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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| Format: | Article |
| Language: | English |
| Published: |
SciPost
2025-06-01
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| Series: | SciPost Physics |
| Online Access: | https://scipost.org/SciPostPhys.18.6.192 |
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