TRANSFER-MATRIX MONTE-CARLO ESTIMATES OF CRITICAL-POINTS IN THE SIMPLE-CUBIC ISING, PLANAR, AND HEISENBERG MODELS

The principle and the efficiency of the Monte Carlo transfer-matrix al gorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. W e demonstrate how the statistical noise can be reduced considerably by a similarity transformation of the transfer matrix using a variationa l estimate of its leading eigenvector, in analogy with a common practi ce in various quantum Monte Carlo techniques. Here we take the two-dim ensional coupled XY-Ising model as an example. Furthermore, we calcula te interface free energies of finite three-dimensional O(n) models, fo r the three cases n=1, 2, and 3. Application of finite-size scaling to the numerical results yields estimates of the critical points of thes e three models. The statistical precision of the estimates is satisfac tory for the modest amount of computer time spent.