论文标题
建模主动非马克维亚振荡
Modelling Active Non-Markovian Oscillations
论文作者
论文摘要
建模活动系统的嘈杂振荡是物理和生物学中目前面临的挑战之一。由于这种过程的物理机制通常很难识别，因此我们提出了一个线性随机模型，该模型由非马克维亚双向噪声驱动，该模型能够产生自我维持的周期性振荡。我们为模型的最相关的动力学和热力学特性得出分析预测。这种最小的模型证明了从实验数据中提取的牛肉囊中头发束的精确双束样振荡运动。根据这些数据的一致并一致，我们估计维持这种主动振荡所需的功率为每次振荡周期一百$ k_b t $的顺序。
Modelling noisy oscillations of active systems is one of the current challenges in physics and biology. Because the physical mechanisms of such processes are often difficult to identify, we propose a linear stochastic model driven by a non-Markovian bistable noise that is capable of generating self-sustained periodic oscillation. We derive analytical predictions for most relevant dynamical and thermodynamic properties of the model. This minimal model turns out to describe accurately bistable-like oscillatory motion of hair bundles in bullfrog sacculus, extracted from experimental data. Based on and in agreement with these data, we estimate the power required to sustain such active oscillations to be of the order of one hundred $k_B T$ per oscillation cycle.
