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Computing Invariant Dynamics for Differential Equations: Spectral Methods, Errors, and Computer Assisted Proof

机译:计算微分方程的不变动力学:谱方法,误差和计算机辅助证明

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摘要

The qualitative theory of dynamical systems is concerned with studying the long time behavior discrete and continuous time models such as nonlinear differential equations. The long time behavior of such models is organized by landmarks called invariant sets. For complicated nonlinear equations these invariant sets are difficult to study via pen and paper analysis, and we typically employ numerical simulations to gain insights into the dynamics. If we now think of these computer assisted insights as mathematical conjectures, then it is natural to ask how we might obtain proofs. Since the conjectures themselves originate with the computer it is not surprising that computer assistance is sometimes needed to prove the desired theorems. In this talk I will discuss some numerical methods for computing invariant sets for nonlinear differential equations, and indicate how these computations can be distilled into mathematical theorems. A byproduct of this discussion is that we obtain `validatedu27 a posteriori error bounds on our scientific computations.
机译:动力学系统的定性理论涉及研究长时间行为的离散和连续时间模型,例如非线性微分方程。这种模型的长期行为由称为不变集的界标组织。对于复杂的非线性方程,很难通过笔和纸分析来研究这些不变集,并且我们通常使用数值模拟来获得对动力学的见解。如果我们现在将这些计算机辅助的见解视为数学猜想,那么自然会问我们如何获得证明。由于猜想本身是由计算机产生的,因此有时需要计算机辅助来证明所需的定理也就不足为奇了。在本次演讲中,我将讨论一些用于计算非线性微分方程不变集的数值方法,并指出如何将这些计算提炼为数学定理。讨论的副产品是,我们在科学计算中获得了“后验误差界限”。

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    James J. D. Mireles;

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  • 年度 2015
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