for stochastic dynamical systems driven by either symmetric -stable Lévy motion () or Brown…

math.DS2018

Hamiltonian Systems with Lévy Noise: Symplecticity, Hamilton's Principle and Averaging Principle

Pingyuan Wei, Ying Chao, Jinqiao Duan

This work focuses on topics related to Hamiltonian stochastic differential equations with Lévy noise. We first show that the phase flow of the stochastic system preserves symplecti…