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Random matrix theory (RMT) universality is the defining property of quantum mechanical chaotic systems, and can be probed by observables like the spectral form factor (SFF). In this paper, we describe systematic deviations from RMT…

Statistical Mechanics · Physics 2025-01-15 Rahel L. Baumgartner , Luca V. Delacrétaz , Pranjal Nayak , Julian Sonner

In the latter half of the last century, it became evident that there exists an ever increasing number of different states of the so-called elementary particles. The usual reductionist approach to this problem was to search for a simpler…

High Energy Physics - Phenomenology · Physics 2016-01-20 Krzysztof Redlich , Helmut Satz

These notes are based on the lectures delivered at the Les Houches Summer School in July 2015. They are addressed at a mixed audience of physicists and mathematicians with some basic working knowledge of random matrix theory. The first part…

Mathematical Physics · Physics 2018-07-20 Gernot Akemann

The Wigner-Dyson-Gaudin-Mehta conjecture asserts that the local eigenvalue statistics of large real and complex Hermitian matrices with independent, identically distributed entries are universal in a sense that they depend only on the…

Probability · Mathematics 2014-07-24 Laszlo Erdos

We propose a method based on the Wang-Landau algorithm to numerically generate the spectral densities of random matrix ensembles. The method employs Dyson's log-gas formalism for random matrix eigenvalues and also enables one to…

Statistical Mechanics · Physics 2013-01-28 Santosh Kumar

It recently has been found that methods of the statistical theories of spectra can be a useful tool in the analysis of spectra far from levels of Hamiltonian systems. Several examples originate from areas, such as quantitative linguistics…

Statistical Mechanics · Physics 2020-05-26 Rongrong Xie , Weibing Deng , Mauricio P. Pato

A simple model for open quantum systems is analyzed with Random Matrix Theory. The system is coupled to the continuum in a minimal way. In this paper we see the effect of opening the system on the level statistics, in particular the…

Nuclear Theory · Physics 2015-01-12 Declan Mulhall

Given a random quantum state of multiple distinguishable or indistinguishable particles, we provide an effective method, rooted in symplectic geometry, to compute the joint probability distribution of the eigenvalues of its one-body reduced…

Quantum Physics · Physics 2014-10-21 Matthias Christandl , Brent Doran , Stavros Kousidis , Michael Walter

Random geometric graphs (RGG) can be formalized as hidden-variables models where the hidden variables are the coordinates of the nodes. Here we develop a general approach to extract the typical configurations of a generic hidden-variables…

Disordered Systems and Neural Networks · Physics 2015-04-28 Massimo Ostilli , Ginestra Bianconi

Quantum chaotic systems exhibit certain universal statistical properties that closely resemble predictions from random matrix theory (RMT). With respect to observables, it has recently been conjectured that, when truncated to a sufficiently…

Statistical Mechanics · Physics 2026-01-16 Mariel Kempa , Markus Kraft , Robin Steinigeweg , Jochen Gemmer , Jiaozi Wang

The joint eigenvalue distributions of random-matrix ensembles are derived by applying the principle maximum entropy to the Renyi, Abe and Kaniadakis entropies. While the Renyi entropy produces essentially the same matrix-element…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

These lecture notes are a concise introduction of recent techniques to prove local spectral universality for a large class of random matrices. The general strategy is presented following the recent book with H.T. Yau. We extend the scope of…

Probability · Mathematics 2019-03-26 Laszlo Erdos

The random matrix ensembles (RME) of Hamiltonian matrices, e.g. Gaussian random matrix ensembles (GRME) and Ginibre random matrix ensembles (Ginibre RME), are applicable to following quantum statistical systems: nuclear systems, molecular…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

This thesis addresses two persistent and closely related challenges in modern deep learning, reliability and efficiency, through a unified framework grounded in Spectral Geometry and Random Matrix Theory (RMT). As deep networks and large…

Machine Learning · Computer Science 2026-02-27 Davide Ettori

This work analyzes singular-value spectra of weight matrices in pretrained transformer models to understand how information is stored at both ends of the spectrum. Using Random Matrix Theory (RMT) as a zero information hypothesis, we…

Machine Learning · Computer Science 2025-11-07 Max Staats , Matthias Thamm , Bernd Rosenow

Neural networks have been used successfully in a variety of fields, which has led to a great deal of interest in developing a theoretical understanding of how they store the information needed to perform a particular task. We study the…

Disordered Systems and Neural Networks · Physics 2022-11-16 Matthias Thamm , Max Staats , Bernd Rosenow

This contribution describes a statistical model for decaying quantum systems (e.g. photo-dissociation or -ionization). It takes the interference between direct and indirect decay processes explicitely into account. The resulting expressions…

Chaotic Dynamics · Physics 2009-11-11 T. Gorin

This paper gives an in-depth study of a multiple-antenna wireless communication scenario in which a weak signal received at an intermediate relay station is amplified and then forwarded to the final destination. The key quantity determining…

Exactly Solvable and Integrable Systems · Physics 2013-06-11 Yang Chen , Nazmus S. Haq , Matthew R. McKay

We introduce a random matrix framework for studying statistical-mechanical lattice systems through spectral observables. Equilibrium configurations sampled from a Boltzmann measure are mapped to matrix ensembles whose covariance structure…

Disordered Systems and Neural Networks · Physics 2026-05-21 Yaprak Önder , Abbas Ali Saberi , Roderich Moessner

We present experimentally and numerically accessible quantities that can be used to differentiate among various families of random entangled states. To this end, we analyze the entanglement properties of bipartite reduced states of a…