摘要翻译：
我们描述了一种新的基于“反向”蒙特卡罗方法的切换算法，该算法在系统结构移动之前随机修改电势。该算法使聚类Monte Carlo方法的推广成为可能，并使离散和连续两个自由度系统的聚类算法成为可能。用该方法研究了sine-Gordon模型中的粗糙化转变，并对系统尺寸高达1024^2$的系统进行了高精度模拟，研究了表面粗糙度在转变温度以上的对数发散，揭示了Kosterlitz-Thouless型普遍标度的明显证据。
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英文标题：
《A New Monte Carlo Method and Its Implications for Generalized Cluster
  Algorithms》
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作者：
C. H. Mak and Arun K. Sharma
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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：Soft Condensed Matter        软凝聚态物质
分类描述：Membranes, polymers, liquid crystals, glasses, colloids, granular matter
膜，聚合物，液晶，玻璃，胶体，颗粒物质
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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：
  We describe a novel switching algorithm based on a ``reverse'' Monte Carlo method, in which the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of cluster-type Monte Carlo methods, and the generalization makes it possible to derive cluster algorithms for systems with both discrete and continuous degrees of freedom. The roughening transition in the sine-Gordon model has been studied with this method, and high-accuracy simulations for system sizes up to $1024^2$ were carried out to examine the logarithmic divergence of the surface roughness above the transition temperature, revealing clear evidence for universal scaling of the Kosterlitz-Thouless type.
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PDF链接：
https://arxiv.org/pdf/704.1539