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We consider discrete one-dimensional Schr\"odinger operators whose potentials are generated by H\"older continuous sampling along the orbits of a uniformly hyperbolic transformation. For any ergodic measure satisfying a suitable bounded…

Spectral Theory · Mathematics 2024-02-02 Artur Avila , David Damanik , Zhenghe Zhang

We investigate the scaling properties of eigenstates of a one-dimensional (1D) Anderson model in the presence of a constant electric field. The states show a transition from exponential to factorial localization. For infinite systems this…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matthias Weiss , Tsampikos Kottos , Theo Geisel

Using numerical exact diagonalization, we study matrix elements of a local spin operator in the eigenbasis of two different nonintegrable quantum spin chains. Our emphasis is on the question to what extent local operators can be represented…

Statistical Mechanics · Physics 2020-10-27 Jonas Richter , Anatoly Dymarsky , Robin Steinigeweg , Jochen Gemmer

In this paper we study the local spectral statistics in the localised region of various random operator models, including the $d$-dimensional the Anderson model and random Schr\"odinger operators. It is already established, in the above…

Spectral Theory · Mathematics 2024-10-08 M. Krishna

When studying high-dimensional dynamical systems such as macromolecules, quantum systems and polymers, a prime concern is the identification of the most probable states and their stationary probabilities or free energies. Often, these…

Data Analysis, Statistics and Probability · Physics 2013-01-01 Hao Wu , Frank Noé

The Eigenstate Thermalization Hypothesis (ETH) was developed as a framework for understanding how the principles of statistical mechanics emerge in the long-time limit of isolated quantum many-body systems. Since then, ETH has shifted the…

Statistical Mechanics · Physics 2025-12-01 Elisa Vallini , Laura Foini , Silvia Pappalardi

We propose an Anderson Acceleration (AA) scheme for the adaptive Expectation-Maximization (EM) algorithm for unsupervised learning a finite mixture model from multivariate data (Figueiredo and Jain 2002). The proposed algorithm is able to…

Machine Learning · Computer Science 2020-09-29 Truong Nguyen , Guangye Chen , Luis Chacon

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

We prove a unique continuation principle for spectral projections of Schr\" odinger operators. We consider a Schr\" odinger operator $H= -\Delta + V$ on $\mathrm{L}^2(\mathbb{R}^d)$, and let $H_{\Lambda}$ denote its restriction to a finite…

Mathematical Physics · Physics 2013-01-10 Abel Klein

In this work, we study the spectral statistics for Anderson model on $\ell^2(\mathbb{N})$ with decaying randomness whose single site distribution has unbounded support. Here we consider the operator $H^\omega$ given by $(H^\omega…

Spectral Theory · Mathematics 2018-05-21 Anish Mallick , Dhriti Ranjan Dolai

We study the universality of spectral statistics of large random matrices. We consider $N\times N$ symmetric, hermitian or quaternion self-dual random matrices with independent, identically distributed entries (Wigner matrices) where the…

Mathematical Physics · Physics 2015-05-18 Laszlo Erdos

To investigate whether treating cancer patients with erythropoiesis-stimulating agents (ESAs) would increase the mortality risk, Bennett et al. [Journal of the American Medical Association 299 (2008) 914--924] conducted a meta-analysis with…

Applications · Statistics 2010-10-11 Rui Wang , Lu Tian , Tianxi Cai , L. J. Wei

We develop and evaluate point and interval estimates for the random effects $\theta_i$, having made observations $y_i|\theta_i\stackrel{\m athit{ind}}{\sim}N[\theta_i,V_i],i=1,...,k$ that follow a two-level Normal hierarchical model.…

Methodology · Statistics 2011-08-17 Carl Morris , Ruoxi Tang

The recently developed energy-scale-dependent Composite Operator Method is applied to the single-impurity Anderson model. A fully self-consistent solution is given and analyzed. At very low temperatures, the density of states presents, on…

Strongly Correlated Electrons · Physics 2007-05-23 Adolfo Avella , Ferdinando Mancini , Roland Hayn

This paper concerns the use of the expectation-maximisation (EM) algorithm for inference in partially observed diffusion processes. In this context, a well known problem is that all except a few diffusion processes lack closed-form…

Statistics Theory · Mathematics 2010-08-18 Jimmy Olsson , Jonas Ströjby

We consider a single particle spectrum as given by the eigenvalues of the Wigner-Dyson ensembles of random matrices, and fill consecutive single particle levels with n fermions. Assuming that the fermions are non-interacting, we show that…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 O. Bohigas , P. Leboeuf , M. J. Sanchez

In this work we consider the Anderson model on the $d$-dimensional lattice with the single site potential having singular distribution, mainly $\alpha$-H\"older continuous ones and show that the eigenvalue statistics is Poisson in the…

Spectral Theory · Mathematics 2014-08-20 Dhriti Ranjan Dolai , M. Krishna

We prove the Wegner bounds for the one-dimensional interacting multi-particle Anderson models in the continuum. The results apply to singular probability distribution functions such as the Bernoulli's measures. The proofs need the amplitude…

Mathematical Physics · Physics 2017-06-20 Trésor Ekanga

We study the multi-particle Anderson model in the continuum and show that under some mild assumptions on the random external potential and the inter-particle interaction, for any finite number of particles, the multi-particle lower edges of…

Mathematical Physics · Physics 2017-02-15 Trésor Ekanga

Unlike traditional evolutionary algorithms which produce offspring via genetic operators, Estimation of Distribution Algorithms (EDAs) sample solutions from probabilistic models which are learned from selected individuals. It is hoped that…

Neural and Evolutionary Computing · Computer Science 2018-02-05 Per Kristian Lehre , Phan Trung Hai Nguyen