2011
DOI: 10.1137/100782139
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Stability of a Stochastic Two-Dimensional Non-Hamiltonian System

Abstract: Abstract. We study the largest Lyapunov exponent of the response of a two dimensional non-Hamiltonian system driven by additive white noise. The specific system we consider is the third-order truncated normal form of the unfolding of a Hopf bifurcation. We show that in the small-noise limit the top Lyapunov exponent always approaches zero from below (and is thus negative for noise sufficiently small); we also show that there exist large sets of parameters for which the top Lyapunov exponent is positive. Thus t… Show more

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Cited by 22 publications
(38 citation statements)
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“…Numerical evidence from [12] and Figure 3 suggest that large shear leads to positive top Lyapunov exponent. Unfortunately, we are not able to prove this analytically and formulate this in the following conjecture.…”
Section: Negativity Of Top Lyapunov Exponent and Synchronisationmentioning
confidence: 93%
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“…Numerical evidence from [12] and Figure 3 suggest that large shear leads to positive top Lyapunov exponent. Unfortunately, we are not able to prove this analytically and formulate this in the following conjecture.…”
Section: Negativity Of Top Lyapunov Exponent and Synchronisationmentioning
confidence: 93%
“…The main aim of this paper is to provide a precise mathematical analysis to describe and explain the observations sketched above. Numerical investigations by Lin and Young [25], Wieczorek [29] and Deville et al [12] already highlighted the fact that shear can cause Lyapunov exponents to become positive and induce chaotic behaviour. A first analytical proof of this phenomenon has been given by us in [14] in the case of a stochastically driven limit cycle on the cylinder.…”
Section: Introductionmentioning
confidence: 99%
“…Theorem 3. Let system (1) satisfy (2), ( 3), ( 5), ( 6), and 1 ≤ n ≤ q be an integer such that assumptions (12), ( 13) and (16)…”
Section: Resultsmentioning
confidence: 99%
“…2 ( 12), ( 13), n = q λ n < 0 polynomially stable (12), (13), n > q stable (12), ( 13), ( 16), n ≤ q, σ ≥ n q λ n > δ σ,n/q µ 2 2 unstable Th. 3 ( 12), ( 13), (16),…”
Section: Assumptionsmentioning
confidence: 99%
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