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A sequence of large invertible matrices given by a small random perturbation around a fixed diagonal and positive matrix induces a random dynamics on a high-dimensional sphere. For a certain class of rotationally invariant random…

Mathematical Physics · Physics 2019-07-29 Florian Dorsch , Hermann Schulz-Baldes

We place ourselves in the setting of high-dimensional statistical inference where the number of variables $p$ in a dataset of interest is of the same order of magnitude as the number of observations $n$. We consider the spectrum of certain…

Statistics Theory · Mathematics 2010-01-05 Noureddine El Karoui

Electronic transport through chaotic quantum dots exhibits universal, system independent, properties, consistent with random matrix theory. The quantum transport can also be rooted, via the semiclassical approximation, in sums over the…

Chaotic Dynamics · Physics 2013-03-06 Gregory Berkolaiko , Jack Kuipers

In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The…

Machine Learning · Computer Science 2023-03-07 Sarmad N. Mohammed , Semra Gündüç

We have discussed earlier the correlation functions of the random variables $\det(\la-X)$ in which $X$ is a random matrix. In particular the moments of the distribution of these random variables are universal functions, when measured in the…

Mathematical Physics · Physics 2009-10-31 E. Brezin , S. Hikami

We propose a random matrix modeling for the parametric evolution of eigenstates. The model is inspired by a large class of quantized chaotic systems. Its unique feature is having parametric invariance while still possessing the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 J. A. Mendez-Bermudez , Tsampikos Kottos , Doron Cohen

The family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping scalar fields of arbitrary dimension into…

Data Analysis, Statistics and Probability · Physics 2017-09-13 Lucas Lacasa , Jacopo Iacovacci

Over the past decades, a great body of theoretical and mathematical work has been devoted to random-matrix descriptions of open quantum systems. In these notes, based on lectures delivered at the Les Houches Summer School "Stochastic…

Disordered Systems and Neural Networks · Physics 2017-01-09 Henning Schomerus

We obtain expected number of arrivals, absorption probabilities and expected time until absorption for an asymmetric discrete random walk on a graph in the presence of multiple function barriers. On each edge of the graph and in each vertex…

Probability · Mathematics 2023-07-26 Theo van Uem

We treat three cubic recurrences, two of which generalize the famous iterated map $x \mapsto x (1-x)$ from discrete chaos theory. A feature of each asymptotic series developed here is a constant, dependent on the initial condition but…

Dynamical Systems · Mathematics 2025-07-16 Steven Finch

We analyze the asymptotic behavior of random variables $x(n,x\_0)$ defined by $x(0,x\_0)=x\_0$ and $x(n+1,x\_0)=A(n)x(n,x\_0)$, where $\sAn$ is a stationary and ergodic sequence of random matrices with entries in the semi-ring…

Probability · Mathematics 2007-05-23 Glenn Merlet

We consider invariant matrix processes diffusing in non-confining cubic potentials of the form $V_a(x)= x^3/3 - a x, a\in \mathbb{R}$. We construct the trajectories of such processes for all time by restarting them whenever an explosion…

Probability · Mathematics 2015-07-07 Romain Allez , Laure Dumaz

We consider one-dimensional asymmetric exclusion processes with a simple attractive interaction, where the distance between consecutive particles is not allowed to exceed a certain limit and investigate the consequences of this coupling on…

Disordered Systems and Neural Networks · Physics 2009-11-13 Róbert Juhász

We consider two different stationary random processes whose probability distributions are very close and indistinguishable by standard tests for large but limited statistics. Yet we demonstrate that these processes can be reliably…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Gursoy B. Akguc , Jorge Flores , Sergey Yu. Kun

We study transient behaviour in the dynamics of complex systems described by a set of non-linear ODE's. Destabilizing nature of transient trajectories is discussed and its connection with the eigenvalue-based linearization procedure. The…

Chaotic Dynamics · Physics 2017-08-23 Jacek Grela

We study random matrices acting on tensor product spaces which have been transformed by a linear block operation. Using operator-valued free probability theory, under some mild assumptions on the linear map acting on the blocks, we compute…

Probability · Mathematics 2016-01-26 Octavio Arizmendi , Ion Nechita , Carlos Vargas

We present a new fluid-dynamical model of traffic flow. This model generalizes the model of Aw and Rascle [SIAM J. Appl. Math. 60 916-938] and Greenberg [SIAM J. Appl. Math 62 729-745] by prescribing a more general source term to the…

Statistical Mechanics · Physics 2007-05-23 Florian Siebel , Wolfram Mauser

Traffic flow at low densities (free traffic) is characterized by a quasi-one-dimensional relation between traffic flow and vehicle density, while no such fundamental diagram exists for `synchronized' congested traffic flow. Instead, a…

Statistical Mechanics · Physics 2009-11-07 Dirk Helbing , Davide Batic , Martin Schoenhof , Martin Treiber

In this paper we investigate the ability of some recently introduced discrete kinetic models of vehicular traffic to catch, in their large time behavior, typical features of theoretical fundamental diagrams. Specifically, we address the…

Mathematical Physics · Physics 2014-03-25 Luisa Fermo , Andrea Tosin

We introduce microscopic and macroscopic stochastic traffic models including traffic accidents. The microscopic model is based on a Follow-the-Leader approach whereas the macroscopic model is described by a scalar conservation law with…

Probability · Mathematics 2021-11-19 Simone Göttlich , Thomas Schillinger