首页> 外文会议>IUTAM Symposium on Nonlinear Stochastic Dynamics; Aug 26-30, 2002; Monticello, Illinois >THE REDUCTION OF POTENTIAL DIFFUSIONS TO FINITE STATE MARKOV CHAINS AND STOCHASTIC RESONANCE
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THE REDUCTION OF POTENTIAL DIFFUSIONS TO FINITE STATE MARKOV CHAINS AND STOCHASTIC RESONANCE

机译:有限状态马尔可夫链和随机共振的势能减小

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Consider a dynamical system describing the motion of a particle in a double well potential with a periodic perturbation of very small frequency, and a white noise perturbation of intensity ε. If its trajectories amplify the small periodic perturbation in a 'best possible way', it is said to be in stochastic resonance. A lower bound for the ratio of amplitude and logarithm of the period above which quasi-deterministic periodic behavior can be observed is obtained via large deviations theory. However, to obtain optimality, periodicity of trajectories has to be studied by means of a measure of quality of tuning such as spectral power amplification. In the particular setting where the potential alternates every half period between two spatially antisymmetric double well states we encounter a surprise. The stochastic resonance pattern is not correctly described by the reduced dynamics associated with a two state Markov chain whose periodic hopping rates between the potential minima mimic the large (spatial) scale motion of the diffusion. Only if small scale fluctuations inside the potential wells where the diffusion spends most of its time are carefully eliminated, the reduced dynamics is robust.
机译:考虑一个动力学系统,该系统描述粒子在双阱势中的运动,其周期的扰动频率非常小,而白噪声的扰动强度为ε。如果其轨迹以“最佳可能的方式”放大小的周期性扰动,则可以说是随机共振。通过大偏差理论获得了周期的幅度与对数之比的下限,在该下限之上可以观察到准确定的周期性行为。然而,为了获得最优性,必须借助于诸如频谱功率放大之类的调谐质量的措施来研究轨迹的周期性。在特定的环境中,电势在两个空间反对称双阱状态之间每半周期交替出现,我们会遇到一个惊喜。随机共振模式没有正确地描述为与二态马尔可夫链相关的动力学降低,该二态马尔可夫链的电位最小值之间的周期性跳跃率模仿了扩散的大(空间)运动。只有仔细消除了扩散花费大部分时间的潜在阱内部的小规模波动,降低的动力学才具有鲁棒性。

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