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This paper introduces the fractal interpolation problem defined over domains with a nonlinear partition. This setting generalizes known methodologies regarding fractal functions and provides a new holistic approach to fractal interpolation.…

Metric Geometry · Mathematics 2022-08-31 Peter R. Massopust

We study the noncommutative superspace of arbitrary dimensions in a systematic way. Superfield theories on a noncommutative superspace can be formulated in two folds, through the star product formalism and in terms of the supermatrices. We…

High Energy Physics - Theory · Physics 2016-09-06 Jeong-Hyuck Park

We introduce graph width parameters, called $\alpha$-edge-crossing width and edge-crossing width. These are defined in terms of the number of edges crossing a bag of a tree-cut decomposition. They are motivated by edge-cut width, recently…

Data Structures and Algorithms · Computer Science 2025-07-31 Yeonsu Chang , O-joung Kwon , Myounghwan Lee

We introduce and study the concept which we call the splitting of a graph and compare algebraic properties of the edge ideals of graphs and those of their splitting graphs.

Commutative Algebra · Mathematics 2019-08-27 Jürgen Herzog , Somayeh Moradi , Masoomeh Rahimbeigi

We introduce the concept of entanglement width as measure of the spatial distribution of entanglement in multiparticle systems. We develop criteria to detect the width of entanglement using global observables such as energy and magnetic…

Quantum Physics · Physics 2017-02-02 Sabine Wölk , Otfried Gühne

We show that the tangle space of a graph, which compactifies it, is a quotient of its Stone-\v{C}ech remainder obtained by contracting the connected components.

General Topology · Mathematics 2019-10-23 Jan Kurkofka , Max Pitz

Spectral graph theory is well known and widely used in computer vision. In this paper, we analyze image segmentation algorithms that are based on spectral graph theory, e.g., normalized cut, and show that there is a natural connection…

Computer Vision and Pattern Recognition · Computer Science 2016-11-09 Chengxi Ye , Yuxu Lin , Mingli Song , Chun Chen , David W. Jacobs

We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function of two vertices denotes the similarity or proximity of the…

Machine Learning · Computer Science 2010-07-27 Jérôme Kunegis , Ernesto W. De Luca , Sahin Albayrak

Fair graph partition of social networks is a crucial step toward ensuring fair and non-discriminatory treatments in unsupervised user analysis. Current fair partition methods typically consider node balance, a notion pursuing a…

Social and Information Networks · Computer Science 2023-07-18 Tingwei Liu , Peizhao Li , Hongfu Liu

In differential topology two smooth submanifolds $S_1$ and $S_2$ of euclidean space are said to be transverse if the tangent spaces at each common point together form a spanning set. The purpose of this article is to explore a much more…

Classical Analysis and ODEs · Mathematics 2022-03-15 Jonathan Bennett , Neal Bez

Bach et al. [1] recently presented an algorithm for constructing confluent drawings, by leveraging power graph decomposition to generate an auxiliary routing graph. We identify two issues with their method which we call the node split and…

Computational Geometry · Computer Science 2019-09-04 Jonathan X. Zheng , Samraat Pawar , Dan F. M. Goodman

We introduce an abstract framework for the study of clustering in metric graphs: after suitably metrising the space of graph partitions, we restrict Laplacians to the clusters thus arising and use their spectral gaps to define several…

Spectral Theory · Mathematics 2020-05-05 James B. Kennedy , Pavel Kurasov , Corentin Léna , Delio Mugnolo

Recently, many researchers have been focusing on the definition of neural networks for graphs. The basic component for many of these approaches remains the graph convolution idea proposed almost a decade ago. In this paper, we extend this…

Machine Learning · Computer Science 2018-11-27 Dinh Van Tran , Nicolò Navarin , Alessandro Sperduti

Graph convolutional networks are a popular class of deep neural network algorithms which have shown success in a number of relational learning tasks. Despite their success, graph convolutional networks exhibit a number of peculiar features,…

Machine Learning · Computer Science 2022-08-22 Thomas Gebhart

Based on the previously proposed concept Understanding Tree, this paper introduces two concepts: Understanding Graph and Understanding Map, and explores their potential applications. Understanding Graph and Understanding Map can be deemed…

Human-Computer Interaction · Computer Science 2017-11-20 Gangli Liu

In several unified field theories the torsion trace is set equal to the electromagnetic potential. Using fibre bundle techniques we show that this is no leading principle but a formal consequence of another geometric relation between…

High Energy Physics - Theory · Physics 2008-02-03 Kenichi Horie

A new form of local unitary (LU) transformation invariant is given for multi-qubit states . The general relation between tangle and the LU transformation invariant of pure three and four-qubit states is given. We find that the tangle…

Quantum Physics · Physics 2014-04-22 Xin-wei Zha , Yun-Guang Zhang , Jian-Xia Qi , Hai-Yang Song

The need to harmonise apparently irreconcilable arrangements in an ecosystem --nestedness and segregation-- has triggered so far different strategies. Methodological refinements, or the inclusion of behavioural preferences to the network…

Physics and Society · Physics 2018-07-13 Albert Solé-Ribalta , Claudio J. Tessone , Carlo G. Ferrari , Javier Borge-Holthoefer

The degree distribution is one of the most fundamental graph properties of interest for real-world graphs. It has been widely observed in numerous domains that graphs typically have a tailed or scale-free degree distribution. While the…

Data Structures and Algorithms · Computer Science 2015-11-30 Olivia Simpson , C. Seshadhri , Andrew McGregor

Hereby we inspect two-partite entanglement using thought experiment that relates properties of incoherently mixed states to the impossibility of faster-than-light (FTL) signalling. We show that if there appears a way to distinguish…

Quantum Physics · Physics 2020-01-27 Stanislav Filatov , Marcis Auzinsh