Accurate dynamics from self-consistent memory in stochastic chemical reactions with small copy numbers

Moshir Harsh, Peter Sollich
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引用次数: 2

Abstract

Abstract We present a method that captures the fluctuations beyond mean field in chemical reactions in the regime of small copy numbers and hence large fluctuations, using self-consistently determined memory : by integrating information from the past we can systematically improve our approximation for the dynamics of chemical reactions. This memory emerges from a perturbative treatment of the effective action of the Doi-Peliti field theory for chemical reactions. By dressing only the response functions and by the self-consistent replacement of bare responses by the dressed ones, we show how a very small class of diagrams contributes to this expansion, with clear physical interpretations. From these diagrams, a large sub-class can be further resummed to infinite order, resulting in a method that is stable even for large values of the expansion parameter or equivalently large reaction rates. We demonstrate this method and its accuracy on single and multi-species binary reactions across a range of reaction constant values.
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小拷贝数随机化学反应中自洽记忆的精确动力学
摘要:本文提出了一种方法,利用自一致决定的记忆,在小拷贝数和大波动的情况下,捕捉化学反应中超过平均场的波动:通过整合过去的信息,我们可以系统地改进对化学反应动力学的近似。这种记忆来自于Doi-Peliti场理论对化学反应有效作用的摄动处理。通过仅修饰响应函数,以及用修饰后的响应自一致地替换裸响应,我们展示了一组非常小的图表如何有助于这种扩展,并具有清晰的物理解释。从这些图中,一个大的子类可以进一步恢复到无限阶,从而得到即使在大的展开参数值或相当大的反应速率下也是稳定的方法。我们证明了这种方法及其在反应常数范围内的单种和多种二元反应上的准确性。
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