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Auteurs principaux: Haubenwallner, Paul, Heller, Matthias
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:https://arxiv.org/abs/2602.20226
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author Haubenwallner, Paul
Heller, Matthias
author_facet Haubenwallner, Paul
Heller, Matthias
contents We present trainsum, a versatile Python package for doing computations with multidimensional quantics tensor trains: https://github.com/fh-igd-iet/trainsum. Using the Array API standard together with opt_einsum, trainsum allows the effortless approximation of tensors or functions by tensor trains independent of their shape or dimensionality. Once approximated, our package can perform normal arithmetic operations with quantics tensor trains, including addition, Einstein summations and element-wise transformations. It can be therefore used for generic computations with applications in simulation, data compression, machine learning and data analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2602_20226
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle trainsum -- A Python package for quantics tensor trains
Haubenwallner, Paul
Heller, Matthias
Mathematical Software
Computational Physics
Quantum Physics
We present trainsum, a versatile Python package for doing computations with multidimensional quantics tensor trains: https://github.com/fh-igd-iet/trainsum. Using the Array API standard together with opt_einsum, trainsum allows the effortless approximation of tensors or functions by tensor trains independent of their shape or dimensionality. Once approximated, our package can perform normal arithmetic operations with quantics tensor trains, including addition, Einstein summations and element-wise transformations. It can be therefore used for generic computations with applications in simulation, data compression, machine learning and data analysis.
title trainsum -- A Python package for quantics tensor trains
topic Mathematical Software
Computational Physics
Quantum Physics
url https://arxiv.org/abs/2602.20226