论文标题

莱维噪声驱动的开关间歇性中的1/f噪声和异常缩放

1/f noise and anomalous scaling in Lévy noise-driven on-off intermittency

论文作者

van Kan, Adrian, Pétrélis, François

论文摘要

开关间歇性发生在接近分叉点的非平衡物理系统中,其特征是在“状态和小振幅”状态的大振幅“状态和小振幅”状态之间进行良性切换。 LévyOn-On-Ow-Ow-Own-Ownertencience是最近引入了对乘法Lévy噪声的开关间歇性的概括,这取决于稳定性参数$α$和偏斜的参数$β$。在这里,我们通过利用LévyFlights的首次计时时间统计数据的已知确切结果来获得有关LévyOn-On-Ow-Ow-Ow-Ow-Off间歇性的两个新结果。首先,我们通过一种启发式方法,首次通过任意lévy噪声参数$(α,β)$明确计算异常的临界指数,以补充先前的结果。使用分数Fokker-Planck方程的数值解验证了预测。其次,我们得出了Lévyon-On-Ow-Ow-Off Intermittency的Power Spectrum $ s(f)$,并表明它在低频$ f $下显示了功率定律$ s(f)\ propto f^κ$,其中$κ\ in(-1,0)$取决于噪声参数$α,β$。根据$(α,β)$,获得了$κ$的明确表达。使用Lévyon-On-Ow-Ow-Ow-Owntertilence的长时间序列实现来验证这些预测。我们的发现有助于阐明不平衡,幂律分布的波动的不稳定性,强调它们的性质可能与高斯波动的情况明显不同。

On-off intermittency occurs in nonequilibrium physical systems close to bifurcation points and is characterised by an aperiodic switching between a large-amplitude "on" state and a small-amplitude "off" state. Lévy on-off intermittency is a recently introduced generalisation of on-off intermittency to multiplicative Lévy noise, which depends on a stability parameter $α$ and a skewness parameter $β$. Here, we derive two novel results on Lévy on-off intermittency by leveraging known exact results on the first-passage time statistics of Lévy flights. First, we compute anomalous critical exponents explicitly as a function of arbitrary Lévy noise parameters $(α,β)$ for the first time, by a heuristic method, complementing previous results. The predictions are verified using numerical solutions of the fractional Fokker-Planck equation. Second, we derive the power spectrum $S(f)$ of Lévy on-off intermittency and show that it displays a power law $S(f)\propto f^κ$ at low frequencies $f$, where $κ\in (-1,0)$ depends on the noise parameters $α,β$. An explicit expression for $κ$ is obtained in terms of $(α,β)$. The predictions are verified using long time series realisations of Lévy on-off intermittency. Our findings help shed light on instabilities subject to non-equilibrium, power-law-distributed fluctuations, emphasizing that their properties can differ starkly from the case of Gaussian fluctuations.

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