Adaptive Low-Rank Approximations for Operator Equations: Accuracy Control and Computational Complexity

Adaptive Low-Rank Approximations for Operator Equations: Accuracy Control and Computational Complexity
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算子方程的自适应低阶近似:精度控制和计算复杂性

DOI:
10.1090/conm/754/15151
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发表时间:
2020
期刊:
Contemporary mathematics
影响因子:
--
通讯作者:
Dahmen, W.
Dahmen, W.
中科院分区:
--
文献类型:
--
作者:
Bachmayr, M.;Dahmen, W.

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掌握巨大规模的计算任务的挑战往往往往压倒了质疑数值结果的准确性。这并不意味着离散设置内的精度,这本身也可能是远远不明显的病态问题或迭代求解器时,涉及。精度控制计算是指数值近似与相关度量中基本连续问题的精确解的偏差,这是最初的兴趣所在。一个数值结果的准确性是否可以被严格地证明--这是一个在不确定性量化的背景下特别重要的问题,因为许多可能的不确定性来源相互作用。这是贯穿本文的指导性问题,本文回顾了高空间维度问题的低秩近似方法的最新发展。特别是,我们强调的作用,自适应处理这种强非线性的方法,集成在一个自然的方式问题的离散和连续的准确性。
The challenge of mastering computational tasks of enormous size tends to frequently override questioning the quality of the numerical outcome in terms of accuracy. By this we do not mean the accuracy within the discrete setting, which itself may also be far from evident for ill-conditioned problems or when iterative solvers are involved. By accuracy-controlled computation we mean the deviation of the numerical approximation from the exact solution of an underlying continuous problem in a relevant metric, which has been the initiating interest in the first place. Can the accuracy of a numerical result be rigorously certified - a question that is particularly important in the context of uncertainty quantification, when many possible sources of uncertainties interact. This is the guiding question throughout this article, which reviews recent developments of low-rank approximation methods for problems in high spatial dimensions. In particular, we highlight the role of adaptivity when dealing with such strongly nonlinear methods that integrate in a natural way issues of discrete and continuous accuracy.
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