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Recent developments have exposed close connections between quantum information and holography. In this paper, we explore the geometrical interpretations of the recently introduced $Q$-correlation and $R$-correlation, $E_Q$ and $E_R$. We…

High Energy Physics - Theory · Physics 2020-02-19 Joshua Levin , Oliver DeWolfe , Graeme Smith

We develop holographic quantum simulation techniques to prepare correlated electronic ground states in quantum matrix product state (qMPS) form, using far fewer qubits than the number of orbitals represented. Our approach starts with a…

Strongly Correlated Electrons · Physics 2022-09-14 Daoheng Niu , Reza Haghshenas , Yuxuan Zhang , Michael Foss-Feig , Garnet Kin-Lic Chan , Andrew C. Potter

The development of models for multiple heterogeneous network data is of critical importance both in statistical network theory and across multiple application domains. Although single-graph inference is well-studied, multiple graph…

Hypergraphs naturally represent group interactions, which are omnipresent in many domains: collaborations of researchers, co-purchases of items, joint interactions of proteins, to name a few. In this work, we propose tools for answering the…

Social and Information Networks · Computer Science 2020-07-21 Geon Lee , Jihoon Ko , Kijung Shin

Kauffman and Lomonaco explored the idea of understanding quantum entanglement (the non-local correlation of certain properties of particles) topologically by viewing unitary entangling operators as braiding operators. In the work of G.…

Geometric Topology · Mathematics 2018-08-01 Louis H. Kauffman , Eshan Mehrotra

We study the connection between probability distributions satisfying certain conditional independence (CI) constraints, and point and line arrangements in incidence geometry. To a family of CI statements, we associate a polynomial ideal…

Commutative Algebra · Mathematics 2021-04-01 Oliver Clarke , Fatemeh Mohammadi , Harshit J. Motwani

The success of machine learning models relies heavily on effectively representing high-dimensional data. However, ensuring data representations capture human-understandable concepts remains difficult, often requiring the incorporation of…

Machine Learning · Statistics 2024-11-01 Jiayu Su , David A. Knowles , Raul Rabadan

We study properties of the minimal cross section of entanglement wedge which connects two disconnected subsystems in holography. In particular we focus on various inequalities which are satisfied by this quantity. They suggest that it is a…

High Energy Physics - Theory · Physics 2018-12-17 Tadashi Takayanagi , Koji Umemoto

Conditional Independence (CI) graph is a special type of a Probabilistic Graphical Model (PGM) where the feature connections are modeled using an undirected graph and the edge weights show the partial correlation strength between the…

Artificial Intelligence · Computer Science 2024-10-23 Urszula Chajewska , Harsh Shrivastava

Connectivity is a central notion of graph theory and plays an important role in graph algorithm design and applications. With emerging new applications in networks, a new type of graph connectivity problem has been getting more…

Discrete Mathematics · Computer Science 2020-12-22 Rupei Xu , Warren Shull

Metasurfaces composed of subwavelength nanostructures enable simultaneous control of polarization and wavefront, greatly enhancing holographic information capacity. Building on this capability, we extend holography into the quantum domain…

We use the topological quantum field theory description of states in Chern-Simons theory to discuss the relation between spacetime connectivity and entanglement, exploring the paradigm entanglement=topology. We define a special class of…

High Energy Physics - Theory · Physics 2023-12-29 Dmitry Melnikov

We observe that the entanglement entropy resulting from tracing over a subregion of an initially pure state can grow faster than the surface area of the subregion (indeed, proportional to the volume), in contrast to examples studied…

High Energy Physics - Theory · Physics 2015-06-26 R. Buniy , S. Hsu

We build the quasiparticle picture for the tripartite mutual information (TMI) after quantum quenches in spin chains that can be mapped onto free-fermion theories. A nonzero TMI (equivalently, topological entropy) signals quantum…

Statistical Mechanics · Physics 2023-10-30 Fabio Caceffo , Vincenzo Alba

We analyze correlations between subsystems for an extended Hubbard model exactly solvable in one dimension, which exhibits a rich structure of quantum phase transitions (QPTs). The T=0 phase diagram is exactly reproduced by studying…

Strongly Correlated Electrons · Physics 2009-11-11 Alberto Anfossi , Paolo Giorda , Arianna Montorsi , Fabio Traversa

There are increasing evidences that quantum information theory has come to play a fundamental role in quantum gravity especially the holography. In this paper, we show some new potential connections between holography and quantum…

High Energy Physics - Theory · Physics 2020-08-10 Dong-Hui Du , Fu-Wen Shu , Kai-Xin Zhu

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 propose a tensor product structure that is compatible with the hypergraph structure. We define the algebraic connectivity of the $(m+1)$-uniform hypergraph in this product, and prove the relationship with the vertex connectivity. We…

Numerical Analysis · Mathematics 2023-10-10 Jiaqi Gu , Shenghao Feng , Yimin Wei

We carry out an extensive study of the holographic aspects of any-dimensional higher-derivative Einstein-Maxwell theories in a fully analytic and non-perturbative fashion. We achieve this by introducing the $d$-dimensional version of…

High Energy Physics - Theory · Physics 2022-07-13 Pablo A. Cano , Ángel Murcia , Alberto Rivadulla Sánchez , Xuao Zhang

Conditional Independence (CI) graphs are a type of probabilistic graphical models that are primarily used to gain insights about feature relationships. Each edge represents the partial correlation between the connected features which gives…

Machine Learning · Computer Science 2024-08-30 Harsh Shrivastava , Urszula Chajewska
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