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arXiv 2403.09247nlin.PS
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反应-扩散系统中图灵斑图传播速度的研究

On the speed of propagation in Turing patterns for reaction-diffusion systems

Václav Klika, Eamonn A. Gaffney, Philip K. Maini

AI总结:

本研究分析图灵斑图形成中局部扰动引发的瞬态波,通过边缘稳定性准则与包络方程弱非线性分析估计波速,证明两种方法在分岔点附近给出相同波速,并用Schnakenberg和CDIMA动力学数值验证,强调由扩散和反应动力学决定的特征传播速度对实验比较和瞬态波分析的重要性。

摘要:

本研究探讨了图灵斑图形成中的瞬态波动力学,重点关注从局部扰动中涌现的波。虽然扩散驱动不稳定性的传统研究主要集中于稳态解,但相当多的注意力也已转向理解时空行为,特别是从局部扰动传播斑图的过程。我们使用成熟边缘稳定性准则和包络方程的弱非线性分析来分析这些斑图波。两种方法都提供了波速的估计,但后一种方法还近似了波剖面和振幅。然后,我们在分岔点附近解析地比较这两种方法,并揭示边缘稳定性准则产生的波速估计与弱非线性分析完全相同。此外,我们将这些估计与Schnakenberg和CDIMA(二氧化氯-碘-丙二酸)动力学的数值结果进行了评估。特别地,我们的研究强调了斑图传播特征速度的重要性,该速度由扩散动力学决定,并与图灵系统中的反应动力学存在复杂关系。该速度作为与实验观测比较的关键参数,类似于观测到的斑图长度尺度。此外,更一般地,我们的发现为分析图灵系统中的瞬态波特性提供了系统方法,增进了对斑图形成动态演化的理解。

英文摘要:

This study investigates transient wave dynamics in Turing pattern formation, focusing on waves emerging from localised disturbances. While the traditional focus of diffusion-driven instability has primarily centred on stationary solutions, considerable attention has also been directed towards understanding spatio-temporal behaviours, particularly the propagation of patterning from localised disturbances. We analyse these waves of patterning using both the well-established marginal stability criterion and weakly nonlinear analysis with envelope equations. Both methods provide estimates for the wave speed but the latter method, in addition, approximates the wave profile and amplitude. We then compare these two approaches analytically near a bifurcation point and reveal that the marginal stability criterion yields exactly the same estimate for the wave speed as the weakly nonlinear analysis. Furthermore, we evaluate these estimates against numerical results for Schnakenberg and CDIMA (chlorine dioxide-iodine-malonic acid) kinetics. In particular, our study emphasises the importance of the characteristic speed of pattern propagation, determined by diffusion dynamics and a complex relation with the reaction kinetics in Turing systems. This speed serves as a vital parameter for comparison with experimental observations, akin to observed pattern length scales. Furthermore, more generally, our findings provide systematic methodologies for analysing transient wave properties in Turing systems, generating insight into the dynamic evolution of pattern formation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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