The density matrix renormalization group for strongly correlated electron systems: A generic implementation

Published: 29 Nov 2019 | Version 1 | DOI: 10.17632/r5s6td37g4.1
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Description of this data

Abstract
The purpose of this paper is (i) to present a generic and fully functional implementation of the density-matrix renormalization group (DMRG) algorithm, and (ii) to describe how to write additional strongly-correlated electron models and geometries by using templated classes. Besides considering general models and geometries, the code implements Hamiltonian symmetries in a generic way and parallelization over symmetry-related matrix blocks.

Title of program: DMRG++
Catalogue Id: AEDJ_v1_0

Nature of problem
Strongly correlated electrons systems, display a broad range of important phenomena, and their study is a major area of research in condensed matter physics. In this context, model Hamiltonians are used to simulate the relevant interactions of a given compound, and the relevant degrees of freedom. These studies rely on the use of tight-binding lattice models that consider electron localization, where states on one site can be labeled by spin and orbital degrees of freedom. The calculation of pro ...

Versions of this program held in the CPC repository in Mendeley Data
AEDJ_v1_0; DMRG++; 10.1016/j.cpc.2009.02.016
AEDJ_v2_0; DMRG++; 10.1016/j.cpc.2012.04.025

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)

Experiment data files

This data is associated with the following publication:

The density matrix renormalization group for strongly correlated electron systems: A generic implementation

Published in: Computer Physics Communications

Latest version

  • Version 1

    2019-11-29

    Published: 2019-11-29

    DOI: 10.17632/r5s6td37g4.1

    Cite this dataset

    Alvarez, G. (2019), “The density matrix renormalization group for strongly correlated electron systems: A generic implementation ”, Mendeley Data, v1 http://dx.doi.org/10.17632/r5s6td37g4.1

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Categories

Statistical Physics, Computational Physics, Thermodynamics

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