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Introduction to the Modeling and Analysis of Complex Systems

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220 CHAPTER 12. CELLULAR AUTOMATA II: ANALYSISI am well aware that <strong>the</strong> explanation above is still vague <strong>and</strong> somewhat cryptic, solet’s discuss <strong>the</strong> detailed steps <strong>of</strong> how this method works. Here are typical steps <strong>of</strong> howrenormalization group analysis is done:1. Define a property <strong>of</strong> a “portion” <strong>of</strong> <strong>the</strong> system you are interested in. This propertymust be definable <strong>and</strong> measurable for portions <strong>of</strong> any size, like a material property<strong>of</strong> matter. For analyzing percolation, it is typically defined as <strong>the</strong> probability for aportion <strong>to</strong> conduct a fire or a disease from one side <strong>to</strong> ano<strong>the</strong>r side through it.2. Calculate <strong>the</strong> property at <strong>the</strong> smallest scale, p 1 . This is usually at <strong>the</strong> single-celllevel, which should be immediately obtainable from a model parameter.3. Derive a ma<strong>the</strong>matical relationship between <strong>the</strong> property at <strong>the</strong> smallest scale, p 1 ,<strong>and</strong> <strong>the</strong> same property at a one-step larger scale, p 2 = Φ(p 1 ). This derivation isdone by using single cells as building blocks <strong>to</strong> describe <strong>the</strong> process at a largerscale (e.g., two-by-two blocks)4. Assume that <strong>the</strong> relationship derived above can be applied <strong>to</strong> predict <strong>the</strong> propertyat even larger scales, <strong>and</strong> <strong>the</strong>n study <strong>the</strong> asymp<strong>to</strong>tic behavior <strong>of</strong> <strong>the</strong> iterative mapp s+1 = Φ(p s ) when scale s goes <strong>to</strong> infinity.Let’s see what <strong>the</strong>se steps actually look like with a specific forest fire CA model withMoore neighborhoods. The essential parameter <strong>of</strong> this model is, as discussed in Section11.5, <strong>the</strong> density <strong>of</strong> trees in a space. This tree density was called p in <strong>the</strong> previous chapter,but let’s rename it q here, in order <strong>to</strong> avoid confusion with <strong>the</strong> property <strong>to</strong> be studied in thisanalysis. The key property we want <strong>to</strong> measure is whe<strong>the</strong>r a portion <strong>of</strong> <strong>the</strong> system (a block<strong>of</strong> <strong>the</strong> forest in this context) can conduct fire from one side <strong>to</strong> ano<strong>the</strong>r. This probability isdefined as a function <strong>of</strong> scale s, i.e., <strong>the</strong> length <strong>of</strong> an edge <strong>of</strong> <strong>the</strong> block (Fig. 12.4). Let’scall this <strong>the</strong> conductance probability for now.The conductance probability at <strong>the</strong> lowest level, p 1 , is simply <strong>the</strong> probability for a tree<strong>to</strong> be present in a single cell (i.e., a 1×1 block). If <strong>the</strong>re is a tree, <strong>the</strong> fire will be conducted,but if not, it won’t. Therefore:p 1 = q (12.11)Next, we calculate <strong>the</strong> conductance probability at a little larger scale, p 2 . In so doing,we use p 1 as <strong>the</strong> basic property <strong>of</strong> a smaller-sized building block <strong>and</strong> enumerate what are<strong>the</strong>ir arrangements that conduct <strong>the</strong> fire across a two-cell gap (Fig. 12.5).As you see in <strong>the</strong> figure, if all four cells are occupied by trees, <strong>the</strong> fire will definitelyreach <strong>the</strong> o<strong>the</strong>r end. Even if <strong>the</strong>re are only three or two trees within <strong>the</strong> 4 area, <strong>the</strong>re are

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