摘要翻译:
由于自旋玻璃材料具有极其缓慢的动力学特性,因此需要采用复杂的数值方法来研究其低温态。本文描述了伊辛模型的经典Kasteleyn处理的一个简单而快速的优化版本,并将其应用于二维伊辛自旋玻璃。该算法将Pfaffian和匹配方法相结合,直接将液滴激励从激发态中剥离出来。环面上伊辛自旋玻璃中的扩展基态在所有边界条件下都得到了优化,用于计算基态能量密度的精确值。
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英文标题:
《Matching Kasteleyn Cities for Spin Glass Ground States》
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作者:
Creighton K. Thomas, A. Alan Middleton
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最新提交年份:
2007
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分类信息:
一级分类:Physics 物理学
二级分类:Disordered Systems and Neural Networks 无序系统与神经网络
分类描述:Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
眼镜和旋转眼镜;随机、非周期和准周期系统的性质;无序介质中的传输;本地化;由缺陷和无序介导的现象;神经网络
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一级分类:Physics 物理学
二级分类:Statistical Mechanics 统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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英文摘要:
As spin glass materials have extremely slow dynamics, devious numerical methods are needed to study low-temperature states. A simple and fast optimization version of the classical Kasteleyn treatment of the Ising model is described and applied to two-dimensional Ising spin glasses. The algorithm combines the Pfaffian and matching approaches to directly strip droplet excitations from an excited state. Extended ground states in Ising spin glasses on a torus, which are optimized over all boundary conditions, are used to compute precise values for ground state energy densities.
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PDF链接:
https://arxiv.org/pdf/706.2866