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Research Article | Open Access

Lower bounds for the maximal Lyapunov exponent in one-parameter families of linear differential systems

Institute of Mathematics of the National Academy of Sciences of Belarus, st. Surganova, 11 220072, Minsk, Republic of Belarus
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Abstract

We consider a two-dimensional, nonautonomous, homogeneous system of linear ordinary differential equations that depends on the real parameter μ. It is assumed that the Cauchy operator for each unit time interval is a product of a rotation matrix by an angle, the value of which is an affine function of μ, and of a diagonal matrix with a unit determinant, which is chosen to be close to a constant and whose norm is sufficiently large to guarantee the monotonicity with respect to μ of polar angle for any solution to the system. This class of systems contains an example of a non-almost-reducible linear system with limit-periodic coefficients constructed by V. M. Millionshchikov. We use his rotation method to establish the positivity of the maximal Lyapunov exponent in one-parameter family for some set of parameter values that has positive Lebesgue measure. To derive this result, we prove the monotonicity with respect to μ of angles in singular-value decomposition for Cauchy operator and moreover that its derivative is separated from zero. Further, the angle itself increases as a monotonic linear function of t. Both of these properties, by induction, give us a small average loss for the Cauchy operator norm on exponentially growing time intervals, which leads to its exponential growth as a function of t.

CLC number: 34A30, 34D08

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AIMS Mathematics
Pages 12178-12203

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Cite this article:
Lipnitskii A. Lower bounds for the maximal Lyapunov exponent in one-parameter families of linear differential systems. AIMS Mathematics, 2026, 11(4): 12178-12203. https://doi.org/10.3934/math.2026500

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Received: 22 December 2025
Revised: 23 April 2026
Accepted: 24 April 2026
Published: 30 April 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)