摘要翻译：
本文讨论了一种新的数值链簇算法在强相关流动模型中的应用。特别地，我们研究了正方形晶格上t-J模型的热力学观察项：化学势、熵、比热和均匀磁化率，当J/T=0.5和0.3时。我们的NLC结果与高温展开(HTE)和有限温度Lanczos方法(FTLM)的结果进行了比较。我们证明了在温度上存在一个相当大的窗口，在这里NLC结果不需要外推就收敛，而HTE结果发散。根据外推，在某些情况下，NLC、HTE和FTLM之间的总体一致性很好，可达0.25T。在中温下，NLC的结果比其他方法更好地控制，使得更容易判断方法的收敛性和数值精度。
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英文标题：
《Numerical Linked-Cluster Algorithms. II. t-J models on the square
  lattice》
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作者：
Marcos Rigol, Tyler Bryant, Rajiv R. P. Singh
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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：Strongly Correlated Electrons        强关联电子
分类描述：Quantum magnetism, non-Fermi liquids, spin liquids, quantum criticality, charge density waves, metal-insulator transitions
量子磁学，非费米液体，自旋液体，量子临界性，电荷密度波，金属-绝缘体跃迁
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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 discuss the application of a recently introduced numerical linked-cluster (NLC) algorithm to strongly correlated itinerant models. In particular, we present a study of thermodynamic observables: chemical potential, entropy, specific heat, and uniform susceptibility for the t-J model on the square lattice, with J/t=0.5 and 0.3. Our NLC results are compared with those obtained from high-temperature expansions (HTE) and the finite-temperature Lanczos method (FTLM). We show that there is a sizeable window in temperature where NLC results converge without extrapolations whereas HTE diverges. Upon extrapolations, the overall agreement between NLC, HTE, and FTLM is excellent in some cases down to 0.25t. At intermediate temperatures NLC results are better controlled than other methods, making it easier to judge the convergence and numerical accuracy of the method.
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PDF链接：
https://arxiv.org/pdf/706.3255