The Ising model is one of the most important theoretical models in statistical physics, which was originally developed to describe ferromagnetism. A system of magnetic particles, for example, can be modeled as a linear chain in one dimension or a lattice in two dimensions, with one particle at each lattice point. Then each particle is assigned a spin . The -state Potts model is a generalization of the Ising model where each spin may take on number of states . Both models have temperature and an externally applied magnetic field as parameters. Many statistical and physical properties of the -state Potts model can be derived by studying its partition function. This includes phase transitions as and/or are varied.
The celebrated Lee-Yang Theorem characterizes such phase transitions of the -state Potts model (the Ising model). This theorem does not hold for . Thus, phase transitions for the Potts model as is varied are more complicated and mysterious. We give some results that characterize the phase transitions of the -state Potts model as is varied for constant on the binary rooted Cayley tree. Similarly to the Ising model, we show that for fixed the -state Potts model for the ferromagnetic case exhibits a phase transition at one critical value of or not at all, depending on . However, an interesting new phenomenon occurs for the -state Potts model because the critical value of can be non-zero for some range of temperatures. The -state Potts model for the antiferromagnetic case exhibits phase transition at up to two critical values of .
The recursive constructions of the level Cayley tree from two copies of the level Cayley tree allow one to write a relatively simple rational function relating the Lee-Yang zeros at one level to the next. This allows us to use techniques from dynamical systems.