The Dynamical Cluster Approximation: A New Technique for Simulations of Strongly Correlated Electron Systems

Physics – Condensed Matter – Strongly Correlated Electrons

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

15 pages, 9 figures; to be published in proceedings of the XIII workshop on Recent Developments in Computer Simulation Studies

Scientific paper

We present the algorithmic details of the dynamical cluster approximation (DCA) algorithm. The DCA is a fully-causal approach which systematically restores non-local correlations to the dynamical mean field approximation (DMFA). The DCA is in the thermodynamic limit and becomes exact for an infinite cluster size, while reducing to the DMFA for a cluster size of unity. Using the one-dimensional Hubbard Model as a non-trivial test of the method, we systematically compare the results of a quantum Monte Carlo (QMC) based DCA with those obtained by finite-size QMC simulations (FSS). We find that the single-particle Green function and the self-energy of the DCA and FSS approach the same limit as the system size is increased, but from complimentary directions. The utility of the DCA in addressing problems that have not been resolved by FSS is demonstrated.

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

The Dynamical Cluster Approximation: A New Technique for Simulations of Strongly Correlated Electron Systems 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 The Dynamical Cluster Approximation: A New Technique for Simulations of Strongly Correlated Electron Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Dynamical Cluster Approximation: A New Technique for Simulations of Strongly Correlated Electron Systems will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-589566

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