On the complexity of isomorphism problems for tensors, groups, and polynomials III: actions by classical groups

Abstract We study the complexity of isomorphism problems for tensors, represented in coordinates by multiway arrays, under natural actions by classical groups such as orthogonal, unitary, and symplectic groups. These problems arise naturally in statistical data analysis and quantum information. We study two types of complexity-theoretic questions. First, for a fixed action type (isomorphism, conjugacy, etc.), we relate the complexity of the isomorphism problem over a classical group to that over the general linear group. Second, for a fixed group type (orthogonal, unitary, or symplectic), we compare the complexity of the isomorphism problems for different actions. Our main results are as follows. First, for orthogonal and symplectic groups acting on 3-way arrays, the isomorphism problems reduce to the corresponding problems over the general linear group. Second, for orthogonal and unitary groups, the isomorphism problems of five natural actions on 3-way arrays are polynomial-time equivalent, and the d -tensor isomorphism problem reduces to the 3-tensor isomorphism problem for any fixed $$d>3$$ d > 3 . For unitary groups, the preceding result implies that LOCC classification of tripartite quantum states is at least as difficult as LOCC classification of d -partite quantum states for any d . Lastly, we also show that the graph isomorphism problem reduces to the tensor isomorphism problem over orthogonal and unitary groups.

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Publication Details

Journal
Computational Complexity
Published
2026-09-22
DOI
https://doi.org/10.1007/s00037-026-00294-x
Citations
2
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
0.00

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article

On the complexity of isomorphism problems for tensors, groups, and polynomials III: actions by classical groups

Joshua A. Grochow, Youming Qiao, Chuanqi Zhang
2 citations
Computational Complexity
Tensor decomposition and applications
article

On the complexity of isomorphism problems for tensors, groups, and polynomials III: actions by classical groups

Joshua A. Grochow, Youming Qiao, Chuanqi Zhang
article en
2 citations

Abstract

Abstract We study the complexity of isomorphism problems for tensors, represented in coordinates by multiway arrays, under natural actions by classical groups such as orthogonal, unitary, and symplectic groups. These problems arise naturally in statistical data analysis and quantum information. We study two types of complexity-theoretic questions. First, for a fixed action type (isomorphism, conjugacy, etc.), we relate the complexity of the isomorphism problem over a classical group to that over the general linear group. Second, for a fixed group type (orthogonal, unitary, or symplectic), we compare the complexity of the isomorphism problems for different actions. Our main results are as follows. First, for orthogonal and symplectic groups acting on 3-way arrays, the isomorphism problems reduce to the corresponding problems over the general linear group. Second, for orthogonal and unitary groups, the isomorphism problems of five natural actions on 3-way arrays are polynomial-time equivalent, and the d -tensor isomorphism problem reduces to the 3-tensor isomorphism problem for any fixed $$d>3$$ d > 3 . For unitary groups, the preceding result implies that LOCC classification of tripartite quantum states is at least as difficult as LOCC classification of d -partite quantum states for any d . Lastly, we also show that the graph isomorphism problem reduces to the tensor isomorphism problem over orthogonal and unitary groups.

Computational ComplexityVol. 35(2)
University of Technology Sydney (AU), Centre for Quantum Technologies (SG), University of Colorado Boulder (US), University of Colorado System (US), Centre for Quantum Computation and Communication Technology (AU), Monash University (AU)
National Science Foundation, National Research Foundation, National Research Foundation Singapore, Centre for Quantum Technologies, Directorate for Computer and Information Science and Engineering
Peace, Justice and strong institutions
Openalex Percentile: Top 99%
Tensor decomposition and applications
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