Numerical Linked-Cluster Algorithms. II. t-J models on the square lattice
| Autor: | Rajiv R. P. Singh, Marcos Rigol, Tyler Bryant |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Specific heat
Strongly Correlated Electrons (cond-mat.str-el) Statistical Mechanics (cond-mat.stat-mech) FOS: Physical sciences Observable 01 natural sciences Square lattice 010305 fluids & plasmas Condensed Matter - Strongly Correlated Electrons Lanczos resampling Entropy (classical thermodynamics) 0103 physical sciences Physics::Accelerator Physics Statistical physics 010306 general physics Algorithm Condensed Matter - Statistical Mechanics Mathematics |
| DOI: | 10.48550/arxiv.0706.3255 |
| Popis: | 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. Comment: 7 pages, 12 figures, as published |
| Databáze: | OpenAIRE |
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