Multi-Grid Monte Carlo via Embedding. II. Two-Dimensional Principal Chiral Model
arXiv:hep-lat/9610021 · doi:10.1103/PhysRevD.55.3674
Abstract
We carry out a high-precision simulation of the two-dimensional principal chiral model at correlation lengths up to , using a multi-grid Monte Carlo (MGMC) algorithm and approximately one year of Cray C-90 CPU time. We extrapolate the finite-volume Monte Carlo data to infinite volume using finite-size-scaling theory, and we discuss carefully the systematic and statistical errors in this extrapolation. We then compare the extrapolated data to the renormalization-group predictions. The deviation from asymptotic scaling, which is at , decreases to at . We also analyze the dynamic critical behavior of the MGMC algorithm using lattices up to , finding the dynamic critical exponent (subjective 68% confidence interval). Thus, for this asymptotically free model, critical slowing-down is greatly reduced compared to local algorithms, but not completely eliminated.
self-unpacking archive including .tex, .sty and .ps files; 126 pages including all figures
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