Lattice Statistical Physics

Lattice statistical physics analyses complex statistics of sytems on regular lattices and includes models of cooperative phase transitions (Potts-Ising models) as well as statistical models such as percolation and self-avoiding walks.
There are five main techniques for analysing lattice statistics problems: Statistical physics has provided concrete examples of a number of concepts that are believed to be important in the study of complex systems. (MORE).

MASCOS project on Stochastic Cellular Automata

The objectives of this project are:
  • understanding the behaviour of deterministic cellular automata by considering them as limits of stochastic cellular automata which can be investigated using the standard techniques of lattice statistical physics listed above.
  • using stochastic cellular automata to model real-world systems.
  • searching for further insight into the behaviour of the corner-transfer-matrix method for series expansion and variational approximation.
  • investigation general statistical problems, including inverse problems, in systems with complex behaviour.
  • Finite Lattice Method (FLM) of series expansion

    The FLM has proved to be a very powerful technique for obtaining power series expansions, particularly in two dimensions. A review of the method is given by Enting, 1996, Nuclear Physics B (proceedings supplement) 47, pp180-187.

    My work in the FLM involves a long-standing collaboration with present and former staff and students at The University of Melbourne, including (most notably) Tony Guttmann, Iwan Jensen, Aleks Owczarek, Richard Brak, Nick Wormald, Doochal Kim, Andrew Conway, Debbie Bennett-Wood and Keith Briggs.
    Application areas have included:

    Recent achievements

    External links

    Disclaimer

    This page, its contents and style, are the responsibility of the author and do not represent the views, policies or opinions of The University of Melbourne.

    Ian Enting: Last update 27/7/07