METROPOLIS MONTE-CARLO SIMULATION OF LATTICE ANIMALS

We propose and study a metropolis Monte Carlo algorithm for the simula tion of weighted lattice animals in Z(d) in the canonical ensemble (wi th a fixed number of edges). We examine the implementation and perform ance of the algorithm. Data obtained by sampling uniformly weighted an imals, and animals weighted as critical-percolation clusters, are repo rted and analysed. In particular, we estimate autocorrelation rimes an d dynamical exponents to study the efficiency of the algorithm, and es timate the metric and branch exponents of lattice animals in two and t hree dimensions.