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In this work, we generalize the graph-theoretic techniques used for the holographic entropy cone to study hypergraphs and their analogously-defined entropy cone. This allows us to develop a framework to efficiently compute entropies and…

Quantum Physics · Physics 2021-10-15 Ning Bao , Newton Cheng , Sergio Hernández-Cuenca , Vincent P. Su

The holographic entropy cone (HEC) is a polyhedral cone first introduced in the study of a class of quantum entropy inequalities. It admits a graph-theoretic description in terms of minimum cuts in weighted graphs, a characterization which…

Combinatorics · Mathematics 2023-01-10 David Avis , Sergio Hernández-Cuenca

We compute the set of all extreme rays of the 6-party subadditivity cone that are compatible with strong subadditivity. In total, we identify 208 new (genuine 6-party) orbits, 52 of which violate at least one known holographic entropy…

Quantum Physics · Physics 2025-07-22 Temple He , Veronika E. Hubeny , Massimiliano Rota

We initiate a systematic enumeration and classification of entropy inequalities satisfied by the Ryu-Takayanagi formula for conformal field theory states with smooth holographic dual geometries. For 2, 3, and 4 regions, we prove that the…

High Energy Physics - Theory · Physics 2015-09-23 Ning Bao , Sepehr Nezami , Hirosi Ooguri , Bogdan Stoica , James Sully , Michael Walter

The holographic entropy cone characterizes the relations between entanglement entropies for a spatial partitioning of the boundary spacetime of a holographic CFT in any state describing a classical bulk geometry. We argue that the…

High Energy Physics - Theory · Physics 2024-09-09 Sergio Hernández-Cuenca , Veronika E. Hubeny , Massimiliano Rota

Graph neural networks (GNNs) have shown advantages in graph-based analysis tasks. However, most existing methods have the homogeneity assumption and show poor performance on heterophilic graphs, where the linked nodes have dissimilar…

Machine Learning · Computer Science 2024-04-16 Tianhao Peng , Wenjun Wu , Haitao Yuan , Zhifeng Bao , Zhao Pengrui , Xin Yu , Xuetao Lin , Yu Liang , Yanjun Pu

The celebrated holographic entanglement entropy triggered investigations on the connections between quantum information theory and quantum gravity. An important achievement is that we have gained more insights into the quantum states. It…

High Energy Physics - Theory · Physics 2022-07-15 Nan Li , Chuan-Shi Dong , Dong-Hui Du , Fu-Wen Shu

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…

High Energy Physics - Theory · Physics 2025-12-23 Veronika E. Hubeny , Massimiliano Rota

We consider the problem of embedding the nodes of a hypergraph into Euclidean space under the assumption that the interactions arose through closeness to unknown hyperedge centres. In this way, we tackle the inverse problem associated with…

Social and Information Networks · Computer Science 2025-09-11 Francesco Zigliotto , Desmond J. Higham

Even though little is known about the quantum entropy cone for $N\geq4$ subsystems, holographic techniques allow one to get a handle on the subspace of entropy vectors corresponding to states with gravity duals. For static spacetimes and…

High Energy Physics - Theory · Physics 2021-10-15 Sergio Hernández-Cuenca

We develop a convenient framework for characterizing multipartite entanglement in composite systems, based on relations between entropies of various subsystems. This continues the program initiated in arXiv:1808.07871, of using holography…

High Energy Physics - Theory · Physics 2019-05-01 Veronika E. Hubeny , Mukund Rangamani , Massimiliano Rota

Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention…

Information Theory · Computer Science 2016-11-18 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention…

Information Theory · Computer Science 2016-07-05 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

Motivated by bit threads, we introduce a new prescription for computing entropy vectors outside the holographic entropy cone. By utilizing cycle flows on directed graphs, we show that the maximum cycle flow associated to any subset of…

High Energy Physics - Theory · Physics 2024-10-29 Temple He , Sergio Hernández-Cuenca , Cynthia Keeler

The holographic entropy cone identifies entanglement entropies of field theory regions, which are consistent with representing semiclassical spacetimes under gauge/gravity duality; it is currently known up to 5 regions. We point out that…

High Energy Physics - Theory · Physics 2023-09-28 Bartlomiej Czech , Sirui Shuai

We propose a deterministic method to find all holographic entropy inequalities that have corresponding contraction maps and argue the completeness of our method. We use a triality between holographic entropy inequalities, contraction maps…

High Energy Physics - Theory · Physics 2025-03-18 Ning Bao , Keiichiro Furuya , Joydeep Naskar

Contrastive learning on graphs aims at extracting distinguishable high-level representations of nodes. In this paper, we theoretically illustrate that the entropy of a dataset can be approximated by maximizing the lower bound of the mutual…

Machine Learning · Computer Science 2023-07-27 Yixuan Ma , Xiaolin Zhang , Peng Zhang , Kun Zhan

The domain of allowed von Neumann entropies of a holographic field theory carves out a polyhedral cone -- the holographic entropy cone -- in entropy space. Such polyhedral cones are characterized by their extreme rays. For an arbitrary…

High Energy Physics - Theory · Physics 2020-08-26 Temple He , Veronika E. Hubeny , Mukund Rangamani

When deploying artificial agents in real-world environments where they interact with humans, it is crucial that their behavior is aligned with the values, social norms or other requirements of that environment. However, many environments…

Machine Learning · Computer Science 2023-05-05 Mattijs Baert , Pietro Mazzaglia , Sam Leroux , Pieter Simoens

The region of entropic vectors is a convex cone that has been shown to be at the core of many fundamental limits for problems in multiterminal data compression, network coding, and multimedia transmission. This cone has been shown to be…

Information Theory · Computer Science 2015-12-11 Yunshu Liu , John MacLaren Walsh
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