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Quantum Machine Learning

On the construction of graph models realizing given entropy vectors

arXiv
Authors: Veronika E. Hubeny, Massimiliano Rota

Year

2025

Paper ID

36446

Status

Preprint

Abstract Read

~2 min

Abstract Words

92

Citations

N/A

Abstract

We present an efficient algorithm for the construction of a holographic simple tree graph model that realizes a given entropy vector, subject to a specific "chordality" condition first introduced in arXiv:2412.18018. We further develop the toolkit of the correlation hypergraph, particularly in relation to coarse-graining and fine-graining of subsystems. We then use these techniques to take the first steps towards the generalization of this new algorithm to arbitrary (not necessarily simple) holographic tree graph models, and the "detection" of unrealizability of an entropy vector independently from the knowledge of holographic entropy inequalities.

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  • We present an efficient algorithm for the construction of a holographic simple tree graph model that realizes a given entropy vector, subject to a specific "chordality"...

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2512.18702 [2] arXiv https://arxiv.org/abs/2512.18702 [3] Publisher https://arxiv.org/abs/2512.18702

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