English

Exploring optimization for the random-field Ising model

Disordered Systems and Neural Networks 2007-05-23 v1 Statistical Mechanics

Abstract

The push-relabel algorithm can be used to calculate rapidly the exact ground states for a given sample with a random-field Ising model (RFIM) Hamiltonian. Although the algorithm is guaranteed to terminate after a time polynomial in the number of spins, implementation details are important for practical performance. Empirical results for the timing in dimensions d=1,2, and 3 are used to determine the fastest among several implementations. Direct visualization of the auxiliary fields used by the algorithm provides insight into its operation and suggests how to optimize the algorithm. Recommendations are given for further study of the RFIM.

Keywords

Cite

@article{arxiv.cond-mat/0501269,
  title  = {Exploring optimization for the random-field Ising model},
  author = {D. Clay Hambrick and Jan H. Meinke and A. Alan Middleton},
  journal= {arXiv preprint arXiv:cond-mat/0501269},
  year   = {2007}
}

Comments

10 pages