Two-level QTT-Tucker format for optimized tensor calculus

Sergey Dolgov, Boris Khoromskij

Research output: Contribution to journalArticlepeer-review

14 Citations (SciVal)

Abstract

We propose a combined tensor format, which encapsulates the benefits of Tucker, tensor train (TT), and quantized TT (QTT) formats. The structure is composed of subtensors in TT representations, so the approximation problem is proven to be stable. We describe all important algebraic and optimization operations, which are recast to the TT routines. Several examples on explicit function and operator representations are provided. The asymptotic storage complexity is at most cubic in the rank parameter, that is larger than for the global QTT approximation, but the numerical examples manifest that the ranks in the two-level format usually increase more slowly with the approximation accuracy than the QTT ones. In particular, we observe that high rank peaks, which usually occur in the TT/QTT representations, are significantly relaxed. Thus the reduced costs can be achieved.

Original languageEnglish
Pages (from-to)593-623
Number of pages31
JournalSIAM Journal on Matrix Analysis and Applications
Volume34
Issue number2
DOIs
Publication statusPublished - 16 May 2013

Keywords

  • Constructive tensor representations
  • DMRG/ALS
  • Higher dimensions
  • Multilinear algebra
  • QTT format
  • Tensor formats
  • Tensor methods
  • Tucker format

ASJC Scopus subject areas

  • Analysis

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