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Some new identities for quantum variance and covariance involving commutators are presented, in which the density matrix and the operators are treated symmetrically. A measure of entanglement is proposed for bipartite systems, based on…

Quantum Physics · Physics 2009-11-06 R I A Davis , R Delbourgo , P D Jarvis

We investigate traces of powers of random matrices whose distributions are invariant under rotations (with respect to the Hilbert--Schmidt inner product) within a real-linear subspace of the space of $n\times n$ matrices. The matrices we…

Probability · Mathematics 2023-11-30 Elizabeth S. Meckes , Mark W. Meckes

Random matrix theory allows for the deduction of stability criteria for complex systems using only a summary knowledge of the statistics of the interactions between components. As such, results like the well-known elliptical law are…

Disordered Systems and Neural Networks · Physics 2023-11-06 Lyle Poley , Tobias Galla , Joseph W. Baron

Supersymmetry is nowadays indispensable for many problems in Random Matrix Theory. It is presented here with an emphasis on conceptual and structural issues. An introduction to supermathematics is given. The Hubbard-Stratonovich…

Mathematical Physics · Physics 2012-07-16 Thomas Guhr

The eigenfunctions of quantized chaotic systems cannot be described by explicit formulas, even approximate ones. This survey summarizes (selected) analytical approaches used to describe these eigenstates, in the semiclassical limit. The…

Dynamical Systems · Mathematics 2012-01-09 Stéphane Nonnenmacher

We consider a many-parametric piecewise mapping with discontinuity. That is a one dimensional model of singular dynamic system. The stability boundary are calculated analytically and numerically. New typical features of stable cycle…

Chaotic Dynamics · Physics 2015-06-26 S. V. Naydenov , A. V. Tur , A. V. Yanovsky , V. V. Yanovsky

In this short note we collect together known results on the use of Random Matrix Theory in lattice statistical mechanics. The purpose here is two fold. Firstly the RMT analysis provides an intrinsic characterization of integrability, and…

Statistical Mechanics · Physics 2007-05-23 J. -Ch. Angles d'Auriac , J. -M. Maillard

We study heavy-tailed Hermitian random matrices that are unitarily invariant. The invariance implies that the eigenvalue and eigenvector statistics are decoupled. The motivating question has been whether a freely stable random matrix has…

Mathematical Physics · Physics 2021-09-27 Mario Kieburg , Adam Monteleone

We demonstrate the connection between an operator's matrix element distribution and entangling power via numerical simulations of random, pseudo-random, and quantum chaotic operators. Creating operators with a random distribution of matrix…

Quantum Physics · Physics 2007-05-23 Yaakov S. Weinstein , C. Stephen Hellberg

We show that the semiclassical approach to chaotic quantum transport in the presence of time-reversal symmetry can be described by a matrix model, i.e. a matrix integral whose perturbative expansion satisfies the semiclassical diagrammatic…

Chaotic Dynamics · Physics 2015-02-11 Marcel Novaes

Consider a deterministic self-adjoint matrix X_n with spectral measure converging to a compactly supported probability measure, the largest and smallest eigenvalues converging to the edges of the limiting measure. We perturb this matrix by…

Probability · Mathematics 2011-09-05 Florent Benaych-Georges , Alice Guionnet , Mylène Maïda

The complicated interactions in presence of disorder lead to a correlated randomization of states. The Hamiltonian as a result behaves like a multi-parametric random matrix with correlated elements. We show that the eigenvalue correlations…

Disordered Systems and Neural Networks · Physics 2009-11-10 Pragya Shukla

A sum of a large-dimensional random matrix polynomial and a fixed low-rank matrix polynomial is considered. The main assumption is that the resolvent of the random polynomial converges to some deterministic limit. A formula for the limit of…

Probability · Mathematics 2022-05-23 Patryk Pagacz , Michał Wojtylak

We introduce a random interaction matrix model (RIMM) for finite-size strongly interacting fermionic systems whose single-particle dynamics is chaotic. The model is applied to Coulomb blockade quantum dots with irregular shape to describe…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Y. Alhassid , Ph. Jacquod , A. Wobst

A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative…

Optimization and Control · Mathematics 2019-03-15 Melike Sirlanci , Susan E. Luczak , I. Gary Rosen

Motivated by a series of recent works, an interest in multifractal phases has risen as they are believed to be present in the Many-Body Localized (MBL) phase and are of high demand in quantum annealing and machine learning. Inspired by the…

Disordered Systems and Neural Networks · Physics 2024-01-17 Anton Kutlin , Ivan M. Khaymovich

We use random matrix theory to explore late-time chaos in supersymmetric quantum mechanical systems. Motivated by the recent study of supersymmetric SYK models and their random matrix classification, we consider the Wishart-Laguerre unitary…

High Energy Physics - Theory · Physics 2018-06-05 Nicholas Hunter-Jones , Junyu Liu

We apply Tsallis's q-indexed nonextensive entropy to formulate a random matrix theory (RMT), which may be suitable for systems with mixed regular-chaotic dynamics. We consider the super-extensive regime of q < 1. We obtain analytical…

Mathematical Physics · Physics 2011-12-06 A. Abd El-Hady , A. Y. Abul-Magd

We investigate the statistical properties of the complexness parameter which characterizes uniquely complexness (biorthogonality) of resonance eigenstates of open chaotic systems. Specifying to the regime of isolated resonances, we apply…

Other Condensed Matter · Physics 2009-11-10 Charles Poli , Dmitry Savin , Olivier Legrand , Fabrice Mortessagne

We develop and apply an approach for analyzing multi-curve data where each curve is driven by a latent state process. The state at any particular point determines a smooth function, forcing the individual curve to switch from one function…

Methodology · Statistics 2021-12-24 Camila P. E. de Souza , Nancy E. Heckman , Helena Xu