Numerical linked-cluster algorithms. I. Spin systems on square, triangular, and kagomé lattices

Marcos Rigol, Tyler Bryant, Rajiv R.P. Singh

Research output: Contribution to journalArticle

65 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number061118
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume75
Issue number6
DOIs
StatePublished - Jun 21 2007

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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