Abstract
Tensor networks have a gauge degree of freedom on the virtual degrees of freedom that are contracted. A canonical form is a choice of fixing this degree of freedom. For matrix product states, choosing a canonical form is a powerful tool, both for theoretical and numerical purposes. On the other hand, for tensor networks in dimension two or greater there is only limited understanding of the gauge symmetry. Here we introduce a new canonical form, the minimal canonical form, which applies to projected entangled pair states (PEPS) in any dimension, and prove a corresponding fundamental theorem. Already for matrix product states this gives a new canonical form, while in higher dimensions it is the first rigorous definition of a canonical form valid for any choice of tensor. We show that two tensors have the same minimal canonical forms if and only if they are gauge equivalent up to taking limits; moreover, this is the case if and only if they give the same quantum state for any geometry. In particular, this implies that the latter problem is decidable - in contrast to the well-known undecidability for equality of PEPS on grids. We also provide rigorous algorithms for computing minimal canonical forms. To achieve this we draw on geometric invariant theory and recent progress in theoretical computer science in non-commutative group optimization.
Original language | English |
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Title of host publication | Proceedings - 2023 IEEE 64th Annual Symposium on Foundations of Computer Science, FOCS 2023 |
Publisher | IEEE |
Publication date | 2023 |
Pages | 328-362 |
ISBN (Electronic) | 9798350318944 |
DOIs | |
Publication status | Published - 2023 |
Event | 64th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2023 - Santa Cruz, United States Duration: 6 Nov 2023 → 9 Nov 2023 |
Conference
Conference | 64th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2023 |
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Country/Territory | United States |
City | Santa Cruz |
Period | 06/11/2023 → 09/11/2023 |
Sponsor | IEEE, IEEE Computer Society, IEEE Computer Society Technical Committee on Mathematical Foundations of Computing, NSF |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- invariant theory
- non-commutative optimization
- tensor networks