Density matrix minimization with ℓ1 regularization

Published

Journal Article

We propose a convex variational principle to find sparse representation of low-lying eigenspace of symmetric matrices. In the context of electronic structure calculation, this corresponds to a sparse density matrix minimization algorithm with ℓ1 regularization. The minimization problem can be efficiently solved by a split Bregman iteration type algorithm. We further prove that from any initial condition, the algorithm converges to a minimizer of the variational principle.

Full Text

Duke Authors

Cited Authors

  • Lai, R; Lu, J; Osher, S

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 13 / 8

Start / End Page

  • 2097 - 2117

Electronic International Standard Serial Number (EISSN)

  • 1945-0796

International Standard Serial Number (ISSN)

  • 1539-6746

Digital Object Identifier (DOI)

  • 10.4310/CMS.2015.v13.n8.a6

Citation Source

  • Scopus