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We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

We investigate the spectrum of the infinitesimal generator of the continuous time random walk on a randomly weighted oriented graph. This is the non-Hermitian random nxn matrix L defined by L(j,k)=X(j,k) if k<>j and…

Probability · Mathematics 2014-02-18 Charles Bordenave , Pietro Caputo , Djalil Chafai

To understand typical dynamics of an open quantum system in continuous time, we introduce an ensemble of random Lindblad operators, which generate Markovian completely positive evolution in the space of density matrices. Spectral properties…

We study ensembles of sparse random block matrices generated from the adjacency matrix of a Erd\"os-Renyi random graph with $N$ vertices of average degree $Z$, inserting a real symmetric $d \times d$ random block at each non-vanishing…

Mathematical Physics · Physics 2022-06-22 Giovanni M. Cicuta , Mario Pernici

Theoretical analysis of biological and artificial neural networks e.g. modelling of synaptic or weight matrices necessitate consideration of the generic real-asymmetric matrix ensembles, those with varying order of matrix elements e.g. a…

Disordered Systems and Neural Networks · Physics 2025-09-15 Ratul Dutta , Pragya Shukla

Markovian population models are suitable abstractions to describe well-mixed interacting particle systems in situation where stochastic fluctuations are significant due to the involvement of low copy particles. In molecular biology,…

Quantitative Methods · Quantitative Biology 2014-01-17 Christoph Zechner , Federico Wadehn , Heinz Koeppl

We take on a Random Matrix theory viewpoint to study the spectrum of certain reversible Markov chains in random environment. As the number of states tends to infinity, we consider the global behavior of the spectrum, and the local behavior…

Probability · Mathematics 2010-06-15 Charles Bordenave , Pietro Caputo , Djalil Chafai

Sparsity is a desirable attribute. It can lead to more efficient and more effective representations compared to the dense model. Meanwhile, learning sparse latent representations has been a challenging problem in the field of computer…

Computer Vision and Pattern Recognition · Computer Science 2022-09-22 Hanao Li , Tian Han

The spectral moments of ensembles of sparse random block matrices are analytically evaluated in the limit of large order. The structure of the sparse matrix corresponds to the Erd\"os-Renyi random graph. The blocks are i.i.d. random…

Mathematical Physics · Physics 2022-04-13 Giovanni M. Cicuta , Mario Pernici

One of the simplest models for the slow relaxation and aging of glasses is the trap model by Bouchaud and others, which represents a system as a point in configuration-space hopping between local energy minima. The time evolution depends on…

Disordered Systems and Neural Networks · Physics 2018-08-01 Riccardo Giuseppe Margiotta , Reimer Kühn , Peter Sollich

We numerically analyze the spectral statistics of the multiparametric Gaussian ensembles of complex matrices with zero mean and variances with different decay routes away from the diagonals. As the latter mimics different degree of…

Disordered Systems and Neural Networks · Physics 2024-03-05 Mohd. Gayas Ansari , Pragya Shukla

A statistical description of part of a many body system often requires a non-Hermitian random matrix ensemble with nature and strength of randomness sensitive to underlying system conditions. For the ensemble to be a good description of the…

Disordered Systems and Neural Networks · Physics 2024-12-17 Mohd. Gayas Ansari , Pragya Shukla

A sparse random block matrix model suggested by the Hessian matrix used in the study of elastic vibrational modes of amorphous solids is presented and analyzed. By evaluating some moments, benchmarked against numerics, differences in the…

Disordered Systems and Neural Networks · Physics 2018-03-21 Giovanni M. Cicuta , Johannes Krausser , Rico Milkus , Alessio Zaccone

This paper examines the relationship between sparse random network architectures and neural network stability by examining the eigenvalue spectral distribution. Specifically, we generalise classical eigenspectral results to sparse…

Neurons and Cognition · Quantitative Biology 2023-10-12 Isabelle D Harris , Hamish Meffin , Anthony N Burkitt , Andre D. H Peterson

In this article we consider the spectrum of a Laplacian matrix, also known as the Markov matrix, under the independence assumption. We assume that the entries have a variance profile. Motivated by recent works on generalized Wigner matrices…

Probability · Mathematics 2021-07-13 Anirban Chatterjee , Rajat Subhra Hazra

We study the statistical and dynamic properties of the systems characterized by an ultrametric space of states and translationary non-invariant symmetric transition matrices of the Parisi type subjected to "locally constant" randomization.…

Disordered Systems and Neural Networks · Physics 2009-11-13 V. A. Avetisov , A. Kh. Bikulov , S. K. Nechaev

Sparse non-Hermitian random matrices arise in the study of disordered physical systems with asymmetric local interactions, and have applications ranging from neural networks to ecosystem dynamics. The spectral characteristics of these…

Statistical Mechanics · Physics 2024-02-21 Fernando Lucas Metz , Izaak Neri , Tim Rogers

Continuous-time Markovian evolution appears to be manifestly different in classical and quantum worlds. We consider ensembles of random generators of $N$-dimensional Markovian evolution, quantum and classical ones, and evaluate their…

Statistical Mechanics · Physics 2021-09-22 W. Tarnowski , I. Yusipov , T. Laptyeva , S. Denisov , D. Chruściński , K. Życzkowski

We study generic open quantum systems with Markovian dissipation, focusing on a class of stochastic Liouvillian operators of Lindblad form with independent random dissipation channels (jump operators) and a random Hamiltonian. We establish…

Quantum Physics · Physics 2020-08-07 Lucas Sá , Pedro Ribeiro , Tomaž Prosen

This paper studies sparse elliptic random matrix models which generalize both the classical elliptic ensembles and sparse i.i.d. matrix models by incorporating correlated entries and a tunable sparsity parameter $p_n$. Each $n\times n$…

Probability · Mathematics 2025-08-08 Jackson Carpenter , Sean O'Rourke
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