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Quantum Machine Learning Quantum Simulation

trainsum - A Python package for quantics tensor trains

arXiv
Authors: Paul Haubenwallner, Matthias Heller

Year

2026

Paper ID

15737

Status

Preprint

Abstract Read

~2 min

Abstract Words

86

Citations

N/A

Abstract

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.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • We present trainsum, a versatile Python package for doing computations with multidimensional quantics tensor trains: https://github.com/fh-igd-iet/trainsum.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2602.20226 [2] arXiv https://arxiv.org/abs/2602.20226 [3] Publisher https://arxiv.org/abs/2602.20226

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