A stochastic complex network model society.
A stochastic system of particles is considered in which the sizes of the particles increase by successive binary mergers with the constraint that each coagulation event involves a particle with minimal size. Convergence of a suitably renormalized version of this process to a deterministic hydrodynamical limit is shown and the time evolution of the minimal size is studied for both deterministic and stochastic models.
We consider the coarse-graining of a lattice system with continuous spin variable. In the first part, two abstract results are established: sufficient conditions for a logarithmic Sobolev inequality with constants independent of the dimension (Theorem 3) and sufficient conditions for convergence to the hydrodynamic limit (Theorem 8). In the second part, we use the abstract results to treat a specific example, namely the Kawasaki dynamics with Ginzburg–Landau-type potential.
We consider a model of the shape of a growing polymer introduced by Durrett and Rogers (Probab. Theory Related Fields92 (1992) 337–349). We prove their conjecture about the asymptotic behavior of the underlying continuous process Xt (corresponding to the location of the end of the polymer at time t) for a particular type of repelling interaction function without compact support.