报告题目：Assessing numerical methods for molecular and particle simulation

报 告 人：商晓成副教授（英国伯明翰大学）

报告时间：2025年8月7日上午10:00

报告地址：广州国际校区C3-c204

报告邀请人：周嘉嘉教授

邀请单位：前沿软物质学院 

报告摘要：

　　We discuss the design of state-of-the-art numerical methods for molecular dynamics, focusing on the demands of soft matter simulation, where the purposes include sampling and dynamics calculations both in and out of equilibrium. We discuss the characteristics of different algorithms, including their essential conservation properties, the convergence of averages, and the accuracy of numerical discretizations. Formulations of the equations of motion which are suited to both equilibrium and nonequilibrium simulation include Langevin dynamics, dissipative particle dynamics (DPD), and the more recently proposed “pairwise adaptive Langevin” (PAdL) method, which, like DPD but unlike Langevin dynamics, conserves momentum and better matches the relaxation rate of orientational degrees of freedom. PAdL is easy to code and suitable for a variety of problems in nonequilibrium soft matter modeling; our simulations of polymer melts indicate that this method can also provide dramatic improvements in computational efficiency. Moreover we show that PAdL gives excellent control of the relaxation rate to equilibrium. In the nonequilibrium setting, we further demonstrate that while PAdL allows the recovery of accurate shear viscosities at higher shear rates than are possible using the DPD method at identical timestep, it also outperforms Langevin dynamics in terms of stability and accuracy at higher shear rates. 

个人简介:

　　商晓成，2016年博士毕业于英国爱丁堡大学，现为英国伯明翰大学数学学院副教授。研究方向为随机微分方程数值解与误差分析、分子动力学、高分子模拟、机器学习（大数据），在SIAM Review、SIAM Journal on Scientific Computing、Journal of Computational Physics、Proceedings of the Royal Society A、Soft Matter、Advances in Neural Information Processing Systems (NeurIPS)等国际著名期刊、会议发表论文十余篇。