We present evidence that multigrid (MG) works for wave equations in disordered systems, e.g. in the presence of gauge fields, no matter how strong the disorder. We introduce a "neural computations" point of view into large scale simulations: First, the system must learn how to do the simulations efficiently, then do the simulation (fast). The method can also be used to provide smooth interpolation kernels which are needed in multigrid Monte Carlo updates.
@article{arxiv.hep-lat/9211031,
title = {Multigrid meets Neural Nets},
author = {M. Baeker and G. Mack and M. Speh},
journal= {arXiv preprint arXiv:hep-lat/9211031},
year = {2009}
}
Comments
contribution to LATTICE '92, 4 pages, LaTeX [revised version: no change in content; problems printing PS figures corrected]