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STOCHASTICITY DEFINED EVOLUTION IN DYNAMICAL SYSTEMS AND COMPLEX NETWORKS

机译:动态系统和复杂网络中的随机定义了演化

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Nonlinear stochastic differential equations are often encountered in the quantitative modelling of phenomena in both natural and social sciences. One of the most important questions is the robustness and stability of the system. It is usually computationally expense to find it out by direct and real time calculation. Here we report a novel method allowing us to find a global measure of the stability without direct real time computation. It is similar to the finding of a "potential" in physical sciences. To be specific dynamics near and far from thermal equilibrium is studied within a new framework of stochastic differential equations. A stochasticity-dissipation relation is proposed to emphasize the equal importance of the stochastic and deterministic forces in describing the system's evolution and destination. An explicit novel construction of the potential energy is illustrated through a gauged ψ-decomposition. Possible directions to extend the present study to generic situations are pointed out.
机译:自然和社会科学两种现象的定量建模中常常遇到非线性随机微分方程。最重要的问题之一是系统的稳健性和稳定性。通过直接和实时计算来查找它通常是计算的费用。在这里,我们报告了一种新的方法,允许我们在没有直接实时计算的情况下找到稳定性的全球度量。它类似于在物理科学中找到“潜力”。在随机微分方程的新框架内研究了附近的特定动态和远离热平衡。提出了一种随机耗散关系,以强调随机和确定性力量在描述系统的演变和目的地时的平等重要。通过测量的ψ分解示出了显式新颖的潜在能量的结构。指出了将本研究扩展到通用情况的可能指示。

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