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Stochastic dynamical low-rank approximation method

Numerical Analysis 2018-07-05 v2

Abstract

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.

Keywords

Cite

@article{arxiv.1803.00499,
  title  = {Stochastic dynamical low-rank approximation method},
  author = {Yu Cao and Jianfeng Lu},
  journal= {arXiv preprint arXiv:1803.00499},
  year   = {2018}
}

Comments

27 pages, 8 figures