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The graph polynomial for the number of independent sets of size $k$ in a general undirected graph is shown to be equal to an elementary symmetric polynomial of the vertex monomials, which are determined by the edges incident at the…

Combinatorics · Mathematics 2023-12-12 R. L. Streit

We show that graphs, networks and other related discrete model systems carry a natural supersymmetric structure, which, apart from its conceptual importance as to possible physical applications, allows to derive a series of spectral…

Mathematical Physics · Physics 2011-07-19 Manfred Requardt

To some extent, graph evolutionary mechanisms can be explained by its spectra. Here, we are interested in two graph operations, namely, motif (subgraph) doubling and attachment that are biologically relevant. We investigate how these two…

Combinatorics · Mathematics 2016-02-01 Ranjit Mehatari , Anirban banerjee

We study the effects of a domain deformation to the nodal set of Laplacian eigenfunctions when the eigenvalue is degenerate. In particular, we study deformations of a rectangle that perturb one side and how they change the nodal sets…

Analysis of PDEs · Mathematics 2025-01-15 Andrew Lyons

We write the spectral zeta function of the Laplace operator on an equilateral metric graph in terms of the spectral zeta function of the normalized Laplace operator on the corresponding discrete graph. To do this, we apply a relation…

Mathematical Physics · Physics 2017-11-02 Jonathan Harrison , Tracy Weyand

The Laplacian spread of a graph is the difference between the largest eigenvalue and the second-smallest eigenvalue of the Laplacian matrix of the graph. We find that the class of strongly regular graphs attains the maximum of largest…

Combinatorics · Mathematics 2014-11-25 Fan-Hsuan Lin , Chih-wen Weng

This paper deals with spectral graph theory issues related to questions of monotonicity and comparison of eigenvalues. We consider finite directed graphs with non symmetric edge weights and we introduce a special self-adjoint operator as…

Spectral Theory · Mathematics 2019-04-25 Marwa Balti

We undertake a systematic investigation of the maxima and minima of the eigenfunctions associated with the first nontrivial eigenvalue of the Laplacian on a metric graph equipped with standard (continuity--Kirchhoff) vertex conditions. This…

Spectral Theory · Mathematics 2021-05-05 James B. Kennedy , Jonathan Rohleder

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph $G_N$ with vertex set $[N] = \{1,\dots,N\}$ for which the pair of vertices $i,j \in [N]$, $i\neq j$, is connected by an edge with probability $r_N(\tfrac{i}{N},\tfrac{j}{N})$,…

Probability · Mathematics 2025-01-08 Rajat Subhra Hazra , Frank den Hollander , Maarten Markering

We consider a random Gaussian model of Laplace eigenfunctions on the hemisphere satisfying the Dirichlet boundary conditions along the equator. For this model we find a precise asymptotic law for the corresponding zero density functions, in…

Mathematical Physics · Physics 2021-02-24 Valentina Cammarota , Domenico Marinucci , Igor Wigman

Quite often real-world networks can be thought of as being symmetric, in the abstract sense that vertices can be found to have similar or equivalent structural roles. However, traditional measures of symmetry in graphs are based on their…

Probability · Mathematics 2020-09-04 Jefferson Elbert Simões , Daniel R. Figueiredo , Valmir C. Barbosa

We study the problem of predicting numeric labels that are constrained to the integers or to a subrange of the integers. For example, the number of up-votes on social media posts, or the number of bicycles available at a public rental…

Machine Learning · Computer Science 2026-04-14 Bas Maat , Peter Bloem

We investigate quantum graphs with infinitely many vertices and edges without the common restriction on the geometry of the underlying metric graph that there is a positive lower bound on the lengths of its edges. Our central result is a…

Mathematical Physics · Physics 2018-10-30 Pavel Exner , Aleksey Kostenko , Mark Malamud , Hagen Neidhardt

We study the nodal set of eigenfunctions of the Laplace operator on the right angled isosceles triangle. A local analysis of the nodal pattern provides an algorithm for computing the number of nodal domains for any eigenfunction. In…

Mathematical Physics · Physics 2015-05-30 Amit Aronovitch , Ram Band , David Fajman , Sven Gnutzmann

For certain families of finite quantum graphs, we study the question of how eigenfunctions are distributed over the graph. To characterize properties of the distribution, generalized entropies of the R\'{e}nyi and Tsallis types are…

Mathematical Physics · Physics 2017-05-22 Alexey E. Rastegin

The spectral properties of the Laplacian operator on ``small-world'' lattices, that is mixtures of unidimensional chains and random graphs structures are investigated numerically and analytically. A transfer matrix formalism including a…

Disordered Systems and Neural Networks · Physics 2009-10-31 Remi Monasson

In this paper, we prove a variant of the Burger-Brooks transfer principle which, combined with recent eigenvalue bounds for surfaces, allows to obtain upper bounds on the eigenvalues of graphs as a function of their genus. More precisely,…

Metric Geometry · Mathematics 2016-09-02 Omid Amini , David Cohen-Steiner

This paper is devoted to the investigation of the spectral theory and dynamical properties of periodic graphs which are not locally finite but carry non-negative, symmetric and summable edge weights. These graphs are shown to exhibit rather…

Spectral Theory · Mathematics 2025-06-25 Joachim Kerner , Olaf Post , Mostafa Sabri , Matthias Täufer

Motivated by problems of mathematical physics (quantum chaos) questions of equidistribution of eigenfunctions of the Laplace operator on a Riemannian manifold have been studied by several authors. We consider here, in analogy with…

Number Theory · Mathematics 2009-11-07 Siegfried Boecherer , Peter Sarnak , Rainer Schulze-Pillot

Spectral methods that are based on eigenvectors and eigenvalues of discrete graph Laplacians, such as Diffusion Maps and Laplacian Eigenmaps are often used for manifold learning and non-linear dimensionality reduction. It was previously…

Numerical Analysis · Mathematics 2015-06-02 Amit Singer , Hau-tieng Wu
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