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Uncertainty quantification requires efficient summarization of high- or even infinite-dimensional (i.e., non-parametric) distributions based on, e.g., suitable point estimates (modes) for posterior distributions arising from model-specific…

Statistics Theory · Mathematics 2024-04-10 Christian Clason , Tapio Helin , Remo Kretschmann , Petteri Piiroinen

In this paper we describe a strategy to study the Anderson model of an electron in a random potential at weak coupling by a renormalization group analysis. There is an interesting technical analogy between this problem and the theory of…

Condensed Matter · Physics 2009-10-28 J. Magnen , G. Poirot , V. Rivasseau

We measure the field transmission matrix t for microwave radiation propagating through random waveguides in the crossover to Anderson localization. From these measurements, we determine the dimensionless conductance, g, and the individual…

Disordered Systems and Neural Networks · Physics 2012-02-17 Zhou Shi , Azriel Z. Genack

Consider the $n\times n$ matrix $X_n=A_n+H_n$, where $A_n$ is a $n\times n$ matrix (either deterministic or random) and $H_n$ is a $n\times n$ matrix independent from $A_n$ drawn from complex Ginibre ensemble. We study the limiting…

Mathematical Physics · Physics 2025-09-03 Roman Sarapin

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…

Mathematical Physics · Physics 2012-05-08 Victor Chulaevsky

Based on $m$-fold integrated empirical measures, we study three new classes of goodness-of-fits tests, generalizing Anderson-Darling, Cram\'er-von Mises, and Watson statistics, respectively, and examine the corresponding limiting stochastic…

Statistics Theory · Mathematics 2024-04-10 Hsien-Kuei Hwang , Satoshi Kuriki

We construct the generalized entropy optimized by a given arbitrary statistical distribution with a finite linear expectation value of a random quantity of interest. This offers, via the maximum entropy principle, a unified basis for a…

Statistical Mechanics · Physics 2009-11-07 Sumiyoshi Abe

Anderson model of noninteracting disordered electrons is studied in high spatial dimensions. We find that off-diagonal one- and two-particle propagators behave as gaussian random variables w.r.t. momentum summations. With this…

Disordered Systems and Neural Networks · Physics 2008-09-16 V. Janis , J. Kolorenc

We prove that, for a general class of random operators, the family of the unfolded eigenvalues in the localization region is asymptotically ergodic in the sense of N. Minami (see [Mi:11]). N. Minami conjectured this to be the case for…

Spectral Theory · Mathematics 2011-05-25 Frédéric Klopp

The aim of this work is to extend the results from [B2] on local eigenvalue spacings to certain 1D lattice Schrodinger with a Bernoulli potential. We assume the disorder satisfies a certain algebraic condition that enables one to invoke the…

Analysis of PDEs · Mathematics 2013-08-22 Jean Bourgain

The distribution of eigenvalues of N times N random matrices in the limit N to infinity is the solution to a variational principle that determines the ground state energy of a confined fluid of classical unit charges. This fact is a…

Mathematical Physics · Physics 2009-10-31 Michael K. -H. Kiessling , Herbert Spohn

We construct random Schr\"odinger operators, called Anderson Hamiltonians, with Dirichlet and Neumann boundary conditions for a fairly general class of singular random potentials on bounded domains. Furthermore, we construct the integrated…

Probability · Mathematics 2026-05-14 Toyomu Matsuda , Willem van Zuijlen

Inspired by the theory of quantum information, I use two non-Hermitian random matrix models - a weighted sum of circular unitary ensembles and a product of rectangular Ginibre unitary ensembles - as building blocks of three new products of…

Mathematical Physics · Physics 2012-02-27 Andrzej Jarosz

In previous work, we have shown how the description of spin may be generalized and we have worked out this generalization for the cases spin 1/2 and spin 1. In this paper, we deal with the case of spin 2 and give the generalized probability…

Quantum Physics · Physics 2007-05-23 H. V. Mweene

We present a generalization of the ETH conjecture. Using this generalization we are able to derive the fact that an arbitrary eigenstate of a general many body system may be used to represent microcanonical ensemble in any many body…

Statistical Mechanics · Physics 2014-08-18 Garry Goldstein , Natan Andrei

In this paper we develop a complete analytical framework based on Random Matrix Theory for the performance evaluation of Eigenvalue-based Detection. While, up to now, analysis was limited to false-alarm probability, we have obtained an…

Information Theory · Computer Science 2009-09-23 Federico Penna , Roberto Garello

Determining the number of common factors is an important and practical topic in high dimensional factor models. The existing literatures are mainly based on the eigenvalues of the covariance matrix. Due to the incomparability of the…

Methodology · Statistics 2019-09-25 Jianqing Fan , Jianhua Guo , Shurong Zheng

In this article we study in detail a family of random matrix ensembles which are obtained from random permutations matrices (chosen at random according to the Ewens measure of parameter $\theta>0$) by replacing the entries equal to one by…

Probability · Mathematics 2010-05-05 Joseph Najnudel , Ashkan Nikeghbali

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

A Bayesian nonparametric method of James, Lijoi \& Prunster (2009) used to predict future values of observations from normalized random measures with independent increments is modified to a class of models based on negative binomial…

Methodology · Statistics 2024-02-20 Robert C. Griffiths , Ross A. Maller , Soudabeh Shemehsavar