噪声引起的集体动力学波动
Noise-induced volatility of collective dynamics
摘要：
“噪声引起的波动性”是指在存在快速变化的外部信号和中间噪声水平的情况下，可调单元的集体动态中的波动水平增加的现象。这种现象的典型特征是，除了波动水平的增加之外，系统的响应变得与外部驱动力无关，使其不同于随机共振。数值模拟和分析理论的随机动态版本的伊辛模型定期和随机网络证明了这种现象的普遍性和鲁棒性，这被认为是一个可能的原因过度波动的金融市场，增强有效温度在各种各样的平衡系统和强大的选择性反应的免疫系统的复杂的生物有机体。广泛的数值模拟相比，平均场论不同的网络拓扑结构。
英文摘要：
"Noise-induced volatility" refers to a phenomenon of increased level of fluctuations in the collective dynamics of bistable units in the presence of a rapidly varying external signal, and intermediate noise levels. The archetypical signature of this phenomenon is that --beyond the increase in the level of fluctuations-- the response of the system becomes uncorrelated with the external driving force, making it different from stochastic resonance. Numerical simulations and an analytical theory of a stochastic dynamical version of the Ising model on regular and random networks demonstrate the ubiquity and robustness of this phenomenon, which is argued to be a possible cause of excess volatility in financial markets, of enhanced effective temperatures in a variety of out-of-equilibrium systems and of strong selective responses of immune systems of complex biological organisms. Extensive numerical simulations are compared with a mean-field theory for different network topologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
