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The phenomenon of Anderson localization of waves in elastic systems is studied. We analyze this phenomenon in two different set of systems: disordered linear chains of harmonic oscillators and disordered rods which oscillate with torsional…

Classical Physics · Physics 2023-07-19 R. A. Mendez-Sanchez , L. Gutierrez , A. Morales , J. Flores , A. Diaz-de-Anda , G. Monsivais

We investigate delocalization phenomena for eigenvectors of real random matrices that are invariant by orthogonal transformations. A specific phenomenon with these ensembles is that an eigenvector is typically more localized when its…

Probability · Mathematics 2026-02-12 Lucas Benigni , Simon Coste , Guillaume Dubach

We study the localization property of a two-dimensional noninteracting electron gas in the presence of randomly distributed short-range scatterers. We evaluate the participation number of the eigenstates obtained by exact diagonalization…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Z. Gedik , M. Bayindir

We report our experiments in identifying large bipartite subgraphs of simple connected graphs which are based on the sign pattern of eigenvectors belonging to the extremal eigenvalues of different graph matrices: adjacency, signless…

Spectral Theory · Mathematics 2018-06-06 Debdas Paul , Dragan Stevanovic

We prove a central limit theorem for the components of the largest eigenvectors of the adjacency matrix of a finite-dimensional random dot product graph whose true latent positions are unknown. In particular, we follow the methodology…

Statistics Theory · Mathematics 2013-12-24 Avanti Athreya , Vince Lyzinski , David J. Marchette , Carey E. Priebe , Daniel L. Sussman , Minh Tang

In this work we show that, using the eigen-decomposition of the adjacency matrix, we can consistently estimate latent positions for random dot product graphs provided the latent positions are i.i.d. from some distribution. If class labels…

Machine Learning · Statistics 2012-07-31 Daniel L. Sussman , Minh Tang , Carey E. Priebe

We analyse the eigenvectors of the adjacency matrix of a critical Erd\H{o}s-R\'enyi graph $\mathbb G(N,d/N)$, where $d$ is of order $\log N$. We show that its spectrum splits into two phases: a delocalized phase in the middle of the…

Probability · Mathematics 2021-09-01 Johannes Alt , Raphael Ducatez , Antti Knowles

We consider some random band matrices with band-width $N^\mu$ whose entries are independent random variables with distribution tail in $x^{-\alpha}$. We consider the largest eigenvalues and the associated eigenvectors and prove the…

Probability · Mathematics 2015-06-25 Florent Benaych-Georges , Sandrine Péché

We combine numerical diagonalization with a semi-analytical calculations to prove the existence of the intermediate non-ergodic but delocalized phase in the Anderson model on disordered hierarchical lattices. We suggest a new generalized…

Disordered Systems and Neural Networks · Physics 2016-10-12 B. L. Altshuler , E. Cuevas , L. B. Ioffe , V. E. Kravtsov

We consider the ensemble of adjacency matrices of Erd{\H o}s-R\'enyi random graphs, i.e.\ graphs on $N$ vertices where every edge is chosen independently and with probability $p \equiv p(N)$. We rescale the matrix so that its bulk…

Probability · Mathematics 2015-05-27 Laszlo Erdos , Antti Knowles , Horng-Tzer Yau , Jun Yin

We investigate two one-dimensional tight-binding models with disorder that have extended states at zero energy. We use exact and partial diagonalisation of the Hamiltonian to obtain the eigenmodes and the associated participation ratios,…

Disordered Systems and Neural Networks · Physics 2025-08-27 Luca Schaefer , Barbara Drossel

Random graphs defined by an occurrence probability that is invariant under node aggregation have been identified recently in the context of network renormalization. The invariance property requires that edges are drawn with a specific…

Spectral Theory · Mathematics 2025-09-18 Alessio Catanzaro , Rajat Subhra Hazra , Diego Garlaschelli

Taking into account that a proper description of disordered systems should focus on distribution functions, the authors develop a powerful numerical scheme for the determination of the probability distribution of the local density of states…

Disordered Systems and Neural Networks · Physics 2013-06-20 Gerald Schubert , Alexander Weisse , Gerhard Wellein , Holger Fehske

Using the supersymmetry method we analytically calculate the local density of states, the localiztion length, the generalized inverse participation ratios, and the distribution function of eigenvector components for the superposition of a…

Condensed Matter · Physics 2009-10-28 Klaus Frahm , Axel Müller--Groeling

This paper studies how close random graphs are typically to their expectations. We interpret this question through the concentration of the adjacency and Laplacian matrices in the spectral norm. We study inhomogeneous Erd\"os-R\'enyi random…

Probability · Mathematics 2016-08-10 Can M. Le , Elizaveta Levina , Roman Vershynin

We consider the ensemble of adjacency matrices of Erd\H{o}s-R\'{e}nyi random graphs, that is, graphs on $N$ vertices where every edge is chosen independently and with probability $p\equiv p(N)$. We rescale the matrix so that its bulk…

Probability · Mathematics 2013-07-12 László Erdős , Antti Knowles , Horng-Tzer Yau , Jun Yin

Structured epidemic models can be formulated as first-order hyperbolic PDEs, where the "spatial" variables represent individual traits, called structures. For models with two structures, we propose a numerical technique to approximate…

Numerical Analysis · Mathematics 2021-09-08 Dimitri Breda , Simone De Reggi , Francesca Scarabel , Rossana Vermiglio , Jianhong Wu

We show that almost surely the rank of the adjacency matrix of the Erd\"os-R\'enyi random graph $G(n,p)$ equals the number of non-isolated vertices for any $c\ln n/n<p<1/2$, where $c$ is an arbitrary positive constant larger than 1/2. In…

Probability · Mathematics 2007-05-23 Kevin P. Costello , Van H. Vu

The spectral and localization properties of heterogeneous random graphs are determined by the resolvent distributional equations, which have so far resisted an analytic treatment. We solve analytically the resolvent equations of random…

Disordered Systems and Neural Networks · Physics 2022-12-27 Jeferson D. Silva , Fernando L. Metz

We perform a thorough and complete analysis of the Anderson localization transition on several models of random graphs with regular and random connectivity. The unprecedented precision and abundance of our exact diagonalization data (both…

Disordered Systems and Neural Networks · Physics 2023-07-26 Piotr Sierant , Maciej Lewenstein , Antonello Scardicchio