From Tensor Networks to Tractable Circuits, and back

Fuente: arXiv
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Main Authors: Quist, Arend-Jan, Bartra, Marc Farreras, de Colnet, Alexis, van de Wetering, John, Laarman, Alfons
Format: Preprint
Published: 2026
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author Quist, Arend-Jan
Bartra, Marc Farreras
de Colnet, Alexis
van de Wetering, John
Laarman, Alfons
author_facet Quist, Arend-Jan
Bartra, Marc Farreras
de Colnet, Alexis
van de Wetering, John
Laarman, Alfons
contents Tensor networks and circuits are widely used data structures to represent pseudo-Boolean functions. These two formalisms have been studied primarily in separate communities, and this paper aims to establish equivalences between them. We show that some classes of tensor networks that are appealing in practice correspond to classes of circuits with specific properties that have been studied in knowledge compilation as \emph{tractable circuits}. In particular, we prove that matrix product states (tensor trains) coincide with nondeterministic edge-valued decision diagrams and that tree tensor networks exactly correspond to structured-decomposable circuits. These correspondences enable direct transfer of structural and algorithmic results; for example, canonicity and tractability guarantees known for circuits yield analogous guarantees for the associated tensor networks, and vice versa.
format Preprint
id arxiv_https___arxiv_org_abs_2605_00106
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Tensor Networks to Tractable Circuits, and back
Quist, Arend-Jan
Bartra, Marc Farreras
de Colnet, Alexis
van de Wetering, John
Laarman, Alfons
Quantum Physics
Data Structures and Algorithms
Logic in Computer Science
Tensor networks and circuits are widely used data structures to represent pseudo-Boolean functions. These two formalisms have been studied primarily in separate communities, and this paper aims to establish equivalences between them. We show that some classes of tensor networks that are appealing in practice correspond to classes of circuits with specific properties that have been studied in knowledge compilation as \emph{tractable circuits}. In particular, we prove that matrix product states (tensor trains) coincide with nondeterministic edge-valued decision diagrams and that tree tensor networks exactly correspond to structured-decomposable circuits. These correspondences enable direct transfer of structural and algorithmic results; for example, canonicity and tractability guarantees known for circuits yield analogous guarantees for the associated tensor networks, and vice versa.
title From Tensor Networks to Tractable Circuits, and back
topic Quantum Physics
Data Structures and Algorithms
Logic in Computer Science
url https://arxiv.org/abs/2605.00106