Why do complex systems look critical?
March 20, 3:30pm - 4:30pm
Mānoa Campus, Watanabe Hall 112
Department of Physics and Astronomy Colloquium: Prof. Matteo Marsili, International Center for Theoretical Physics (ICTP), to speak on "Why do complex systems look critical?"
The study of complex systems is limited by the fact that only few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the systems behavior. In addition, empirical data typically under sample the space of possible states. We study a generic framework where a complex system is seen as a system of many interacting degrees of freedom, which are known only in part, that optimize a given function. We show that the underlying
distribution with respect to the known variables has the Boltzmann form,
with a temperature that depends on the number of unknown variables. In
particular, when the influence of the unknown degrees of freedom on the
known variables is not too irregular, the temperature decreases as the
number of variables increases. This suggests that models can be
predictable only when the number of relevant variables is less than a
critical threshold. Concerning sampling, we argue that the information
that a sample contains on the behavior of the system is quantified by the
entropy of the frequency with which different states occur. This allows us
to characterize the properties of "maximally informative samples": Within a simple approximation, the most informative frequency size distributions
have power law behavior and Zipf's law emerges at the crossover between the under sampled regime and the regime where the sample contains enough
statistics to make inferences about the behavior of the system. These ideas are illustrated in some applications, showing that they can be used
to identify relevant variables or to select most informative representations of data, e.g. in data clustering.
Physics and Astronomy, Mānoa Campus
Dr. Frederick Harris, (808) 956-2940, email@example.com