Fluctuation-driven Turing patterns
Fluctuation-driven Turing patterns
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DOI：
10.1103/physreve.84.011112
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发表时间：
2011-07-11
影响因子：
2.4
通讯作者：
Goldenfeld, Nigel
中科院分区：
文献类型：
--
作者：
Butler, Thomas;Goldenfeld, Nigel
依赖图灵机制的扩散驱动模式形成模型在许多科学领域都有应用。然而，许多此类模型都存在缺陷，即为了预测空间模式的形成，需要对参数进行精细调整，或者对系统组成部分的扩散率进行不切实际的尺度分离。在一个非常通用的生态模式形成模型的背景下，我们表明，在图灵模型中纳入内禀噪声会导致“准模式”的形成，这些准模式在参数空间的一般区域形成，并且在实验上可与标准图灵模式区分开来。准模式的存在消除了在将图灵模型应用于实际系统时进行非物理的精细调整或尺度分离的需要。
Models of diffusion-driven pattern formation that rely on the Turing mechanism are utilized in many areas of science. However, many such models suffer from the defect of requiring fine tuning of parameters or an unrealistic separation of scales in the diffusivities of the constituents of the system in order to predict the formation of spatial patterns. In the context of a very generic model of ecological pattern formation, we show that the inclusion of intrinsic noise in Turing models leads to the formation of "quasipatterns" that form in generic regions of parameter space and are experimentally distinguishable from standard Turing patterns. The existence of quasipatterns removes the need for unphysical fine tuning or separation of scales in the application of Turing models to real systems.