An Introduction to Sequential Dynamical Systems by Henning S. Mortveit, Christian M. Reidys (auth.)

By Henning S. Mortveit, Christian M. Reidys (auth.)

Sequential Dynamical structures (SDS) are a category of discrete dynamical structures which considerably generalize many facets of structures comparable to mobile automata, and supply a framework for learning dynamical techniques over graphs.

This textual content is the 1st to supply a complete advent to SDS. pushed by means of quite a few examples and thought-provoking difficulties, the presentation deals stable foundational fabric on finite discrete dynamical platforms which leads systematically to an advent of SDS. strategies from combinatorics, algebra and graph idea are used to check a vast diversity of themes, together with reversibility, the constitution of mounted issues and periodic orbits, equivalence, morphisms and relief. in contrast to different books that focus on picking the constitution of assorted networks, this publication investigates the dynamics over those networks by means of concentrating on how the underlying graph constitution impacts the homes of the linked dynamical system.

This booklet is aimed toward graduate scholars and researchers in discrete arithmetic, dynamical platforms conception, theoretical machine technological know-how, and structures engineering who're drawn to research and modeling of community dynamics in addition to their laptop simulations. necessities comprise wisdom of calculus and simple discrete arithmetic. a few machine event and familiarity with straightforward differential equations and dynamical platforms are invaluable yet no longer necessary.

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Extra resources for An Introduction to Sequential Dynamical Systems

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Fn ). Each gene vi is linked or “wired” to ki genes as specified by a map ei : {1, . . , ki } −→ V . The Boolean state xvi of each gene is updated as xvi → fi (xei (1) , . . , xei (ki ) ) , and the whole state configuration is updated synchronously. Traditionally, the value of ki was the same for all the vertices. A gene or vertex v that has state 1 is said to be expressed. A random Boolean network (RBN) can be obtained in the following ways. First, each vertex vi is assigned a sequence of maps f i = (f1i , .

Thus, a symmetric rule f does not depend on the order of its argument. A totalistic function is a function that only depends on (x1 , . . , xn ) through the sum xi (taken in N). Of course, over F2 symmetric and totalistic rules coincide. The radius-2 rules are the rules of the form f : K 5 −→ K that are used to map (xi−2 , xi−1 , xi , xi+1 , xi+2 ) to the new state xi of cell i. In some cases it may be natural or required that we handle the state of a vertex v differently than the states of its neighbor vertices when we update the state xv .

The radius of a one-dimensional CA rule f with neighborhood defined by N is the norm of the largest element of N . 2 is therefore 1. We see that the lattice and the function of a cellular automaton give us an SDS base graph Y as follows. For the vertices of Y we take all the cells. A vertex v is adjacent to all vertices v in n[v]. If v itself is included in n[v], we make the convention of omitting the loop {v, v}. In analogy to SDS, one central goal of CA research is to derive as much information as possible about the global dynamics of the CA map Φf based on known, local properties such as the map f and the neighborhood structure.

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