activity
20192022
most citedQuasi-Monte Carlo sampling for machine-learning partial differential equations

4 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

math.NA2022

Convergence analysis of an implicit finite difference method for the inertial Landau-Lifshitz-Gilbert equation

Jingrun Chen, Panchi Li, Cheng Wang

The Landau-Lifshitz-Gilbert (LLG) equation is a widely used model for fast magnetization dynamics in ferromagnetic materials. Recently, the inertial LLG equation, which contains an…

math.NA2021

A second-order semi-implicit method for the inertial Landau-Lifshitz-Gilbert equation

Panchi Li, Lei Yang, Jin Lan +2

Recent theoretical and experimental advances show that the inertia of magnetization emerges at sub-picoseconds and contributes to the ultrafast magnetization dynamics which cannot…

cs.CE2019

Numerical methods for antiferromagnetics

Panchi Li, Jingrun Chen, Rui Du +1

Compared with ferromagnetic counterparts, antiferromagnetic materials are considered as the future of spintronic applications since these materials are robust against the magnetic…

math.NA20194 cited

Quasi-Monte Carlo sampling for machine-learning partial differential equations

Jingrun Chen, Rui Du, Panchi Li +1

Solving partial differential equations in high dimensions by deep neural network has brought significant attentions in recent years. In many scenarios, the loss function is defined…

math.NA2019

Two improved Gauss-Seidel projection methods for Landau-Lifshitz-Gilbert equation

Panchi Li, Changjian Xie, Rui Du +2

In this paper, we present two improved Gauss-Seidel projection methods with unconditional stability. The first method updates the gyromagnetic term and the damping term simultaneou…