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):061118. doi: 10.1103/PhysRevE.75.061118. Epub 2007 Jun 21.
We discuss recently introduced numerical linked-cluster (NLC) algorithms that allow one to obtain temperature-dependent properties of quantum lattice models, in the thermodynamic limit, from exact diagonalization of finite clusters. We present studies of thermodynamic observables for spin models on square, triangular, and kagomé lattices. Results for several choices of clusters and extrapolations methods, that accelerate the convergence of NLCs, are presented. We also include a comparison of NLC results with those obtained from exact analytical expressions (where available), high-temperature expansions (HTE), exact diagonalization (ED) of finite periodic systems, and quantum Monte Carlo simulations. For many models and properties NLC results are substantially more accurate than HTE and ED.
我们讨论了最近引入的数值关联簇（NLC）算法，该算法能让人在热力学极限下，通过有限簇的精确对角化来获得量子晶格模型的温度相关性质。我们展示了对正方形、三角形和 kagomé 晶格上自旋模型的热力学可观测量的研究。给出了几种簇选择和加速 NLC 收敛的外推方法的结果。我们还将 NLC 结果与从精确解析表达式（如适用）、高温展开（HTE）、有限周期系统的精确对角化（ED）以及量子蒙特卡罗模拟获得的结果进行了比较。对于许多模型和性质，NLC 结果比 HTE 和 ED 要精确得多。
