Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany.
Chaos. 2022 Jan;32(1):013103. doi: 10.1063/5.0070036.
Collective synchronization in a large population of self-sustained units appears both in natural and engineered systems. Sometimes this effect is in demand, while in some cases, it is undesirable, which calls for control techniques. In this paper, we focus on pulsatile control, with the goal to either increase or decrease the level of synchrony. We quantify this level by the entropy of the phase distribution. Motivated by possible applications in neuroscience, we consider pulses of a realistic shape. Exploiting the noisy Kuramoto-Winfree model, we search for the optimal pulse profile and the optimal stimulation phase. For this purpose, we derive an expression for the change of the phase distribution entropy due to the stimulus. We relate this change to the properties of individual units characterized by generally different natural frequencies and phase response curves and the population's state. We verify the general result by analyzing a two-frequency population model and demonstrating a good agreement of the theory and numerical simulations.
在自然和工程系统中都会出现大量自维持单元的集体同步现象。有时这种效应是需要的,而在某些情况下,它是不需要的,这就需要控制技术。在本文中,我们专注于脉动控制,目的是增加或减少同步水平。我们通过相位分布的熵来量化这个水平。受神经科学中可能应用的启发,我们考虑了实际形状的脉冲。利用噪声 Kuramoto-Winfree 模型,我们搜索最优的脉冲轮廓和最优的刺激相位。为此,我们推导出了由于刺激引起的相位分布熵的变化的表达式。我们将这种变化与个体单元的特性联系起来,这些特性由一般不同的自然频率和相位响应曲线以及群体的状态来表征。我们通过分析一个双频群体模型验证了这一一般结果,并展示了理论和数值模拟的良好一致性。