用$q$状态时钟模型近似随机图上的XY模型

Cosimo Lupo, F. Ricci-Tersenghi
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引用次数: 17

摘要

连续变量自旋玻璃模型的数值模拟,解决了连续变量可靠而有效的离散化问题。特别是,主要的问题是,当离散模型的状态数增加时,离散模型中计算的物理观测值向连续模型的观测值收敛的速度有多快。我们在随机图提供的平均场设置中回答了XY模型及其离散化,$q$状态时钟模型的这个问题。我们发现,在时钟模型的状态数量$q$中,物理可观测值的收敛速度呈指数级增长,因此可以通过使用相当少的状态来非常可靠地近似XY模型。此外,这种指数收敛性与所使用的无序分布无关。只有在$T=0$时,收敛速度稍慢(拉伸指数)。我们还研究了$q$态时钟模型在低温自旋玻璃相中的1RSB解。
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Approximating the XY model on a random graph with a $q$-states clock model
Numerical simulations of spin glass models with continuous variables set the problem of a reliable but efficient discretization of such variables. In particular, the main question is how fast physical observables computed in the discretized model converge toward the ones of the continuous model when the number of states of the discretized model increases. We answer this question for the XY model and its discretization, the $q$-states clock model, in the mean-field setting provided by random graphs. It is found that the convergence of physical observables is exponentially fast in the number $q$ of states of the clock model, so allowing a very reliable approximation of the XY model by using a rather small number of states. Furthermore, such an exponential convergence is found to be independent from the disorder distribution used. Only at $T=0$ the convergence is slightly slower (stretched exponential). We also study the 1RSB solution of the $q$-states clock model in the low temperature spin glass phase.
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