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We calculate the Lyapunov exponents describing spatial clustering of particles advected in one- and two-dimensional random velocity fields at finite Kubo numbers Ku (a dimensionless parameter characterising the correlation time of the…

Fluid Dynamics · Physics 2013-11-11 K. Gustavsson , B. Mehlig

We study the Landau level localization and scaling properties of a disordered two-dimensional electron gas in the presence of a strong external magnetic field. The impurities are treated as random distributed scattering centers with…

Condensed Matter · Physics 2009-10-22 Dongzi Liu , S. Das Sarma

We prove the complete spectral and the strong dynamical Anderson localization in a two-particle random Schr\"odinger operators with the Poisson potential. The results apply with sufficiently weak interaction between the particle system.

Mathematical Physics · Physics 2020-07-16 Trésor Ekanga

We report on the impact of variable-scale disorder on 3D Anderson localization of a non-interacting ultracold atomic gas. A spin-polarized gas of fermionic atoms is localized by allowing it to expand in an optical speckle potential. Using a…

Quantum Gases · Physics 2015-06-16 W. R. McGehee , S. S. Kondov , W. Xu , J. J. Zirbel , B. DeMarco

The Anderson model for independent electrons in a disordered potential is transformed analytically and exactly to a basis of random extended states leading to a variant of augmented space. In addition to the widely-accepted phase diagrams…

Strongly Correlated Electrons · Physics 2007-05-23 Nigel Goldenfeld , Roger Haydock

We present a perturbative approach to disordered systems in one spatial dimension that accesses the full range of phase disorder and clarifies the connection between localization and phase information. We consider a long chain of…

Disordered Systems and Neural Networks · Physics 2024-03-04 Adrian B. Culver , Pratik Sathe , Rahul Roy

We present the relativistic analogue of Anderson localization in one dimension. We use Dirac equation to calculate the transmission probability for a spin-$\frac{1}{2}$ particle incident upon a rectangular barrier. Using the transfer matrix…

Disordered Systems and Neural Networks · Physics 2020-03-10 Abhay Mehta , Sandeep Joshi , Sudhir R. Jain

We study the localization properties of electrons moving on two-dimensional bi-partite lattices in the presence of disorder. The models investigated exhibit a chiral symmetry and belong to the chiral orthogonal (chO), chiral symplectic…

Disordered Systems and Neural Networks · Physics 2012-05-16 L. Schweitzer , P. Markos

We propose a novel framework to characterize the thermalization of many-body dynamical systems close to integrable limits using the scaling properties of the full Lyapunov spectrum. We use a classical unitary map model to investigate…

Chaotic Dynamics · Physics 2022-06-16 Merab Malishava , Sergej Flach

We develop a numerical technique to study Anderson localization in interacting electronic systems. The ground state of the disordered system is calculated with quantum Monte-Carlo simulations while the localization properties are extracted…

Disordered Systems and Neural Networks · Physics 2009-02-25 Genevieve Fleury , Xavier Waintal

A model in which a three-dimensional elastic medium is represented by a network of identical masses connected by springs of random strengths and allowed to vibrate only along a selected axis of the reference frame, exhibits an Anderson…

Disordered Systems and Neural Networks · Physics 2017-12-04 Y. M. Beltukov , S. E. Skipetrov

In various disordered systems or non-equilibrium dynamical models, the large deviations of some observables have been found to display different scalings for rare values bigger or smaller than the typical value. In the present paper, we…

Statistical Mechanics · Physics 2021-05-12 Cecile Monthus

We revisit the problem of one-dimensional Anderson localization, by providing perturbative expression for Lyapunov exponent of Anderson model with next-nearest-neighbor (nnn) hopping. By comparison with exact numerical results, we discuss…

Disordered Systems and Neural Networks · Physics 2013-11-08 Reza Sepehrinia

Products of random matrix products of $\mathrm{SL}(2,\mathbb{R})$, corresponding to transfer matrices for the one-dimensional Schr\"odinger equation with a random potential $V$, are studied. I consider both the case where the potential has…

Disordered Systems and Neural Networks · Physics 2020-09-01 Christophe Texier

We introduce a definition of a "localization width" whose logarithm is given by the entropy of the distribution of particle component amplitudes in the Lyapunov vector. Different types of localization widths are observed, for example, a…

Chaotic Dynamics · Physics 2007-05-23 Tooru Taniguchi , Gary P. Morriss

Taking into account that a proper description of disordered systems should focus on distribution functions, the authors develop a powerful numerical scheme for the determination of the probability distribution of the local density of states…

Disordered Systems and Neural Networks · Physics 2013-06-20 Gerald Schubert , Alexander Weisse , Gerhard Wellein , Holger Fehske

Scaling describes how a given quantity $Y$ that characterizes a system varies with its size $P$. For most complex systems it is of the form $Y\sim P^\beta$ with a nontrivial value of the exponent $\beta$, usually determined by regression…

Physics and Society · Physics 2019-10-16 Marc Barthelemy

The scaling behaviour of the Lyapunov exponent near the transition to chaos via type-III intermittency is determined for a generic map. A critical exponent $\beta$ expressing the scaling of the Lyapunov exponent as a function of both, the…

Chaotic Dynamics · Physics 2007-10-02 M. G. Cosenza , O. Alvarez-Llamoza , G. A. Ponce

Anomalies are known to appear in the perturbation theory for the one-dimensional Anderson model. A systematic approach to anomalies at critical points of products of random matrices is developed, classifying and analysing their possible…

Mathematical Physics · Physics 2007-05-23 Hermann Schulz-Baldes

In this article we study if a Deep Learning technique can be used to obtain an approximated value of the Lyapunov exponents of a dynamical system. Moreover, we want to know if Machine Learning techniques are able, once trained, to provide…

Dynamical Systems · Mathematics 2024-06-25 Carmen Mayora-Cebollero , Ana Mayora-Cebollero , Álvaro Lozano , Roberto Barrio