Biancalani Tommaso, Fanelli Duccio, Di Patti Francesca
Dipartimento di Fisica, Università degli Studi di Firenze, via G Sansone 1, 50019 Sesto Fiorentino, Florence, Italy.
Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Apr;81(4 Pt 2):046215. doi: 10.1103/PhysRevE.81.046215. Epub 2010 Apr 27.
A stochastic version of the Brusselator model is proposed and studied via the system size expansion. The mean-field equations are derived and shown to yield to organized Turing patterns within a specific parameters region. When determining the Turing condition for instability, we pay particular attention to the role of cross-diffusive terms, often neglected in the heuristic derivation of reaction-diffusion schemes. Stochastic fluctuations are shown to give rise to spatially ordered solutions, sharing the same quantitative characteristic of the mean-field based Turing scenario, in term of excited wavelengths. Interestingly, the region of parameter yielding to the stochastic self-organization is wider than that determined via the conventional Turing approach, suggesting that the condition for spatial order to appear can be less stringent than customarily believed.
提出了 Brusselator 模型的一个随机版本,并通过系统规模展开进行研究。推导了平均场方程,结果表明在特定参数区域内会产生有组织的图灵模式。在确定不稳定性的图灵条件时,我们特别关注交叉扩散项的作用,在反应扩散方案的启发式推导中,交叉扩散项常常被忽略。结果表明,随机涨落会产生空间有序解,在激发波长方面,这些解与基于平均场的图灵情形具有相同的定量特征。有趣的是,产生随机自组织的参数区域比通过传统图灵方法确定的区域更宽,这表明出现空间有序的条件可能比通常认为的要宽松。