An additive two-level parallel variant of the DMRG algorithm with coarse-space correction

Fuente: arXiv
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Autori principali: Grigori, Laura, Hassan, Muhammad
Natura: Preprint
Pubblicazione: 2025
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author Grigori, Laura
Hassan, Muhammad
author_facet Grigori, Laura
Hassan, Muhammad
contents The density matrix renormalization group (DMRG) algorithm is a popular alternating minimization scheme for solving high-dimensional optimization problems in the tensor train format. Classical DMRG, however, is based on sequential minimization, which raises challenges in its implementation on parallel computing architectures. To overcome this, we propose a novel additive two-level DMRG algorithm that combines independent, local minimization steps with a global update step using a subsequent coarse-space minimization. Our proposed algorithm, which is directly inspired by additive Schwarz methods from the domain decomposition literature, is particularly amenable to implementation on parallel, distributed architectures since both the local minimization steps and the construction of the coarse-space can be performed in parallel. Numerical experiments on strongly correlated molecular systems demonstrate that the method achieves competitive convergence rates while achieving significant parallel speedups.
format Preprint
id arxiv_https___arxiv_org_abs_2505_23429
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An additive two-level parallel variant of the DMRG algorithm with coarse-space correction
Grigori, Laura
Hassan, Muhammad
Numerical Analysis
15A69, 65K10, 65N25, 90C06
The density matrix renormalization group (DMRG) algorithm is a popular alternating minimization scheme for solving high-dimensional optimization problems in the tensor train format. Classical DMRG, however, is based on sequential minimization, which raises challenges in its implementation on parallel computing architectures. To overcome this, we propose a novel additive two-level DMRG algorithm that combines independent, local minimization steps with a global update step using a subsequent coarse-space minimization. Our proposed algorithm, which is directly inspired by additive Schwarz methods from the domain decomposition literature, is particularly amenable to implementation on parallel, distributed architectures since both the local minimization steps and the construction of the coarse-space can be performed in parallel. Numerical experiments on strongly correlated molecular systems demonstrate that the method achieves competitive convergence rates while achieving significant parallel speedups.
title An additive two-level parallel variant of the DMRG algorithm with coarse-space correction
topic Numerical Analysis
15A69, 65K10, 65N25, 90C06
url https://arxiv.org/abs/2505.23429