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Related papers: Measuring Entanglement in Physical Networks

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A wide range of tasks in network analysis, such as clustering network populations or identifying anomalies in temporal graph streams, require a measure of the similarity between two graphs. To provide a meaningful data summary for…

Physics and Society · Physics 2024-10-15 Helcio Felippe , Federico Battiston , Alec Kirkley

It is often desirable to assess how well a given dataset is described by a given model. In network science, for instance, one often wants to say that a given real-world network appears to come from a particular network model. In statistical…

Data-driven analysis of large social networks has attracted a great deal of research interest. In this paper, we investigate 120 real social networks and their measurement-calibrated synthetic counterparts generated by four well-known…

Social and Information Networks · Computer Science 2019-08-23 Marcell Nagy , Roland Molontay

Link prediction is one of the fundamental problems in network analysis. In many applications, notably in genetics, a partially observed network may not contain any negative examples of absent edges, which creates a difficulty for many…

Machine Learning · Statistics 2013-01-30 Yunpeng Zhao , Elizaveta Levina , Ji Zhu

The network inference problem consists of reconstructing the edge set of a network given traces representing the chronology of infection times as epidemics spread through the network. This problem is a paradigmatic representative of…

Data Structures and Algorithms · Computer Science 2013-08-14 Bruno Abrahao , Flavio Chierichetti , Robert Kleinberg , Alessandro Panconesi

Quantum entanglement between several particles is essential for applications like quantum metrology or quantum cryptography, but it is also central for foundational phenomena like quantum non-locality. This leads to the problem of…

Quantum Physics · Physics 2025-10-10 Lisa T. Weinbrenner , Otfried Gühne

We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display…

Social and Information Networks · Computer Science 2019-01-30 Alec Kirkley , George T. Cantwell , M. E. J. Newman

We develop a statistical theory to characterize correlations in weighted networks. We define the appropriate metrics quantifying correlations and show that strictly uncorrelated weighted networks do not exist due to the presence of…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Angeles Serrano , Marian Boguna , Romualdo Pastor-Satorras

We study graphs that are formed by independently-positioned needles (i.e., line segments) in the unit square. To mathematically characterize the graph structure, we derive the probability that two line segments intersect and determine…

Soft Condensed Matter · Physics 2020-10-29 Lucas Böttcher

Several real-world systems can be represented as multi-layer complex networks, i.e. in terms of a superposition of various graphs, each related to a different mode of connection between nodes. Hence, the definition of proper mathematical…

Physics and Society · Physics 2016-10-31 Valerio Gemmetto , Diego Garlaschelli

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly…

Physics and Society · Physics 2018-05-02 Justin P. Coon , Carl P. Dettmann , Orestis Georgiou

Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to…

Discrete Mathematics · Computer Science 2013-11-21 W. Ellens , R. E. Kooij

Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories.…

Data Analysis, Statistics and Probability · Physics 2017-10-25 Marc Wiedermann , Jonathan F. Donges , Jürgen Kurths , Reik V. Donner

Entangled quantum networks provide great flexibilities and scalabilities for quantum information processing or quantum Internet. Most of results are focused on the nonlocalities of quantum networks. Our goal in this work is to explore new…

Quantum Physics · Physics 2021-08-06 Ming-Xing Luo

A fundamental problem in the study of complex networks is to provide quantitative measures of correlation and information flow between different parts of a system. To this end, several notions of communicability have been introduced and…

Physics and Society · Physics 2015-04-08 Ernesto Estrada , Naomichi Hatano , Michele Benzi

This study presents a generalization for a method examining the correlation function of an arbitrary system with interactions in an Ising model to obtain a value of correlation between two arbitrary points on a network. The establishment of…

General Physics · Physics 2017-06-13 Akira Saito

A non-ergodic quantum state of a many body system is in general random as well as multi-parametric, former due to a lack of exact information due to complexity and latter reflecting its varied behavior in different parts of the Hilbert…

Quantum Physics · Physics 2023-06-21 Devanshu Shekhar , Pragya Shukla

In the context of quantum gravity, we clarify entanglement calculations on spin networks: we distinguish the gauge-invariant entanglement between intertwiners located at the nodes and the entanglement between spin states located on the…

General Relativity and Quantum Cosmology · Physics 2018-01-31 Etera R. Livine

Many natural, technological, and social systems incorporate multiway interactions, yet are characterized and measured on the basis of weighted pairwise interactions. In this article, I propose a family of models in which pairwise…

Physics and Society · Physics 2013-06-17 Eduardo López

We define the crossing graph of a given embedded graph (such as a road network) to be a graph with a vertex for each edge of the embedding, with two crossing graph vertices adjacent when the corresponding two edges of the embedding cross…

Data Structures and Algorithms · Computer Science 2017-09-20 David Eppstein , Siddharth Gupta