A real-space stochastic density matrix approach for density functional electronic structure

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

Original languageEnglish
Pages (from-to)31472-31479
Number of pages8
JournalPhysical Chemistry Chemical Physics
Volume17
Issue number47
DOIs
StatePublished - 2015
Externally publishedYes

Funding

FundersFunder number
National Science Foundation1266105

    Fingerprint

    Dive into the research topics of 'A real-space stochastic density matrix approach for density functional electronic structure'. Together they form a unique fingerprint.

    Cite this