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