Friday, January 26, 2007

Physics of religion

Here's an interesting way to think about the spread of religion. Intuitively, it spreads like an infectious disease, so it could be modeled mathematically as a process of contagion, such as influenza or plague. Now some physicists have proposed modeling it like the process of crystallizaton:

Physicists make religion crystal clear
The rise and fall in the popularity of major religions can be described using the same mathematics that is used to model crystallization processes, claim physicists in Belgium. The researchers have modelled the time evolution of the numbers of adherents to religions and claim that their work sheds light on an important social phenomenon -- how a religion such as Christianity can grow rapidly from very small beginnings (Europhysics Letters (EPL) to be published).

Physicists have a long history of applying statistical models to the study of human behaviour and have tackled problems as diverse as the performance of financial markets and the spread of languages. Now, Marcel Ausloos and Filippo Petroni at the University of Liege have turned their attention to the dynamics of religion by relating the emergence, growth and demise of religions to phase transitions that occur during crystallization and other physical processes.

It seems to me that this sort of technique could be applied not only to religions as a whole, but also to smaller-scale phenomena, such as the explosive growth of evangelical Christian megachurches in the U. S. Many of these operations serve thousands of customers and seem to spring up almost overnight. They tend to be started by charismatic individuals who have a special flair for showmanship, such as Ted Haggard (blogged about here).

Of course, some of the ideas behind this line of thinking have a long history – in such fields as crowd psychology. It would be interesting if the research mentioned above could actually produce models that yield quantitative predictions for the nucleation and growth of megachurches in a geographical area, based on sociological variables (demographics, population density, etc.).

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