Orthogonal Polynomial Representation of Imaginary-Time Green's Functions

Physics – Condensed Matter – Strongly Correlated Electrons

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

14 pages, 11 figures

Scientific paper

10.1103/PhysRevB.84.075145

We study the expansion of single-particle and two-particle imaginary-time Matsubara Green's functions of quantum impurity models in the basis of Legendre orthogonal polynomials. We discuss various applications within the dynamical mean-field theory (DMFT) framework. The method provides a more compact representation of the Green's functions than standard Matsubara frequencies and therefore significantly reduces the memory-storage size of these quantities. Moreover, it can be used as an efficient noise filter for various physical quantities within the continuous-time quantum Monte Carlo impurity solvers recently developed for DMFT and its extensions. In particular, we show how to use it for the computation of energies in the context of realistic DMFT calculations in combination with the local density approximation to the density functional theory (LDA+DMFT) and for the calculation of lattice susceptibilities from the local irreducible vertex function.

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

Orthogonal Polynomial Representation of Imaginary-Time Green's Functions 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 Orthogonal Polynomial Representation of Imaginary-Time Green's Functions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Orthogonal Polynomial Representation of Imaginary-Time Green's Functions will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-346992

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