TensorKit.jl: A Julia package for large-scale tensor computations, with a hint of category theory

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.

Publication Details

Journal
ArXiv.org
Published
2025-08-13
Primary Topic
Machine Learning in Materials Science
Type
article
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article

TensorKit.jl: A Julia package for large-scale tensor computations, with a hint of category theory

ArXiv.org
Machine Learning in Materials Science
article

TensorKit.jl: A Julia package for large-scale tensor computations, with a hint of category theory

article en

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.

ArXiv.org
Openalex Percentile: Top 60%
Machine Learning in Materials Science
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TensorKit.jl: A Julia package for large-scale tensor computations, with a hint of category theory · ArXiv.org (2025) | TGRS Research Map | TGRS