Cons-training tensor networks: Embedding and optimization over discrete linear constraints

In this study, we introduce a novel family of tensor networks, termed constrained matrix product states (MPS), designed to incorporate exactly arbitrary discrete linear constraints, including inequalities, into sparse block structures. These tensor networks are particularly tailored for modeling dis...

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Bibliographic Details

Published in:	SciPost physics Vol. 18; no. 6; p. 192
Main Authors:	Lopez Piqueres, Javier, Chen, Jing
Format:	Journal Article
Language:	English
Published:	SciPost 01.06.2025
ISSN:	2542-4653, 2542-4653
Online Access:	Get full text
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