Skip to main content
Mathematics LibreTexts

14: Continuous Field Models II - Analysis

  • Page ID
    7849
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    • 14.1: Finding Equilibrium States
      One nice thing about PDE-based continuous field models is that, unlike CA models, everything is still written in smooth differential equations so we may be able to conduct systematic mathematical analysis to investigate their dynamics (especially their stability or instability) using the same techniques as those we learned for non-spatial dynamical systems in Chapter 7. The first step is, as always, to find the system’s equilibrium states.
    • 14.2: Variable Rescaling
      Variable rescaling of continuous field models comes with yet another bonus variable, i.e., space, which you can rescale to potentially eliminate more parameters from the model. In a 2-D or higher dimensional space, you can, theoretically, have two or more spatial variables to rescale independently. But the space is usually assumed to be isotropic (i.e., there is no difference among the directions of space) in most spatial models, so it may not be practically meaningful to use different rescaling
    • 14.3: Linear Stability Analysis of Continuous Field Models
      We can apply the linear stability analysis to continuous field models. This allows us to analytically obtain the conditions for which a homogeneous equilibrium state of a spatial system loses its stability and thereby the system spontaneously forms non-homogeneous spatial patterns. Note again that the homogeneous equilibrium state discussed here is no longer a single point, but it is a straight line (or a flat plane) that covers the entire spatial domain.
    • 14.4: Linear Stability Analysis of Reaction-Diffusion Systems
      You may have found that the linear stability analysis of continuous field models isn’t as easy as that of non-spatial models. For the latter, we have a very convenient tool called the Jacobian matrices, and the stability analysis is just calculating a Jacobian matrix and then investigating its eigenvalues. Everything is so mechanistic and automatic, compared to what we went through in the previous section. You may wonder, aren’t there any easier shortcuts in analyzing the stability of continuous


    This page titled 14: Continuous Field Models II - Analysis is shared under a CC BY-NC-SA 3.0 license and was authored, remixed, and/or curated by Hiroki Sayama (OpenSUNY) via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.