A phase transition for the coupled branching process

Summary We consider a particular Markov process _t ^u on ^S ,S= ⁿ . The random variable _t ^u (x) is interpreted as the number of particles atx at timet. The initial distribution of this process is a translation invariant measure withf(x)d<. The evolution is as follows: At rateb(x) a particle is born atx but moves instantaneously toy chosen with probabilityq(x, y). All particles at a site die at ratepd withp0, 1],d, ⁺ and individual particles die independently from each other at rate (1–p)d. Every particle moves independently of everything else according to a continuous time random walk.We are mainly interested in the caseb=d andn3. The process exhibits a phase transition with respect to the parameterp: Forp<p ^* all weak limit points of ( _t ^µ ) ast still have particle density (x)d. Forp>p ^*, _t ^µ ) converges ast to the measure concentrated on the configuration identically 0. We calculatep ^* as well asp ⁽ⁿ⁾ , the points with the property that the extremal invariant measures have forp>p ⁽ⁿ⁾ infiniten-th moment of (x) and forp<p ⁽ⁿ⁾ finiten-th moment. We show the case 1>p ^*>p⁽²⁾>p⁽³⁾...p ⁽ⁿ⁾ >0, p⁽ⁿ⁾0 occurs for suitable values of the other parameters. Forp<p ⁽²⁾ we prove the system has a one parameter set of extremal invariant measures and we determine their domain of attraction. Part I contains statements of all results but only the proofs of the results about the process for values ofp withp<p ⁽²⁾ and the behaviour of then-th moments andp ⁽ⁿ⁾ .