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Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elements can have different variances and be correlated with each…

Disordered Systems and Neural Networks · Physics 2016-12-21 Alexander Kuczala , Tatyana O. Sharpee

We revisit the problem of Brownian diffusion with drift in order to study finite-size effects in the geometric Galton-Watson branching process. This is possible because of an exact mapping between one-dimensional random walks and geometric…

Statistical Mechanics · Physics 2018-07-04 Alvaro Corral , Rosalba Garcia-Millan , Nicholas R. Moloney , Francesc Font-Clos

We formulate gaussian and circular random-matrix models representing a coupled system consisting of an absorbing and an amplifying resonator, which are mutually related by a generalized time-reversal symmetry. Motivated by optical…

Quantum Physics · Physics 2012-12-21 Christopher Birchall , Henning Schomerus

Recent studies on the phenomenology of ageing in certain many-particle systems which are at a critical point of their non-equilibrium steady-states, are reviewed. Examples include the contact process, the parity-conserving…

Statistical Mechanics · Physics 2007-05-23 Malte Henkel

The time evolution of a bounded quantum system is considered in the framework of the orthogonal, unitary and symplectic circular ensembles of random matrix theory. For an $N$ dimensional Hilbert space we prove that in the large $N$ limit…

Mesoscale and Nanoscale Physics · Physics 2008-02-03 P. Leboeuf , G. Iacomelli

This paper studies a high-dimensional inference problem involving the matrix tensor product of random matrices. This problem generalizes a number of contemporary data science problems including the spiked matrix models used in sparse…

Information Theory · Computer Science 2020-12-18 Galen Reeves

We investigate the spectra of adjacency matrices of multiplex networks under random matrix theory (RMT) framework. Through extensive numerical experiments, we demonstrate that upon multiplexing two random networks, the spectra of the…

Statistical Mechanics · Physics 2021-11-10 Tanu Raghav , Sarika Jalan

We generalize the diffusion-limited aggregation by issuing many randomly-walking particles, which stick to a cluster at the discrete time unit providing its growth. Using simple combinatorial arguments we determine probabilities of…

Statistical Mechanics · Physics 2017-05-24 Oleg Alekseev , Mark Mineev-Weinstein

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

The diagonal elements of the time correlation matrix are used to probe closed quantum systems that are measured at random times. This enables us to extract two distinct parts of the quantum evolution, a recurrent part and an exponentially…

Quantum Gases · Physics 2021-09-29 Klaus Ziegler

The one-dimensional totally asymmetric simple exclusion process (TASEP) is considered. We study the time evolution property of a tagged particle in TASEP with the step-type initial condition. Calculated is the multi-time joint distribution…

Mathematical Physics · Physics 2007-08-18 T. Imamura , T. Sasamoto

We theoretically study quantum spin transport in a one-dimensional folded XXZ model with an alternating domain-wall initial state via the Bethe ansatz technique, exactly demonstrating that a probability distribution of finding a left-most…

Statistical Mechanics · Physics 2024-12-31 Kazuya Fujimoto , Tomohiro Sasamoto

Let $\aip(t)$ be the Airy$_2$ process. We show that the random variable [\sup_{t\leq\alpha}\{aip(t)-t^2}+\min{0,\alpha}^2] has the same distribution as the one-point marginal of the Airy$_{2\to1}$ process at time $\alpha$. These marginals…

Probability · Mathematics 2020-10-15 Jeremy Quastel , Daniel Remenik

We study a class of interacting particle systems on $\mathbb{R}$ which was recently investigated by F. G\"otze and the second author [GV14]. These ensembles generalize eigenvalue ensembles of Hermitian random matrices by allowing different…

Probability · Mathematics 2018-05-31 Thomas Kriecherbauer , Martin Venker

In this paper we describe a strategy to study the Anderson model of an electron in a random potential at weak coupling by a renormalization group analysis. There is an interesting technical analogy between this problem and the theory of…

Condensed Matter · Physics 2009-10-28 J. Magnen , G. Poirot , V. Rivasseau

Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary…

Soft Condensed Matter · Physics 2015-09-10 Vladimir Mityushev

Interacting random matrix systems are fundamental to modern theoretical physics and data science, yet a unified framework for their analysis has been lacking. This work introduces such a universal framework, built upon two novel concepts:…

Probability · Mathematics 2025-10-24 Cong Chen , Yong Li

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

Distributional approximations of (bi--) linear functions of sample variance-covariance matrices play a critical role to analyze vector time series, as they are needed for various purposes, especially to draw inference on the dependence…

Probability · Mathematics 2018-03-20 Ansgar Steland , Rainer von Sachs

Complex networks with directed, local interactions are ubiquitous in nature, and often occur with probabilistic connections due to both intrinsic stochasticity and disordered environments. Sparse non-Hermitian random matrices arise…

Disordered Systems and Neural Networks · Physics 2019-12-04 Grace H. Zhang , David R. Nelson