Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2000-10-19
Commun. Math. Phys., 214 (2000), 373.
Physics
Condensed Matter
Disordered Systems and Neural Networks
17 pages (RevTeX; 3 figures; to appear in Commun. Math. Phys.)
Scientific paper
10.1007/PL00005535
We study zero-temperature, stochastic Ising models sigma(t) on a d-dimensional cubic lattice with (disordered) nearest-neighbor couplings independently chosen from a distribution mu on R and an initial spin configuration chosen uniformly at random. Given d, call mu type I (resp., type F) if, for every x in the lattice, sigma(x,t) flips infinitely (resp., only finitely) many times as t goes to infinity (with probability one) --- or else mixed type M. Models of type I and M exhibit a zero-temperature version of ``local non-equilibration''. For d=1, all types occur and the type of any mu is easy to determine. The main result of this paper is a proof that for d=2, plus/minus J models (where each coupling is independently chosen to be +J with probability alpha and -J with probability 1-alpha) are type M, unlike homogeneous models (type I) or continuous (finite mean) mu's (type F). We also prove that all other noncontinuous disordered systems are type M for any d greater than or equal to 2. The plus/minus J proof is noteworthy in that it is much less ``local'' than the other (simpler) proof. Homogeneous and plus/minus J models for d greater than or equal to 3 remain an open problem.
Gandolfi Alberto
Newman Charles M.
Stein Daniel L.
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