报告人: 丁效华（哈尔滨工业大学（威海））

报告人简介：丁效华教授，博士，哈尔滨工业大学博士生导师，基础教学带头人，山东省数学类专业及大学数学课程教学指导委员会秘书长，天山学者讲座教授, 威海市第一批有突出贡献的中青年专家,曾获“宝钢”优秀教师奖。中国系统仿真协会会员，中国系统仿真协会算法委员会理事，黑龙江省工业应用数学会常务理事，山东省数学会理事。山东省“十五”重点建设学科计算数学负责人，山东省优秀教学团队“工科数学教学团队”负责人，山东省精品课程群“工科数学系列课程”负责人,《Discrete Dynamics in Nature and Society》编委，《黑龙江大学学报（自然科学版）》编委; 在BIT、JMAA、JCAM、Neurocomputing等高水平刊物上发表论文百余篇。获黑龙江省科学技术进步（自然科学）一等奖，黑龙江省教学成果一等奖，山东省教学成果二等奖，黑龙江省高校科学技术进步一等奖。主编出版《数值分析原理》，国家“十一五”规划教材《工科数学分析教程》（上、下）（获机械工业出版社优秀教材一等奖），《概率论与数理统计》等教材。

报告（一)

报告题目: Stochastic partitioned averaged vector field methods for stochastic differential equations with a conserved quantity

报告摘要：In this paper, stochastic differential equations in the Stratonovich sense with a conserved quantity are considered. A stochastic partitioned averaged vector field method is proposed and analyzed. We prove this numerical method is able to preserve the conserved quantity of the original system. Then the convergence analysis is carried out in detail and we derive the method is convergent with order 1 in the mean-square sense. Finally, some numerical examples are reported to verify the effectiveness and flexibility of the proposed method.

报告时间: 2019年4月23日（星期二）上午10:00-11:00

报告地点: 科技楼南楼702室

报告（二)

报告题目: Numerical simulations for stochastic differential equations on manifolds by stochastic symmetric projection method

报告摘要：Stochastic standard projection technique, as an efficient approach to simulate stochastic differential equations on manifolds, is widely used in the practical applications. However, stochastic standard projection methods usually destroy the geometric properties (such as symplecticity or reversibility), even though the underlying methods are symplectic or symmetric, which seriously affect long-time behavior of the numerical solutions. In this paper, a modification of stochastic standard projection methods for stochastic differential equations is presented. The modified methods which are called the stochastic symmetric projection methods remain the symmetry and the ρ-reversibility of the underlying methods and maintain the numerical solutions on the correct manifolds. The mean square convergence order of these methods are proved to be the same as the underlying methods’. Numerical experiments are implemented to verify the theoretical results and show the superiority of the stochastic symmetric projection methods over the stochastic standard projection methods.

报告时间: 2019年4月23日（星期二）下午4:00-5:00

报告地点: 科技楼南楼702室