While theories for mean-field spin glass are well-developed, their applicability to finite-dimensional spin glasses is still in question. For many years, progress in verifying those theories using simulations have been hampered by the complexity inherent to the task: Just finding a ground state is an NP-hard problem, i.e. it is in the class of the most difficult computational problems known. This is a fruitful and pioneering research area at the interface of statistical physics and computer science, spawning interest in New Optimization Algorithms in Physics. While many areas of science are driven by rapidly improving hardware, the complexity of strongly disordered systems also requires the development of sophisticated methods and algorithms that may anticipate the fate of computational sciences beyond Moore's Law. |

Fitting the stiffness exponent for |
We have pioneered several new approaches to low temperature spin glasses, in particular, the Extremal Optimization (EO) heuristic (see DEMO here). By focusing on Our approach can be applied to any large-scale spin-glass network. We have tested the algorithm by determining
the stiffness exponent, and ground state overlap, entropy, and energy with high accuracy
for the Even for the fully connected Sherrington-Kirkpatrick spin glass at T=0, EO provides some of the most precise predictions to date (see DEMO here). |

©1996-2002 Physics Department, Emory University. These pages may be freely distributed if unmodified. Last Update: 9/26/02; 2:55:53 PM For more information, contact: webmaster@physics.emory.edu |