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Three recently suggested random matrix ensembles (RME) are linked together by an exact mapping and plausible conjections. Since it is known that in one of these ensembles the eigenvector statistics is multifractal, we argue that all three…

Condensed Matter · Physics 2009-10-30 V. E. Kravtsov , K. A. Muttalib

We introduce a class of models containing robust and analytically demonstrable multifractality induced by disorder correlations. Specifically, we investigate the statistics of eigenstates of disordered tight-binding models on two classes of…

Disordered Systems and Neural Networks · Physics 2025-11-27 David E. Logan , Sthitadhi Roy

Multifractal systems usually have singularity spectra defined on bounded sets of H\"older exponents. As a consequence, their associated multifractal scaling exponents are expected to depend linearly upon statistical moment orders at high…

Fluid Dynamics · Physics 2021-06-30 L. Moriconi

Multifractal analysis is a powerful approach for characterizing ergodic or localized nature of eigenstates in complex quantum systems. In this context, the eigenvectors of random matrices belonging to invariant ensembles naturally serve as…

Quantum Physics · Physics 2023-10-06 Ayana Sarkar , Ashutosh Dheer , Santosh Kumar

Fractal dimensions of eigenfunctions for various critical random matrix ensembles are investigated in perturbation series in the regimes of strong and weak multifractality. In both regimes we obtain expressions similar to those of the…

Chaotic Dynamics · Physics 2011-09-26 E. Bogomolny , O. Giraud

We study multifractality in a broad class of disordered systems which includes, e.g., the diluted x-y model. Using renormalized field theory we analyze the scaling behavior of cumulant averaged dynamical variables (in case of the x-y model…

Statistical Mechanics · Physics 2009-11-10 Olaf Stenull

Multifractal dimensions allow for characterizing the localization properties of states in complex quantum systems. For ergodic states the finite-size versions of fractal dimensions converge to unity in the limit of large system size.…

Statistical Mechanics · Physics 2019-10-30 Arnd Bäcker , Masudul Haque , Ivan M. Khaymovich

Multifractal behavior has been identified and mathematically established for large classes of functions, stochastic processes and measures. Multifractality has also been observed on many data coming from Geophysics, turbulence, Physics,…

Classical Analysis and ODEs · Mathematics 2020-02-03 Stephane Seuret

Disordered systems present multifractal properties at criticality. In particular, as discovered by Ludwig (A.W.W. Ludwig, Nucl. Phys. B 330, 639 (1990)) on the case of diluted two-dimensional Potts model, the moments $\bar{\rho^q(r)}$ of…

Disordered Systems and Neural Networks · Physics 2007-08-22 Cecile Monthus , Thomas Garel

Due to their analytical tractability, random matrix ensembles serve as robust platforms for exploring exotic phenomena in systems that are computationally demanding. Building on a companion letter [arXiv:2312.17481], this paper investigates…

Disordered Systems and Neural Networks · Physics 2024-08-01 Weitao Chen , Olivier Giraud , Jiangbin Gong , Gabriel Lemarié

Higher order parametric level correlations in disordered systems with broken time-reversal symmetry are studied by mapping the problem onto a model of coupled Hermitian random matrices. Closed analytical expression is derived for parametric…

Disordered Systems and Neural Networks · Physics 2009-10-31 E. Kanzieper , V. Freilikher

The Boltzmann-Gibbs probability distributions generated by logarithmically correlated random potentials provide a simple yet nontrivial example of disorder-induced multifractal measures. We introduce and discuss two analytically tractable…

Disordered Systems and Neural Networks · Physics 2015-05-14 Yan V Fyodorov

Mixed-frequency Vector AutoRegressions (MF-VAR) model the dynamics between variables recorded at different frequencies. However, as the number of series and high-frequency observations per low-frequency period grow, MF-VARs suffer from the…

Econometrics · Economics 2022-03-21 Alain Hecq , Marie Ternes , Ines Wilms

This paper studies the high-dimensional mixed linear regression (MLR) where the output variable comes from one of the two linear regression models with an unknown mixing proportion and an unknown covariance structure of the random…

Methodology · Statistics 2020-11-10 Linjun Zhang , Rong Ma , T. Tony Cai , Hongzhe Li

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 study the approximation of expectations $\E(f(X))$ for solutions $X$ of SDEs and functionals $f \colon C([0,1],\R^r) \to \R$ by means of restricted Monte Carlo algorithms that may only use random bits instead of random numbers. We…

Numerical Analysis · Mathematics 2019-01-21 Michael B. Giles , Mario Hefter , Lukas Mayer , Klaus Ritter

The distribution function of local amplitudes of eigenstates of a two-dimensional disordered metal is calculated. Although the distribution of comparatively small amplitudes is governed by laws similar to those known from the random matrix…

Condensed Matter · Physics 2016-08-31 Vladimir I. Fal'ko , K. B. Efetov

We study the spectral properties of the adjacency matrix in the giant connected component of Erd\"os-R\'enyi random graphs, with average connectivity $p$ and randomly distributed hopping amplitudes. By solving the self-consistent cavity…

Disordered Systems and Neural Networks · Physics 2024-11-14 Leticia F. Cugliandolo , Grégory Schehr , Marco Tarzia , Davide Venturelli

The construction of multigrid operators for disordered linear lattice operators, in particular the fermion matrix in lattice gauge theories, by means of algebraic multigrid and block LU decomposition is discussed. In this formalism, the…

High Energy Physics - Lattice · Physics 2016-09-01 Christoph Best

This thesis presents original results in two domains of disordered statistical physics: logarithmic correlated Random Energy Models (logREMs), and localization transitions in long-range random matrices. In the first part devoted to logREMs,…

Disordered Systems and Neural Networks · Physics 2017-05-22 Xiangyu Cao
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