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This paper introduces a new model to learn graph neural networks equivariant to rotations, translations, reflections and permutations called E(n)-Equivariant Graph Neural Networks (EGNNs). In contrast with existing methods, our work does…

Machine Learning · Computer Science 2022-02-17 Victor Garcia Satorras , Emiel Hoogeboom , Max Welling

Random networks generators like Erdoes-Renyi, Watts-Strogatz and Barabasi-Albert models are used as models to study real-world networks. Let G^1(V,E_1) and G^2(V,E_2) be two such networks on the same vertex set V. This paper studies the…

Physics and Society · Physics 2013-06-20 Chuan Wen , Loe , Henrik Jeldtoft Jensen

A classical theorem of De Bruijn and Erd\H{o}s asserts that any noncollinear set of n points in the plane determines at least n distinct lines. We prove that an analogue of this theorem holds for graphs. Restricting our attention to…

Combinatorics · Mathematics 2015-01-29 Pierre Aboulker , Guillaume Lagarde , David Malec , Abhishek Methuku , Casey Tompkins

We study the Minimum Shared Edges problem introduced by Omran et al. [Journal of Combinatorial Optimization, 2015] on planar graphs: Planar MSE asks, given a planar graph G = (V,E), two distinct vertices s,t in V , and two integers p, k,…

Computational Complexity · Computer Science 2016-02-04 Till Fluschnik , Manuel Sorge

We reconsider the problem of percolation on an equilibrium random network with degree-degree correlations between nearest-neighboring vertices focusing on critical singularities at a percolation threshold. We obtain criteria for…

Statistical Mechanics · Physics 2009-11-13 A. V. Goltsev , S. N. Dorogovtsev , J. F. F. Mendes

Leveraging topological properties in the response of electromagnetic systems can greatly enhance their potential. Although the investigation of singularity-based electromagnetics and non-Hermitian electronics has considerably increased in…

The topological (graph) structure of complex networks often provides valuable information about the performance and vulnerability of the network. However, there are multiple ways to represent a given network as a graph. Electric power…

Physics and Society · Physics 2014-05-20 Eduardo Cotilla-Sanchez , Paul D. H. Hines , Clayton Barrows , Seth Blumsack

A representation of partially spatially coherent and partially polarized stationary electromagnetic fields is given in terms of mutually uncorrelated, transversely shifted, fully coherent and polarized elementary electric-field modes. This…

Optics · Physics 2015-05-19 Jani Tervo , Jari Turunen , Pasi Vahimaa , Frank Wyrowski

Let $G=(V,E)$ be a random electronic network with the boundary vertices which is obtained by assigning a resistance of each edge in a random graph in $\mathbb{G}(n,p)$ and the voltages on the boundary vertices. In this paper, we prove that…

Combinatorics · Mathematics 2011-11-15 Da-Qian Qian , Xiao-Dong Zhang

Non-Hermitian systems hosting exceptional points (EPs) exhibit signal enhancement and unconventional mode dynamics. Going beyond isolated EPs, here we report on the existence of exceptional rings (ERs) in planar optical resonators with…

The advent of non-Hermitian physics has enriched the plethora of topological phases to include phenomena without Hermitian counterparts. Despite being among the most well-studied uniquely non-Hermitian features, the topological properties…

Mesoscale and Nanoscale Physics · Physics 2025-06-05 Marcus Stålhammar , Lukas Rødland

In this paper, we quantify voltage and current phasor-based measurement requirements for the unique estimation of the electric grid topology and admittance parameters. Our approach is underpinned by the concept of a rigidity matrix that has…

Systems and Control · Electrical Eng. & Systems 2025-02-18 Norak Rin , Iman Shames , Ian R. Petersen , Elizabeth L. Ratnam

Nested graphs have been used in different applications, for example to represent knowledge in semantic networks. On the other hand, graphs with cycles are really important in surface reconstruction, periodic schedule and network analysis.…

Combinatorics · Mathematics 2018-11-08 María Carrasco , Zenaida Castillo , Nerio Borges , Ramón Pino Pérez

This is an attempt to construct a classical microscopic model of the electron which underlies quantum mechanics. An electron is modeled, not as a point particle, but as the end of an electromagnetic string, a line of flux. These lines…

General Physics · Physics 2008-07-24 Robert L. McCarthy

This note is a modest addition to the work arXiv:2109.13952. Here we construct an embedding of the space of electrical networks to the totally non-negative Lagrangian Grassmannian in a generic situation with the help of the technique of…

Mathematical Physics · Physics 2022-03-09 Dmitry Talalaev

We present a novel $n$EPT ($n$th-order Eulerian Perturbation Theory) scheme to model the nonlinear density field by the summation up to $n$th-order density fields in perturbation theory. The obtained analytical power spectrum shows…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-13 Zhenyuan Wang , Donghui Jeong , Atsushi Taruya , Takahiro Nishimichi , Ken Osato

We study the ring of regular functions on the space of planar electrical networks, which we coin the grove algebra. This algebra is an electrical analogue of the Pl\"ucker ring studied classically in invariant theory. We develop the…

Combinatorics · Mathematics 2025-03-19 Yibo Gao , Thomas Lam , Zixuan Xu

Quantification of symmetries in complex networks is typically done globally in terms of automorphisms. Extending previous methods to locally assess the symmetry of nodes is not straightforward. Here we present a new framework to quantify…

We investigate topological aspects of sub-nm electron vortex beams upon elastic propagation through atomic scattering potentials. Two main aspects can be distinguished: (i) Significantly reduced delocalization compared to a similar…

Optics · Physics 2014-10-13 Axel Lubk , Laura Clark , Giulio Guzzinati , Jo Verbeeck

Latent Euclidean embedding models a given network by representing each node in a Euclidean space, where the probability of two nodes sharing an edge is a function of the distances between the nodes. This implies that for two nodes to share…

Social and Information Networks · Computer Science 2019-09-19 Clifford Anderson-Bergman , Phan Nguyen , Jose Cadena Pico