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 <title>ultra-complex systems and categorical dynamics</title>
 <name>CategoricalDynamics</name>
 <created>2008-12-16 16:36:02</created>
 <modified>2009-02-18 23:46:24</modified>
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 <defines>
	<concept>ultra-complex systems</concept>
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	<term>categorical dynamics</term>
	<term>dynamics in categories</term>
	<term>ultra-complex systems</term>
	<term>natural transformations</term>
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 <content>\section{Categorical Dynamics}
A relatively recent area (1958- ) of Category Theory, Higher Dimensional Algebra and mathematical physics developing applications of categories, functors, natural transformations, higher dimensional categories and supercategories to dynamics in classical, quantum, complex and super-complex systems.

One can represent in square categorical diagrams the emergence of ultra-complex
dynamics from the super-complex dynamics of human organisms coupled {\em via} social interactions in characteristic patterns represented by Rosetta biogroupoids, together with the complex--albeit inanimate--systems with chaos. With the emergence of the ultra-complex system of the human mind-- based on the super-complex human organism-- there is always an associated
progression towards higher dimensional algebras from the lower
dimensions of human neural network dynamics and the simple algebra
of physical dynamics, as shown in the following, essentially \emph{non-commutative} categorical diagram.

\begin{definition}
An \emph{ultra-complex system, $U_{CS}$} is defined as an object representation in the following non-commutative
diagram of systems and dynamic system morphisms or `dynamic transformations':

$$ \xymatrix@C=5pc{[SUPER-COMPLEX] \ar [r] ^{(\textbf{Higher
Dim})} \ar[d] _{\Lambda}&amp; ~~~(U_{CS}= ULTRA-COMPLEX) \ar [d]^{onto}\\ COMPLEX&amp;
\ar [l] ^{(\textbf{Generic Map})}[SIMPLE]} $$
\end{definition}
Note that the above diagram is indeed not `natural' (i.e. it is not commutative) for reasons
related to the emergence of the higher dimensions of the super--complex
(biological/organismic) and/or ultra--complex (psychological/neural network dynamic) levels in comparison with
the low dimensions of either simple (physical/classical) or complex (chaotic) dynamic systems.</content>
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