Numerical linked-cluster algorithms. II. t-J models on the square lattice.
Numerical linked-cluster algorithms. II. t-J models on the square lattice.
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DOI：
10.1103/physreve.75.061119
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发表时间：
2007-06
期刊：
影响因子：
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通讯作者：
M. Rigol;Tyler Bryant;Rajiv R. P. Singh
中科院分区：
文献类型：
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作者：
M. Rigol;Tyler Bryant;Rajiv R. P. Singh
我们讨论了最近引入的数值链接簇（NLC）算法在强相关流动模型中的应用。特别是，我们提出了热力学可观测量的研究：化学势、熵、比热和方晶格上 t-J 模型的均匀磁化率，其中 Jt=0.5 和 0.3。我们的 NLC 结果与高温膨胀 (HTE) 和有限温度 Lanczos 方法 (FTLM) 获得的结果进行了比较。我们表明，温度存在一个相当大的窗口，其中 NLC 结果无需外推即可收敛，而 HTE 则发散。根据推断，在某些情况下，NLC、HTE 和 FTLM 之间的总体一致性非常好，低至 0.25t。在中间温度下，NLC 结果比其他方法更好地控制，从而更容易判断该方法的收敛性和数值精度。
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 Jt=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.