结构扰动下的瞬态动力学:桥接非结构和结构伪谱

IF 2.8 2区 数学 Q1 MATHEMATICS, APPLIED
Nicola Guglielmi, Christian Lubich
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引用次数: 0

摘要

SIAM数值分析杂志,第63卷,第2期,908-930页,2025年4月。摘要。引入结构稳定半径作为评价矩阵结构扰动下线性微分方程解的暂态界的鲁棒性的一个量。这适用于一般的线性结构,如具有给定稀疏模式的复矩阵或实矩阵,或具有限制范围和橙色的矩阵,或特殊类,如Toeplitz矩阵。这个概念在概念上将非结构化和结构化伪谱结合在一个联合伪谱中,允许使用非结构化伪谱的可解边界和结构化伪谱的结构化扰动。我们提出并研究了一种计算结构化[数学]稳定半径的算法,该算法通过源自梯度系统的适当离散的秩-1矩阵微分方程来解决特征值优化问题。该算法在计算非结构化和结构化稳定半径方面与已知的rank-1算法的计算成本基本相同。数值实验验证了该算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transient Dynamics under Structured Perturbations: Bridging Unstructured and Structured Pseudospectra
SIAM Journal on Numerical Analysis, Volume 63, Issue 2, Page 908-930, April 2025.
Abstract. The structured [math]-stability radius is introduced as a quantity to assess the robustness of transient bounds of solutions to linear differential equations under structured perturbations of the matrix. This applies to general linear structures such as complex or real matrices with a given sparsity pattern or with restricted range and corange, or special classes such as Toeplitz matrices. The notion conceptually combines unstructured and structured pseudospectra in a joint pseudospectrum, allowing for the use of resolvent bounds as with unstructured pseudospectra and for structured perturbations as with structured pseudospectra. We propose and study an algorithm for computing the structured [math]-stability radius, which solves eigenvalue optimization problems via suitably discretized rank-1 matrix differential equations that originate from a gradient system. The proposed algorithm has essentially the same computational cost as the known rank-1 algorithms for computing unstructured and structured stability radii. Numerical experiments illustrate the behavior of the algorithm.
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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