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对于具有连续无序分布的二维旋转模型的数值链接集群扩展.
Mahmoud Abdelshafy1, Marcos Rigol1
1Department of Physics, <a href="https://ror.org/04p491231">The Pennsylvania State University</a>, University Park, Pennsylvania 16802, USA.
Physical review. E
|June 22, 2024
概括
具有大型构件的数值链接集群扩展 (NLCE) 准确计算无序旋转模型的低温热力学特性. 这种方法在计算权重之前平均NLCE集群中的混乱,即使在基态值上也能达到高精度.
科学领域:
- 凝聚物质物理学 凝聚物质物理学
- 计算物理 计算物理
背景情况:
- 对于无序旋转模型来说,准确的低温计算是具有挑战性的.
- 传统的方法与连续的无序分布作斗争.
研究的目的:
- 为了证明数字链接集群扩展 (NLCEs) 对无序旋转模型的有效性.
- 建立一种方法来获得准确的低温热力学特性.
主要方法:
- 使用大型L,方形和矩形构建块的NLCE.
- 在计算权重之前,计算NLCE集群中的疾病平均值.
- 将该方法应用于经典的伊辛和量子海森堡旋转-1/2模型.
主要成果:
- 准确的低温结果实现了热力学特性.
- 收得到的温度低于能量尺度的两个数量级.
- 精确的能量值在一个维度中得到到基底状态水平.
结论:
- 具有足够大的构建块的NLCE对于无序的旋转模型是有效的.
- 提出的方法使得高精度的低温和地面状态属性计算成为可能.
- 这种方法为研究复杂的磁系统提供了一个强大的工具.
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