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International Conference on Complex Systems (ICCS2006)

Complex Stellar Dynamics and Galactic Patterns Formation

Jean-Claude Torrel

Claude Lattaud

Jean-Claude Heudin

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     Last modified: May 29, 2006

In cosmology, confrontation between numerical simulation and data resulting from observation shows to main problems :
+ results given by the simulation models highly depend on number of elements used. As a realistic number of elements should be around 10^41 for a typical spiral galaxy, there is a problem of computing power.
+ a shift exists between observation and numerical simulation on spheroidal galac­tic formation : angular velocity of peripheral stars get by numerical simulation does not match with observation.

This paper defines a new approach for cosmological simulation based on complex sys­tems theroy : we use a hierarchical multi-­agents system to study the complexity of stellar dynamics. Most cosmological simulations use point-­mass particles and global laws.
Our approach is different : agents and their interactions are aggregated to differ­ents higher-­level agents. At each level of the model the behavior of these higher-­level agents emerge from the behavior of individual lower-­level agents. Our model uses physicaly-­based laws and agent ­interactions to present stellar structures has the re­sult of self­-organisation.
By parameterizing these laws and interactions, we obtain a space of possible universes. This space is qualitatively and quantitatively classified in complexity classes. We try to establish a link with Wolfram's classes of complexity (ordered, choatic, complex) and characterize what leads to complex patterns. Never­theless a strong bond with cosmology is kept by showing the capacity of our model to exibit structures close to thoses of the observable universe.

By replacing the universe "as­-we-­know­-it" in a larger picture of universe "as-­it-­could-­be" we try to understand patterns formation and dynamics evolution. In this framework, this paper focus will be given to the hierarchical multi-­agents model definition and its validation process.

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