Rigol Marcos, Bryant Tyler, Singh Rajiv R P
Department of Physics and Astronomy, University of Southern California, Los Angeles, California 90089, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jun;75(6 Pt 1):061119. doi: 10.1103/PhysRevE.75.061119. Epub 2007 Jun 21.
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.
我们讨论了最近引入的数值关联簇（NLC）算法在强关联巡游模型中的应用。特别地，我们给出了对热力学可观测量的一项研究：正方晶格上t-J模型的化学势、熵、比热和均匀磁化率，其中J/t = 0.5和0.3。我们将NLC结果与通过高温展开（HTE）和有限温度兰索斯方法（FTLM）获得的结果进行了比较。我们表明，在温度上存在一个相当大的窗口，在该窗口内NLC结果无需外推就收敛，而HTE则发散。经过外推后，在某些情况下，NLC、HTE和FTLM之间的总体一致性在低至0.25t时都非常好。在中间温度下，NLC结果比其他方法得到了更好的控制，这使得更容易判断该方法的收敛性和数值精度。
