数学学科Seminar第2213讲 Geometry of Painlevé equations: (5,6)

创建时间:  2021/11/23  龚惠英   浏览次数:   返回

报告题目 (Title):Geometry of Painlevé equations: (5,6)

报告人 (Speaker): Anton DZhamay 教授(北科罗拉多大学)

报告时间 (Time):2021年11月30日(周二) 11:00-13:00

报告地点 (Place):腾讯会议ID:828 397 716

邀请人(Inviter):张大军

主办部门:理学院数学系

报告摘要:In this mini-course we would present some beautiful geometric ideas underlying the theory of Painlevé equations, both differential and discrete. We explain the idea behind the construction, due to K. Okamoto, of the space of initial conditions of a differential Painlevé equation, and how understandign the geometry of this space can help us understand its symmetries (Bäcklund transformations). We also explain the appearance of discrete Painlevé equations as particular combinations of such symmetries that admit a structure of a discrete dynamical systems. We then generalize these ides to explain the full classification scheme of Painlevé equations, due to H. Sakai.

上一条:物理学科Seminar第572讲 自动生成神经网络势能面:增强自组织增量神经网络深度势能方法

下一条:数学学科Seminar第2212讲 Discovering the subdiffusion model in an unknown medium


数学学科Seminar第2213讲 Geometry of Painlevé equations: (5,6)

创建时间:  2021/11/23  龚惠英   浏览次数:   返回

报告题目 (Title):Geometry of Painlevé equations: (5,6)

报告人 (Speaker): Anton DZhamay 教授(北科罗拉多大学)

报告时间 (Time):2021年11月30日(周二) 11:00-13:00

报告地点 (Place):腾讯会议ID:828 397 716

邀请人(Inviter):张大军

主办部门:理学院数学系

报告摘要:In this mini-course we would present some beautiful geometric ideas underlying the theory of Painlevé equations, both differential and discrete. We explain the idea behind the construction, due to K. Okamoto, of the space of initial conditions of a differential Painlevé equation, and how understandign the geometry of this space can help us understand its symmetries (Bäcklund transformations). We also explain the appearance of discrete Painlevé equations as particular combinations of such symmetries that admit a structure of a discrete dynamical systems. We then generalize these ides to explain the full classification scheme of Painlevé equations, due to H. Sakai.

上一条:物理学科Seminar第572讲 自动生成神经网络势能面:增强自组织增量神经网络深度势能方法

下一条:数学学科Seminar第2212讲 Discovering the subdiffusion model in an unknown medium