Improved Algorithms for Simulating Crystalline Membranes
arXiv:physics/9709026 · doi:10.1016/S0010-4655(98)00014-9
Abstract
The physics of crystalline membranes, i.e. fixed-connectivity surfaces embedded in three dimensions and with an extrinsic curvature term, is very rich and of great theoretical interest. To understand their behavior, numerical simulations are commonly used. Unfortunately, traditional Monte Carlo algorithms suffer from very long auto-correlations and critical slowing down in the more interesting phases of the model. In this paper we study the performance of improved Monte Carlo algorithms for simulating crystalline membrane, such as hybrid overrelaxation and unigrid methods, and compare their performance to the more traditional Metropolis algorithm. We find that although the overrelaxation algorithm does not reduce the critical slowing down, it gives an overall gain of a factor 15 over the Metropolis algorithm. The unigrid algorithm does, on the other hand, reduce the critical slowing down exponent to z apprx. 1.7.
14 pages, 1 eps-figure
References in corpus (1)
Cited by in corpus (7)
- Strict Detailed Balance is Unnecessary in Monte Carlo Simulation
- The Statistical Mechanics of Membranes
- Universality Classes of Self-Avoiding Fixed-Connectivity Membranes
- Lattice Gravity and Random Surfaces
- Random Surfaces and Lattice Gravity
- An Introduction to Monte Carlo Simulation of Statistical physics Problem
- Anisotropic Membranes