Researchers at the University of Warwicks Physics Departments Centre for Fusion, Space and Astrophysics have found a powerful technique that could be used to detect precisely when ordered patterns form in everything from plasma in the solar wind and fusion reactors, to crowds of people, or flocks of birds. The technique could even be used to find unusual patterns in stock market behaviour.
The researchers began their work in a research group interested in plasmas. These are difficult to study at the best of times because the opportunities to view plasma in the solar wind are limited by the small number of satellites observing such things and plasmas in nuclear fusion reactions are obviously not easily accessible.
The University of Warwick researchers were particularly interested in how complex systems such as plasma, crowds of people, or flocks of birds suddenly move from a disordered random state to an ordered one. To crack this problem they developed a technique that combines an earlier study of the flocking behavior of large groups of birds and insects with information technology used to correlate information from a range of parallel signals.
University of Warwick physicist Robert Wicks hit upon the idea of using an information technology tool called mutual information that can detect patterns and correlations from a very small set of points (typically 10 within a large system). In theory he believed that this method would be much more accurate than the normal statistical analysis of such dynamic systems such as crowds or plasmas and it should be particularly good at picking up the phase transitions from disorder to order in such complicated systems.
Initially the researchers were stumped as to how to test this theory. The very complexity (and often inaccessibility) that caused the observation problems they were trying to overcome meant there was no accurate real world date set to check their new tech
Contact: Robert Wicks
University of Warwick