5 research outputs found

    On the mixing time of the 2D stochastic Ising model with "plus" boundary conditions at low temperature

    Full text link
    We consider the Glauber dynamics for the 2D Ising model in a box of side L, at inverse temperature β\beta and random boundary conditions τ\tau whose distribution P either stochastically dominates the extremal plus phase (hence the quotation marks in the title) or is stochastically dominated by the extremal minus phase. A particular case is when P is concentrated on the homogeneous configuration identically equal to + (equal to -). For β\beta large enough we show that for any ϵ\epsilon there exists c=c(β,ϵ)c=c(\beta,\epsilon) such that the corresponding mixing time TmixT_{mix} satisfies limLP(Tmix>exp(cLϵ))=0\lim_{L\to\infty}P(T_{mix}> \exp({cL^\epsilon})) =0. In the non-random case τ+\tau\equiv + (or τ\tau\equiv -), this implies that Tmix<exp(cLϵ)T_{mix}< \exp({cL^\epsilon}). The same bound holds when the boundary conditions are all + on three sides and all - on the remaining one. The result, although still very far from the expected Lifshitz behaviour Tmix=O(L2)T_{mix}=O(L^2), considerably improves upon the previous known estimates of the form Tmixexp(cL1/2+ϵ)T_{mix}\le \exp({c L^{1/2 + \epsilon}}). The techniques are based on induction over length scales, combined with a judicious use of the so-called "censoring inequality" of Y. Peres and P. Winkler, which in a sense allows us to guide the dynamics to its equilibrium measure.Comment: 39 pages, 8 figures; v2: typos corrected, two references added. To appear on Comm. Math. Phy

    Relaxation Times of Markov Chains in Statistical Mechanics and Combinatorial Structures

    No full text
    corecore