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相关论文: Single parameter scaling in one-dimensional locali…

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By using dimensionless conductances as scaling variables, the conventional one-parameter scaling theory of localization fails for non-reciprocal non-Hermitian systems such as the Hanato-Nelson model. Here, we propose a one-parameter scaling…

无序系统与神经网络 · 物理学 2024-06-05 C. Wang , Wenxue He , X. R. Wang , Hechen Ren

We report a numerical investigation of the fluctuations of the Lyapunov exponent of a two dimensional non-interacting disordered system. While the ratio of the mean to the variance of the Lyapunov exponent is not constant, as it is in one…

无序系统与神经网络 · 物理学 2009-11-10 K. Slevin , Y. Asada , L. I. Deych

This review presents a unified view on the problem of Anderson localization in one-dimensional weakly disordered systems with short-range and long-range statistical correlations in random potentials. The following models are analyzed: the…

无序系统与神经网络 · 物理学 2012-05-15 F. M. Izrailev , A. A. Krokhin , N. M. Makarov

We numerically study the distribution function of the conductance (transmission) in the one-dimensional tight-binding Anderson and periodic-on-average superlattice models in the region of fluctuation states where single parameter scaling is…

无序系统与神经网络 · 物理学 2009-11-10 L. I. Deych , M. V. Erementchouk , A. A. Lisyansky , Alexey Yamilov , Hui Cao

The single parameter scaling hypothesis is the foundation of our understanding of the Anderson transition. However, the conductance of a disordered system is a fluctuating quantity which does not obey a one parameter scaling law. It is…

无序系统与神经网络 · 物理学 2009-11-07 Keith Slevin , Peter Markoš , Tomi Ohtsuki

We use a new eigenvalue concentration bound for the fluctuation of the sample mean of the random extternal potential in the multi-particle Anderson model and prove the spectral exponential and the strong dynamical localization. The results…

数学物理 · 物理学 2020-04-07 Trésor Ekanga

A weak-coupling scaling diagram for the Lyapunov exponent and the integrated density of states near a band edge of a random Jacobi matrix is obtained. The analysis is based on the use of a Fokker-Planck operator describing the…

数学物理 · 物理学 2009-11-13 Christian Sadel , Hermann Schulz-Baldes

We study the expansion of an initially strongly confined wave packet in a one-dimensional weak random potential with short correlation length. At long times, the expansion of the wave packet comes to a halt due to destructive interferences…

量子物理 · 物理学 2016-07-06 Juan Pablo Ramírez Valdes , Thomas Wellens

The single-parameter scaling hypothesis relating the average and variance of the logarithm of the conductance is a pillar of the theory of electronic transport. We use a maximum-entropy ansatz to explore the logarithm of the energy density,…

无序系统与神经网络 · 物理学 2017-11-22 Xiaojun Cheng , Xujun Ma , Miztli Yepez , Azriel Z. Genack , Pier A. Mello

We propose a simplified version of the Multi-Scale Analysis of tight-binding Anderson models with strongly mixing random potentials which leads directly to uniform exponential bounds on decay of eigenfunctions in arbitrarily large finite…

数学物理 · 物理学 2012-05-08 Victor Chulaevsky

We reconcile the phenomenon of mesoscopic conductance fluctuations with the single parameter scaling theory of the Anderson transition. We calculate three averages of the conductance distribution: $\exp(<\ln g>)$, $<g>$ and $1/<R>$ where…

无序系统与神经网络 · 物理学 2009-11-07 Keith Slevin , Peter Markoš , Tomi Ohtsuki

A simple Kronig-Penney model for one-dimensional (1D) mesoscopic systems with $\delta $ peak potentials is used to study numerically the influence of a spatial disorder on the conductance fluctuations and distribution at different regimes.…

无序系统与神经网络 · 物理学 2015-05-13 Rabah Benhenni , Khaled Senouci , Nouredine Zekri , Rachid Bouamrane

We analyze the conductance distribution function in the one-dimensional Anderson model of localization, for arbitrary energy. For energy at the band center the distribution function deviates from the universal form assumed in…

无序系统与神经网络 · 物理学 2007-05-23 H. Schomerus , M. Titov

The proof of Anderson localization for the 1D Anderson model with arbitrary (e.g. Bernoulli) disorder, originally given by Carmona-Klein-Martinelli in 1987, is based in part on the multi-scale analysis. Later, in the 90s, it was realized…

数学物理 · 物理学 2019-07-24 Svetlana Jitomirskaya , Xiaowen Zhu

For the weakly interacting one-dimensional multi-particle Anderson model in the continuum space of configurations, we prove the spectral exponential and the strong dynamical localization. The results require the interaction amplitude to be…

数学物理 · 物理学 2016-12-04 Trésor Ekanga

We develop an alternative scaling approach to determine the criteria for Anderson localization in one-dimensional tight-binding models with random site energies having a bandwidth that decays as a power law in space, $H_{ij} \propto |i -…

无序系统与神经网络 · 物理学 2008-10-27 Shimul Akhanjee

The Anderson localization problem in one and two dimensions is solved analytically via the calculation of the generalized Lyapunov exponents. This is achieved by making use of signal theory. The phase diagram can be analyzed in this way. In…

凝聚态物理 · 物理学 2007-05-23 V. N. Kuzovkov , W. von Niessen , V. Kashcheyevs , O. Hein

For a fast particle moving within a two-dimensional array of soft scatterers - centers of weak and short-range potential - the dependence of the Lyapunov exponent on the system parameters is studied. The use of the linearized equations for…

混沌动力学 · 物理学 2009-11-10 P. V. Elyutin

A self-consistent theory of the frequency dependent diffusion coefficient for the Anderson localization problem is presented within the tight-binding model of non-interacting electrons on a lattice with randomly distributed on-site energy…

无序系统与神经网络 · 物理学 2015-01-23 Johann Kroha

Scaling regions -- intervals on a graph where the dependent variable depends linearly on the independent variable -- abound in dynamical systems, notably in calculations of invariants like the correlation dimension or a Lyapunov exponent.…

数据分析、统计与概率 · 物理学 2023-06-08 Varad Deshmukh , Elizabeth Bradley , Joshua Garland , James D. Meiss