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Consider Ginibre's ensemble of $N \times N$ non-Hermitian random matrices in which all entries are independent complex Gaussians of mean zero and variance $\frac{1}{N}$. As $N \uparrow \infty$ the normalized counting measure of the…

Probability · Mathematics 2007-05-23 Brian Rider

We propose to study unitary matrix ensembles defined in terms of unitary stochastic transition matrices associated with Markov processes on graphs. We argue that the spectral statistics of such an ensemble (after ensemble averaging) depends…

Chaotic Dynamics · Physics 2009-11-07 Gregor Tanner

The role of the normalized modularity matrix in finding homogeneous cuts will be presented. We also discuss the testability of the structural eigenvalues and that of the subspace spanned by the corresponding eigenvectors of this matrix. In…

Statistics Theory · Mathematics 2013-01-23 Marianna Bolla

We address the important question of the extent to which random variables and vectors with truncated power tails retain the characteristic features of random variables and vectors with power tails. We define two truncation regimes, soft…

Probability · Mathematics 2010-01-20 Arijit Chakrabarty , Gennady Samorodnitsky

The truncation operation facilitates the articulation and analysis of several aspects of the structure of archimedean vector lattices; we investigate two such aspects in this article. We refer to archimedean vector lattices equipped with a…

Functional Analysis · Mathematics 2019-06-04 Richard N. Ball

Let $m\in \mathbb{N}$, $\alpha\in[0,1]$, and $V$ be a 1-periodic complex-valued distribution in the negative Sobolev space $H^{-m\alpha}[0,1]$. The singular non-self-adjoint eigenvalue problem $D^{2m}u+V u=\lambda u$, $D=-i d/dx$, with…

Functional Analysis · Mathematics 2014-03-12 Vladimir Mikhailets , Volodymyr Molyboga

We present a new technique to obtain polynomial decay estimates for the matrix coefficients of unitary operators. Our approach, based on commutator methods, applies to nets of unitary operators, unitary representations of topological…

Mathematical Physics · Physics 2021-09-02 S. Richard , R. Tiedra de Aldecoa

We numerically analyze the random matrix ensembles of real-symmetric matrices with column/row constraints for many system conditions e.g. disorder type, matrix-size and basis-connectivity. The results reveal a rich behavior hidden beneath…

Statistical Mechanics · Physics 2015-10-28 Suchetana Sadhukhan , Pragya Shukla

In these proceedings we summarise how the determinantal structure for the conditional overlaps among left and right eigenvectors emerges in the complex Ginibre ensemble at finite matrix size. An emphasis is put on the underlying structure…

Mathematical Physics · Physics 2023-07-19 Gernot Akemann , Roger Tribe , Athanasios Tsareas , Oleg Zaboronski

Consider $n$ linearly independent vectors in $\mathbb{C}^n$ which form columns of a matrix $A$. The recursive evaluation of eigen directions (normalized eigenvectors) of $A$ is the solution of an eigenvalue problem of the form…

General Mathematics · Mathematics 2025-11-28 M Hariprasad

Concatenating matrices is a common technique for uncovering shared structures in data through singular value decomposition (SVD) and low-rank approximations. The fundamental question arises: How does the singular value spectrum of the…

Machine Learning · Computer Science 2025-07-01 Maksym Shamrai

Consider a matrix function f defined for Hermitian matrices. The purpose of this paper is two-fold. We derive new results for the absolute structured condition number of the matrix function and we derive new bounds for the perturbation…

Numerical Analysis · Mathematics 2012-06-20 Elias Jarlebring , Emanuel H. Rubensson

We analyze the problem of global reconstruction of functions as accurately as possible, based on partial information in the form of a truncated power series at some point, and additional analyticity properties. This situation occurs…

Complex Variables · Mathematics 2022-05-30 Ovidiu Costin , Gerald V. Dunne

In this paper, subnormal operators, not necessarily bounded, are discussed as generalized observables. In order to describe not only the information about the probability distribution of the output data of their measurement but also a…

Quantum Physics · Physics 2009-11-06 Masahito Hayashi , Fuminori Sakaguchi

We consider the overlap of Bethe vectors of the XXX spin chain with a diagonal twist and the modified Bethe vectors with a general twist. We find a determinant representation for this overlap under one additional condition on the twist…

Mathematical Physics · Physics 2021-11-03 S. Belliard , N. A. Slavnov

An ensemble of random unistochastic (orthostochastic) matrices is defined by taking squared moduli of elements of random unitary (orthogonal) matrices distributed according to the Haar measure on U(N) (or O(N), respectively). An ensemble of…

Chaotic Dynamics · Physics 2009-11-07 K. Zyczkowski , W. Slomczynski , M. Kus , H. -J. Sommers

Tangent numbers $T_{2n-1}$, which enumerate alternating permutations of odd length, play a prominent role in the Taylor series expansion of the tangent function $\tan(x)$. In this work, we adopt a combinatorial approach based on the…

Combinatorics · Mathematics 2026-03-25 Jean-Christophe Pain

This paper investigates the decay rate of the probability that the row sum of a triangular array of truncated heavy tailed random variables is larger than an integer (k) times the truncating threshold, as both - the number of summands and…

Probability · Mathematics 2017-03-21 Arijit Chakrabarty

Ensemble learning is a popular technique to improve the accuracy of machine learning models. It traditionally hinges on the rationale that aggregating multiple weak models can lead to better models with lower variance and hence higher…

Optimization and Control · Mathematics 2026-01-06 Huajie Qian , Donghao Ying , Henry Lam , Wotao Yin

As an important problem in causal inference, we discuss the identification and estimation of treatment effects (TEs) under limited overlap; that is, when subjects with certain features belong to a single treatment group. We use a latent…

Machine Learning · Statistics 2022-04-22 Pengzhou Wu , Kenji Fukumizu
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