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It is long known that the best single-site coherent potential approximation (CPA) falls short of describing Anderson localization (AL). Here, we study a binary alloy disorder (or equivalently, a spinless Falicov-Kimball (FK)) model and…

Strongly Correlated Electrons · Physics 2017-09-20 P. Haldar , M. S. Laad , S. R. Hassan

The recent quantum information boom has effected a resurgence of interest in unitary coupled cluster (UCC) theory. Our group's interest in local energy landscapes of unitary ans\"atze prompted us to investigate the classical approach of…

Chemical Physics · Physics 2022-11-01 Harper R. Grimsley , Nicholas J. Mayhall

The level spacing distribution is numerically calculated at the disorder-induced metal--insulator transition for dimensionality d=4 by applying the Lanczos diagonalisation. The critical level statistics are shown to deviate stronger from…

Disordered Systems and Neural Networks · Physics 2017-09-27 I. Kh. Zharekeshev , B. Kramer

We consider the phase coherent transport of a quasi one-dimensional beam of Bose-Einstein condensed particles through a disordered potential of length L. Among the possible different types of flow identified in [T. Paul et al., Phys. Rev.…

Quantum Gases · Physics 2009-09-18 T. Paul , M. Albert , P. Schlagheck , P. Leboeuf , N. Pavloff

We study the gradual transition from one-dimensional to two-dimensional Anderson localization upon transformation of the dimensionality of disordered waveguide arrays. An effective transition from one- to two-dimensional system is achieved…

We study scaling properties of the localized eigenstates of the random dimer model in which pairs of local site energies are assigned at random in a one dimensional disordered tight-binding model. We use both the transfer matrix method and…

Condensed Matter · Physics 2009-10-28 F. M. Izrailev , T. Kottos , G. P. Tsironis

We introduce the cut averaged entanglement entropy in disordered periodic spin chains and prove it to be a concave function of subsystem size for individual eigenstates. This allows us to identify the entanglement scaling as a function of…

Strongly Correlated Electrons · Physics 2016-11-21 Xiongjie Yu , David J. Luitz , Bryan K. Clark

The propagation of light through samples with random inhomogeneities can be described by way of transmission eigenchannels, which connect incoming and outgoing external propagating modes. Although the detailed structure of a disordered…

Disordered Systems and Neural Networks · Physics 2014-04-18 A. Peña , A. Girschik , F. Libisch , S. Rotter , A. A. Chabanov

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…

Disordered Systems and Neural Networks · Physics 2015-01-23 Johann Kroha

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…

Condensed Matter · Physics 2007-05-23 V. N. Kuzovkov , W. von Niessen , V. Kashcheyevs , O. Hein

The phase diagram of correlated, disordered electron systems is calculated within dynamical mean-field theory using the H\"older mean local density of states. A critical disorder strength is determined in the Anderson-Falicov-Kimball model…

Strongly Correlated Electrons · Physics 2009-11-13 Andre M. C. Souza , Daniela de O. Maionchi , Hans J. Herrmann

We show that the tails of the asymptotic density distribution of a quantum wave packet that localizes in the the presence of random or quasiperiodic disorder can be described by the diagonal term of the projection over the eingenstates of…

Quantum Gases · Physics 2014-01-28 Marco Moratti , Michele Modugno

The use of quantum entanglement to study condensed matter systems has been flourishing in critical systems and topological phases. Additionally, using real-space entanglement entropies and entanglement spectra one can characterize localized…

Mesoscale and Nanoscale Physics · Physics 2013-12-20 Ian Mondragon-Shem , Mayukh Khan , Taylor L. Hughes

We conduct a numerical investigation into wave propagation and localization in one-dimensional lattices subject to nonlinear disorder, focusing on cases with fixed input conditions. Utilizing a discrete nonlinear Schr\"odinger equation with…

Disordered Systems and Neural Networks · Physics 2024-08-30 Ba Phi Nguyen , Kihong Kim

Anderson localisation -- the inhibition of wave propagation in disordered media -- is a surprising interference phenomenon which is particularly intriguing in two-dimensional (2D) systems. While an ideal, non-interacting 2D system of…

An effective medium approach similar to the coherent potential approximation (CPA) in the theory of disordered alloys and to the DMFT has been extended to the renormalization group equations in the local potential approximation (LPA).…

Statistical Mechanics · Physics 2019-10-14 V. I. Tokar

The scale invariant properties of wave functions in finite samples of one dimensional random systems with correlated disorder are analyzed. The random dimer model and its generalizations are considered and the wave functions are compared.…

Disordered Systems and Neural Networks · Physics 2009-10-30 Imre Varga , Janos Pipek

We investigate the probable delocalization-localization transition in open quantum systems with disorder. The disorder can induce localization in isolated quantum systems and it is generally recognized that localization is fragile under the…

Disordered Systems and Neural Networks · Physics 2025-05-28 Xuanpu Yang , Xiang-Ping Jiang , Zijun Wei , Yucheng Wang , Lei Pan

Dynamic tensor data are becoming prevalent in numerous applications. Existing tensor clustering methods either fail to account for the dynamic nature of the data, or are inapplicable to a general-order tensor. Also there is often a gap…

Machine Learning · Statistics 2018-09-17 Will Wei Sun , Lexin Li

Recent advances in center-based clustering continue to improve upon the drawbacks of Lloyd's celebrated $k$-means algorithm over $60$ years after its introduction. Various methods seek to address poor local minima, sensitivity to outliers,…

Machine Learning · Statistics 2021-10-28 Debolina Paul , Saptarshi Chakraborty , Swagatam Das , Jason Xu
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