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Quantum Machine Learning
Quantum Chemistry
TensorKit.jl: A Julia package for large-scale tensor computations, with a hint of category theory
arXiv
Authors: Lukas Devos, Jutho Haegeman
Year
2026
Paper ID
68642
Status
Preprint
Abstract Read
~2 min
Abstract Words
66
Citations
N/A
Abstract
TensorKit.jl is a Julia-based software package for tensor computations, especially focusing on tensors with internal symmetries. This paper introduces the design philosophy, core functionalities, and distinctive features, including how to handle abelian, non-abelian, and anyonic symmetries through the "TensorMap" type. We highlight the software's flexibility, performance, and its capability to extend to new tensor types and symmetries, illustrating its practical applications through select case studies.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- TensorKit.jl is a Julia-based software package for tensor computations, especially focusing on tensors with internal symmetries.
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