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反应扩散系统离散诱导的随机定态:自洽分析和随机模拟

Discreteness-induced Stochastic Steady State in Reaction Diffusion Systems: Self-consistent Analysis and Stochastic Simulations

Yuichi Togashi, Kunihiko Kaneko

摘要:

提出了一个用于推导反应扩散系统离散诱导随机定态的自洽方程。对于这种形式主义,我们使用所谓的Kuramoto长度,这是分子在其生命周期中扩散的典型距离,最初是为了确定局部波动是否会影响整个系统。我们表明,这仓本长度也是相关的,以确定是否离散的分子是显着的或不。如果仓本长度内的某种物质的分子数量很小且离散,则会导致其他一些化学物质的局部化,这可以加速某些反应。当这种加速影响的浓度的原始分子物种,它示出了一种新的,随机的稳态诱导,不出现在连续极限。一种理论来获得和表征这种状态的介绍,基于自洽方程的化学浓度。通过对一个反应模型的数值模拟,证实了这种随机稳定态的存在,与理论估计相吻合。不同的随机状态的域的形成和共存的报告,这是保持离散性。我们的结果细胞内反应的相关性进行了简要讨论。

英文摘要:

A self-consistent equation to derive a discreteness-induced stochastic steady state is presented for reaction-diffusion systems. For this formalism, we use the so-called Kuramoto length, a typical distance over which a molecule diffuses in its lifetime, as was originally introduced to determine if local fluctuations influence globally the whole system. We show that this Kuramoto length is also relevant to determine whether the discreteness of molecules is significant or not. If the number of molecules of a certain species within the Kuramoto length is small and discrete, localization of some other chemicals is brought about, which can accelerate certain reactions. When this acceleration influences the concentration of the original molecule species, it is shown that a novel, stochastic steady state is induced that does not appear in the continuum limit. A theory to obtain and characterize this state is introduced, based on the self-consistent equation for chemical concentrations. This stochastic steady state is confirmed by numerical simulations on a certain reaction model, which agrees well with the theoretical estimation. Formation and coexistence of domains with different stochastic states are also reported, which is maintained by the discreteness. Relevance of our result to intracellular reactions is briefly discussed.

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