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arXiv 2602.08147math.DSmath-phmath.MPmath.PR
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稀疏耦合线性cocycles的Lyapunov指数

Lyapunov Exponents for Sparsely Coupled Linear Cocycles

Reza Rastegar

AI总结:

本文提出了一种通过稀疏结构和三角控制计算稀疏耦合线性cocycles的Lyapunov指数的方法,并应用于线性系统扰动模型。

摘要:

本文研究了实矩阵的结构乘积,其中顶部Lyapunov指数可通过将动力学减少到可换群的上三角矩阵泛化形式来获取。利用给定的零模式(包括块上三角性和稀疏分解,方便地通过有向稀疏图编码),我们通过结合确定性三角控制和Furstenberg-Kifer引理的适当改进,获得显式、可计算的界限,并在有利情况下得到γ₁的公式。这些估计既适用于温顺(可能确定性)序列,也适用于满足标准积分性的平稳随机随机cocycles。我们还讨论了线性系统扰动模型中的应用,包括低秩更新,其中减少将问题转换为低维或标量cocycles。

英文摘要:

This paper studies structured products of real matrices for which the top Lyapunov exponent can be accessed by reducing the dynamics to an amenable generalization of upper triangular matrices. Exploiting prescribed zero patterns (including block-triangularity and sparse decompositions, conveniently encoded by a directed sparsity graph), we obtain explicit, computable bounds and, in favorable cases, formulas for $γ_1$ by combining deterministic triangular controls with a suitable refinement of the Furstenberg--Kifer lemma for block-triangular products. The estimates apply both to tempered (possibly deterministic) sequences and to stationary ergodic random cocycles under standard integrability. We also discuss applications to perturbation models for linear systems, including low-rank updates, where the reduction converts the problem to lower-dimensional or scalar cocycles.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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