Numerical Linked-Cluster Algorithms. II. t-J models on the square lattice

Physics – Condensed Matter – Strongly Correlated Electrons

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

7 pages, 12 figures, as published

Scientific paper

10.1103/PhysRevE.75.061119

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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Numerical Linked-Cluster Algorithms. II. t-J models on the square lattice does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Numerical Linked-Cluster Algorithms. II. t-J models on the square lattice, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Numerical Linked-Cluster Algorithms. II. t-J models on the square lattice will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-187354

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.