Mathematical Sciences: Conference on Dynamical Numerical Analysis
Mathematical Sciences: Conference on Dynamical Numerical Analysis
批准号:
9503447
负责人:
Luca Dieci
金额:
$0.82万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1995
资助国家:
美国
项目状态:
已结题
起止时间:
1995-08-01 至 1996-07-31
中文摘要
Dieci 研究者和他的同事组织了一个关于动力系统数值方法的国际会议。 近年来,随着经典定量数值分析的局限性越来越明显,动力系统和数值分析之间的相互作用也越来越大。 在实践中,计算的一个共同目标是获得关于中到长时间间隔内的解的信息,然而经典的误差分析通常在短的初始瞬态之后没有意义。 因此,它是基本的微分方程的数值分析,以解决现有的计算方法的有效性和设计的特殊方法计算在很长的时间间隔。 具体的主题将涵盖包括收敛的积分算法在长时间间隔(包括长时间误差界和不变集的收敛性),长时间间隔内积分算法的稳定性(包括保持动力学结构和虚假解决方案),新的方法进行误差分析(包括阴影结果和向后误差分析),以及不变集的计算技术的设计,例如计算不变torii,惯性流形,异宿轨道,同宿轨道和李雅普诺夫指数。 微分方程描述了一个物理系统在空间中的一个位置在特定时间如何影响邻近的位置。 正是微分方程的这种局部性质使得模拟复杂的物理情况成为可能,因为这意味着不必同时描述整个系统。 但这也意味着获得系统的正确微分方程模型并不是故事的结束,因为还需要求解微分方程才能获得有关原始系统的信息。 因此,微分方程解的研究已经成为数学的主要领域之一,同时在科学和工程中变得非常重要。 计算机的引入使得第一次在大范围内近似求解微分方程成为可能。 在过去的三十年里,数值数学家在设计微分方程特定解的近似方法以及分析近似解的准确性方面取得了很大进展。 研究微分方程数值方法的经典方法非常善于描述在短时间间隔内小空间区域内特定解的近似行为。 但是,要理解非线性方程的本质,需要了解相对较长时间间隔内的许多解。 为了满足这一需求,人们越来越感兴趣地使用数值方法来研究微分方程解的结构和模式,这被称为方程的动力学行为。 本次会议聚集了来自美国和世界各地的顶尖专家,代表了该领域的几乎所有方面,以及感兴趣的学生和其他研究人员,讨论当前的艺术状态并刺激新的发展。 预计会议将对科学和工程领域的许多应用产生长期影响。
英文摘要
Dieci The investigator and his colleagues organize an international conference on numerical methods for dynamical systems. The interaction between dynamical systems and numerical analysis has grown in recent years as the limitations of classical quantitative numerical analysis have become increasingly apparent. In practice, a common goal of computation is to obtain information about solutions over moderate to long time intervals, yet classical error analysis is generally not meaningful past a short initial transient. It is thus fundamental to the numerical analysis of differential equations to address both the efficacy of existing computational methods and the design of special methods for computation over long time intervals. Specific topics to be covered include convergence of integration algorithms over long time intervals (including long-time error bounds and convergence of invariant sets), stability of integration algorithms over long time intervals (including preservation of dynamical structure and spurious solutions), new approaches to error analysis (including shadowing results and backward error analysis), and design of computational techniques for invariant sets such as algorithms to compute invariant torii, inertial manifolds, heteroclinic orbits, homoclinic orbits, and Lyapunov exponents. Differential equations describe how one position in space of a physical system at a particular time influences neighboring positions in the immediate future. It is this local nature of a differential equation that makes it possible to model complicated physical situations, because it means that the entire system does not have to be described simultaneously. But this also means that obtaining the correct differential equation model of a system is not the end of the story, because it is necessary to solve the differential equation to obtain information about the original system. Accordingly, the study of solutions of differential equations has grown int o one of the major areas of mathematics while becoming centrally important in science and engineering. The introduction of the computer made it possible to approximately solve differential equations on a wide scale for the first time. Over the last thirty years, numerical mathematicians have made great progress in devising methods to approximate a specific solution of a differential equation and in analyzing the accuracy of the approximate solution. The classical approach to study numerical methods for differential equations is very good at describing the behavior of the approximation of a particular solution in a small region of space over a short time interval. But understanding the nature of nonlinear equations requires knowledge about many solutions over relatively long time intervals. In response to this need, there is increasing interest in using numerical methods to study structures and patterns in solutions of differential equations, which is known as the dynamical behavior of the equation. This conference gathers leading experts from the United States and from around the world, representing nearly all aspects of the area, together with interested students and other researchers, to discuss the current state of the art and to stimulate new developments. The conference is expected to have a long-ranging impact on many applications in science and engineering.
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Support for USA participants in the Dynamics of Evolution Equations conference
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批准号:1562181
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项目类别:Standard Grant
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资助金额:$3.0万
-
财政年份:2016
-
负责人:Luca Dieci
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依托单位:
Increasing the number of mathematics graduate students and of professional mathematicians entering the workforce
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批准号:1060333
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项目类别:Continuing Grant
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资助金额:$60.0万
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财政年份:2011
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负责人:Luca Dieci
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依托单位:
FRG: Collaborative Research: Approximation of Lyapunov Exponents
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批准号:0139895
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项目类别:Standard Grant
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资助金额:$23.55万
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财政年份:2002
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负责人:Luca Dieci
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依托单位:
Some Approximation Problems in Differential Equations
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批准号:9973266
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项目类别:Standard Grant
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资助金额:$12.95万
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财政年份:1999
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负责人:Luca Dieci
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依托单位:
Mathematical Sciences: Some Approximation Problems in Differential Equations
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批准号:9625813
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项目类别:Standard Grant
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资助金额:$11.59万
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财政年份:1996
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负责人:Luca Dieci
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依托单位:
Mathematical Sciences: Numerical Solution of Matrix Differential Equations and Approximation of Invariant Tori
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批准号:9306412
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项目类别:Continuing Grant
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资助金额:$8.53万
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财政年份:1993
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负责人:Luca Dieci
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依托单位:
Mathematical Sciences Computing Research Environments
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批准号:9207070
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项目类别:Standard Grant
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资助金额:$3.0万
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财政年份:1992
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负责人:Luca Dieci
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依托单位:
Mathematical Sciences: Numerical Aspects of Riccati Transformation, Invariant Manifold Approximation, and Connected Issues
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批准号:9104564
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项目类别:Standard Grant
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资助金额:$3.92万
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财政年份:1991
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负责人:Luca Dieci
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依托单位:
On the Numerical Solution of Differential and Riccati Equations, and Related Matters
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批准号:8802762
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项目类别:Standard Grant
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资助金额:$4.55万
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财政年份:1988
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负责人:Luca Dieci
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依托单位:
国内基金
海外基金
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