Stochastic dynamical low-rank approximation method


Journal Article

© 2018 Elsevier Inc. In this paper, we extend the dynamical low-rank approximation method to the space of finite signed measures. Under this framework, we derive stochastic low-rank dynamics for stochastic differential equations (SDEs) coming from classical stochastic dynamics or unraveling of Lindblad quantum master equations. We justify the proposed method by error analysis and also numerical examples for applications in solving high-dimensional SDE, stochastic Burgers' equation, and high-dimensional Lindblad equation.

Full Text

Duke Authors

Cited Authors

  • Cao, Y; Lu, J

Published Date

  • November 1, 2018

Published In

Volume / Issue

  • 372 /

Start / End Page

  • 564 - 586

Electronic International Standard Serial Number (EISSN)

  • 1090-2716

International Standard Serial Number (ISSN)

  • 0021-9991

Digital Object Identifier (DOI)

  • 10.1016/

Citation Source

  • Scopus