English
Related papers

Related papers: Spectral networks

200 papers

Degeneracies in the energy spectra of physical systems are commonly considered to be either of accidental character or induced by symmetries of the Hamiltonian. We develop an approach to explain degeneracies by tracing them back to…

Quantum Physics · Physics 2023-02-08 M. Röntgen , M. Pyzh , C. V. Morfonios , N. E. Palaiodimopoulos , F. K. Diakonos , P. Schmelcher

A geometric entropy is defined as the Riemannian volume of the parameter space of a statistical manifold associated with a given network. As such it can be a good candidate for measuring networks complexity. Here we investigate its ability…

Mathematical Physics · Physics 2017-12-20 D. Felice , R. Franzosi , S. Mancini , M. Pettini

Higher order networks are able to characterize data as different as functional brain networks, protein interaction networks and social networks beyond the framework of pairwise interactions. Most notably higher order networks include…

Disordered Systems and Neural Networks · Physics 2018-11-26 Daan Mulder , Ginestra Bianconi

We study complex networks formed by triangulations and higher-dimensional simplicial complexes representing closed evolving manifolds. In particular, for triangulations, the set of possible transformations of these networks is restricted by…

The spectral properties of the adjacency (connectivity) and distance matrix for various types of networks: exponential, scale-free (Albert--Barabasi) and classical random ones (Erdos--Renyi) are evaluated. The graph spectra for dense graph…

Disordered Systems and Neural Networks · Physics 2008-07-03 K. Malarz

Spatial dependency and spatial embedding are basic physical properties of many phenomena modeled by networks. The most indicated computational environment to deal with spatial information is to use Georeferenced Information System (GIS) and…

Graph Neural Networks (GNNs) are the subject of intense focus by the machine learning community for problems involving relational reasoning. GNNs can be broadly divided into spatial and spectral approaches. Spatial approaches use a form of…

Machine Learning · Statistics 2021-01-05 Kimberly Stachenfeld , Jonathan Godwin , Peter Battaglia

The spectral properties of traditional (dyadic) graphs, where an edge connects exactly two vertices, are widely studied in different applications. These spectral properties are closely connected to the structural properties of dyadic…

Social and Information Networks · Computer Science 2025-06-23 Hao Tian , Shengmin Jin , Reza Zafarani

There is a well-known relationship between the binary Pascal's triangle and Sierpinski triangle in which the latter obtained from the former by successive modulo 2 additions on one of its corners. Inspired by that, we define a binary…

Disordered Systems and Neural Networks · Physics 2024-03-28 Eduardo M. K. Souza , Guilherme M. A. Almeida

It is a common belief that the order of a Boolean network is mainly determined by its attractors, including fixed points and cycles. Using semi-tensor product (STP) of matrices and the algebraic state-space representation (ASSR) of Boolean…

Systems and Control · Electrical Eng. & Systems 2021-11-30 Xiao Zhang , Zhengping Ji , Daizhan Cheng

A new class of isospectral graphs is presented. These graphs are isospectral with respect to both the normalised Laplacian on the discrete graph and the standard differential Laplacian on the corresponding metric graph. The new class of…

Spectral Theory · Mathematics 2023-02-20 Pavel Kurasov , Jacob Muller

In this work we prove that every locally symmetric smooth submanifold gives rise to a naturally defined smooth submanifold of the space of symmetric matrices, called spectral manifold, consisting of all matrices whose ordered vector of…

Optimization and Control · Mathematics 2012-12-18 Aris Daniilidis , Jerome Malick , Hristo Sendov

We propose a new method for quantitative characterization of spatial network-like patterns with loops, such as surface fracture patterns, leaf vein networks and patterns of urban streets. Such patterns are not well characterized by purely…

Pattern Formation and Solitons · Physics 2015-05-20 Andrea Perna , Pascale Kuntz , Stéphane Douady

Recent evidence indicates that the abundance of recurring elementary interaction patterns in complex networks, often called subgraphs or motifs, carry significant information about their function and overall organization. Yet, the…

Disordered Systems and Neural Networks · Physics 2009-11-10 A. Vazquez , R. Dobrin , D. Sergi , J. -P. Eckmann , Z. N. Oltvai , A. -L. Barabasi

It is well-known that the behavior of many dynamical processes running on networks is intimately related to the eigenvalue spectrum of the network. In this paper, we address the problem of inferring global information regarding the…

Optimization and Control · Mathematics 2011-01-14 Victor M. Preciado , Ali Jadbabaie

Real-world systems in epidemiology, social sciences, power transportation, economics and engineering are often described as multilayer networks. Here we first define and compute the symmetries of multilayer networks, and then study the…

Chaotic Dynamics · Physics 2020-07-29 F. Della Rossa , L. Pecora , K. Blaha , A. Shirin , I. Klickstein , F. Sorrentino

The spectral theory of quantum graphs is related via an exact trace formula with the spectrum of the lengths of periodic orbits (cycles) on the graphs. The latter is a degenerate spectrum, and understanding its structure (i.e.,finding out…

Mathematical Physics · Physics 2009-11-13 U. Gavish , U. Smilansky

We report on a hitherto unnoticed type of resonances occurring in scattering from networks (quantum graphs) which are due to the complex connectivity of the graph - its topology. We consider generic open graphs and show that any cycle leads…

Chaotic Dynamics · Physics 2015-06-12 Sven Gnutzmann , Holger Schanz , Uzy Smilansky

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features…

Data Analysis, Statistics and Probability · Physics 2017-10-05 Paweł Oświȩcimka , Lorenzo Livi , Stanisław Drożdż

Spectral embedding of network adjacency matrices often produces node representations living approximately around low-dimensional submanifold structures. In particular, hidden substructure is expected to arise when the graph is generated…

Machine Learning · Statistics 2022-06-27 Francesco Sanna Passino , Nicholas A. Heard