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The Dyson Brownian motion model for transistions to the CUE is considered. For initial eigenvalue probability density functions corresponding to the COE and CSE, the density-density correlation function between an eigenvalue at position…

chao-dyn · Physics 2015-06-24 P. J. Forrester

We present a modified Brownian motion model for random matrices where the eigenvalues (or levels) of a random matrix evolve in "time" in such a way that they never cross each other's path. Also, owing to the exact integrability of the level…

Condensed Matter · Physics 2007-05-23 Sudhir R. Jain , Zafar Ahmed

We evaluate, in the large-$N$ limit, the complete probability distribution $\mathcal{P}(A,m)$ of the values $A$ of the sum $\sum_{i=1}^{N} |\lambda_i|^m$, where $\lambda_i$ ($i=1,2,\dots, N$) are the eigenvalues of a Gaussian random matrix,…

Statistical Mechanics · Physics 2024-02-20 Alexander Valov , Baruch Meerson , Pavel V. Sasorov

The eigenvalue spectrum of the sum of large random matrices that are mutually "free", i.e., randomly rotated, can be obtained using the formalism of R-transforms, with many applications in different fields. We provide a direct…

Disordered Systems and Neural Networks · Physics 2025-04-18 Pierre Bousseyroux , Jean-Philippe Bouchaud

We compute the survival probability of an initial state, with an energy in a certain window, by means of random matrix theory. We determine its probability distribution and show that is is universal, i.e. caracterised only by the symmetry…

Chaotic Dynamics · Physics 2009-11-07 Herve Kunz

To model a complex system intrinsically separated by a barrier, we use two random Hamiltonians, coupled to each other either by a tunneling matrix element or by an intermediate transition state. We study that model in the universal limit of…

Quantum Physics · Physics 2024-04-22 H. A. Weidenmüller

Two quantum systems, each described as a random-matrix ensemble. are coupled to each other via a number of transition states. Each system is strongly coupled to a large number of channels. The average transmission probability is the product…

Quantum Physics · Physics 2024-03-14 Hans A. Weidenmüller

We demonstrate that the update of weight matrices in learning algorithms can be described in the framework of Dyson Brownian motion, thereby inheriting many features of random matrix theory. We relate the level of stochasticity to the ratio…

Disordered Systems and Neural Networks · Physics 2025-01-10 Gert Aarts , Biagio Lucini , Chanju Park

In this paper we consider an asymptotic question in the theory of the Gaussian Unitary Ensemble of random matrices. In the bulk scaling limit, the probability that there are no eigenvalues in the interval (0,2s) is given by P_s=det(I-K_s),…

Functional Analysis · Mathematics 2007-05-23 P. Deift , A. Its , I. Krasovsky , X. Zhou

We compute the full order statistics of a one-dimensional gas of fermions in a harmonic trap at zero temperature, including its large deviation tails. The problem amounts to computing the probability distribution of the $k$th smallest…

Statistical Mechanics · Physics 2014-11-05 Isaac Pérez Castillo

We offer an alternative viewpoint on Dyson's original paper regarding the application of Brownian motion to random matrix theory (RMT). In particular we show how one may use the same approach in order to study the stochastic motion in the…

Mathematical Physics · Physics 2015-03-24 Christopher H. Joyner , Uzy Smilansky

We present a simple Coulomb gas method to calculate analytically the probability of rare events where the maximum eigenvalue of a random matrix is much larger than its typical value. The large deviation function that characterizes this…

Statistical Mechanics · Physics 2009-02-27 Satya N. Majumdar , Massimo Vergassola

We study the quantum dynamics of a many-body system subject to coherent evolution and coupled to a non-Markovian bath. We propose a technique to unravel the non-Markovian dynamics in terms of quantum jumps, a connection that was so far only…

The circular Dyson Brownian motion model refers to the stochastic dynamics of the log-gas on a circle. It also specifies the eigenvalues of certain parameter-dependent ensembles of unitary random matrices. This model is considered with the…

Statistical Mechanics · Physics 2016-08-31 P. J. Forrester , T. Nagao

It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special…

Statistical Mechanics · Physics 2007-05-23 P. Leboeuf

In molecular dynamics (MD) simulations, accessing transition probabilities between states is crucial for understanding kinetic information, such as reaction paths and rates. However, standard MD simulations are hindered by the capacity to…

Chemical Physics · Physics 2025-08-07 Yanbin Wang , Jakub Rydzewski , Ming Chen

We recently proposed a method for estimation of states and parameters in stochastic differential equations, which included intermediate time points between observations and used the Laplace approximation to integrate out these intermediate…

Probability · Mathematics 2025-04-01 Uffe Høgsbro Thygesen

The goal of these expository notes is to give an introduction to random matrices for non-specialist of this topic focusing on the link between random matrices and systems of particles in interaction. We first recall some general results…

Analysis of PDEs · Mathematics 2026-02-09 Valentin Pesce

We consider $N\times N$ symmetric random matrices where the probability distribution for each matrix element is given by a measure $\nu$ with a subexponential decay. We prove that the eigenvalue spacing statistics in the bulk of the…

Mathematical Physics · Physics 2010-11-25 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau

A Gaussian fluctuation formula is proved for linear statistics of complex random matrices in the case that the statistic is rotationally invariant. For a general linear statistic without this symmetry, Coulomb gas theory is used to predict…

Statistical Mechanics · Physics 2007-05-23 P. J. Forrester
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