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We show that spectral fluctuation of interaction matrices of yeast a core protein interaction network and a metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we…

Molecular Networks · Quantitative Biology 2009-11-11 Feng Luo , Jianxin Zhong , Yunfeng Yang , Richard H. Scheuermann , Jizhong Zhou

We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world and random networks follow…

Adaptation and Self-Organizing Systems · Physics 2016-09-08 Jayendra N. Bandyopadhyay , Sarika Jalan

We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of adjacency matrix of various model networks, namely, random,…

Statistical Mechanics · Physics 2009-11-13 Sarika Jalan , Jayendra N. Bandyopadhyay

We investigate spectral fluctuations in multilayer networks within the random matrix theory (RMT) framework to characterize universal and non-universal features. The adjacency matrix of a multilayer network exhibits a block structure, with…

Mathematical Physics · Physics 2025-08-19 Himanshu Shekhar , Ashutosh Dheer , Santosh Kumar , N. Sukumar

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

We analyze eigenvalues fluctuations of the Laplacian of various networks under the random matrix theory framework. Analyses of random networks, scale-free networks and small-world networks show that nearest neighbor spacing distribution of…

Statistical Mechanics · Physics 2009-11-11 Sarika Jalan , Jayendra N. Bandyopadhyay

In this work, we study some statistical properties of the extreme eigenstates of the randomly-weighted adjacency matrices of random graphs. We focus on two random graph models: Erd\H{o}s-R\'{e}nyi (ER) graphs and random geometric graphs…

Disordered Systems and Neural Networks · Physics 2025-06-17 C. T Martínez Martínez , J. A. Méndez Bermúdez

We study the time dynamics of random density matrices generated by evolving the same pure state using a Gaussian orthogonal ensemble (GOE) of Hamiltonians. We show that the spectral statistics of the resulting mixed state is well described…

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, Random Matrix Theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior…

Disordered Systems and Neural Networks · Physics 2015-05-13 J. X. de Carvalho , Sarika Jalan , M. S. Hussein

We study spectral behavior of sparsely connected random networks under the random matrix framework. Sub-networks without any connection among them form a network having perfect community structure. As connections among the sub-networks are…

Statistical Mechanics · Physics 2015-05-13 Sarika Jalan

Correlation functions involving products and ratios of half-integer powers of characteristic polynomials of random matrices from the Gaussian Orthogonal Ensemble (GOE) frequently arise in applications of Random Matrix Theory (RMT) to…

Mathematical Physics · Physics 2015-04-23 Yan V. Fyodorov , André Nock

Random Matrix Theory (RMT) is capable of making predictions for the spectral fluctuations of a physical system only after removing the influence of the level density by unfolding the spectra. When the level density is known, unfolding is…

Statistical Mechanics · Physics 2013-12-16 Ashraf A. Abul-Magd , Adel Y. Abul-Magd

Parameter-dependent statistical properties of spectra of totally connected irregular quantum graphs with Neumann boundary conditions are studied. The autocorrelation functions of level velocities c(x) and c(w,x) as well as the distributions…

Chaotic Dynamics · Physics 2009-07-17 Oleh Hul , Petr Seba , Leszek Sirko

Mutualistic networks are used to study the structure and processes inherent to mutualistic relationships. In this paper, we introduce a random matrix ensemble (RME) representing the adjacency matrices of mutualistic networks composed by two…

Disordered Systems and Neural Networks · Physics 2021-11-10 C. T. Martínez-Martínez , J. A. Méndez-Bermúdez , Thomas Peron , Yamir Moreno

The distribution of the ratios of consecutive eigenvalue spacings of random matrices has emerged as an important tool to study spectral properties of many-body systems. This article numerically investigates the eigenvalue ratios…

Disordered Systems and Neural Networks · Physics 2022-07-13 Ankit Mishra , Tanu Raghav , Sarika Jalan

We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral…

Molecular Networks · Quantitative Biology 2015-05-18 Sarika Jalan , Norbert Solymosi , Gabör Vattay , Baowen Li

The connection between random matrices and the spectral fluctuations of complex quantum systems in a suitable limit can be explained by using the setup of random matrix theory. Higher-order spacing statistics in the $m$ superposed spectra…

Data Analysis, Statistics and Probability · Physics 2025-10-03 Sashmita Rout , Udaysinh T. Bhosale

We study the spectral properties of and spectral-crossovers between different random matrix ensembles (Poissonian, GOE, GUE) in correlated spin-chain systems, in the presence of random magnetic fields, and the scalar spin-chirality term,…

Statistical Mechanics · Physics 2023-09-26 Debojyoti Kundu , Santosh Kumar , Subhra Sen Gupta

We use ab initio electronic-structure methods to investigate random-matrix theory (RMT) universality in molecular electronic structure. Using single-reference electronic structure methods, including Hartree-Fock, configuration-interaction…

Strongly Correlated Electrons · Physics 2026-02-26 Zhen Tao , Victor Galitski

We have computed the spectral number variances of an extended random matrix ensemble predicted by Guhr's supersymmetry formula, showing a non-monotone increase of the curves that arises from an "overshoot" of the two-level correlation…

Condensed Matter · Physics 2007-05-23 Hiroshi Hasegawa , Baowen Li , Jian-Zhong Ma , Bambi Hu
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