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We examine a purely geometric property of a point in the boundary of the numerical range of a (Hilbert space) operator that implies that such a point is a reducing essential eigenvalue of the given operator. Roughly speaking, such a…

Spectral Theory · Mathematics 2016-09-06 Norberto Salinas , Maria Victoria Velasco

Given N quantum systems prepared according to the same density operator \rho, we propose a measurement on the N-fold system which approximately yields the spectrum of \rho. The projections of the proposed observable decompose the Hilbert…

Quantum Physics · Physics 2009-11-07 M. Keyl , R. F. Werner

We turn back to the well known problem of interpretation of the Schrodinger operator with the pseudopotential being the first derivative of the Dirac function. We show that the problem in its conventional formulation contains hidden…

Spectral Theory · Mathematics 2011-06-08 Yuriy D. Golovaty , Stepan S. Man'ko

An eigenvalue problem relevant for non-linear sigma model with singular metric is considered. We prove the existence of a non-degenerate pure point spectrum for all finite values of the size R of the system. In the infrared (IR) regime…

Mathematical Physics · Physics 2008-11-26 V. A. Fateev , E. Onofri

A lower semi-definite self-adjoint linear operator in a Hilbert space is taken whose discrete spectrum is not empty and comprises at least several eigenvalues $\lambda_{min}=\lambda_1\leqslant\ldots\leqslant\lambda_m<\sigma_{ess}$. The…

Spectral Theory · Mathematics 2019-02-19 Ruslan Sharipov

In this paper, we generalize the notion of joint eigenvalues and joint spectrum of matrices and operator tupples on a bi complex Hilbert space. We observe that unlike the spectrum of a bounded operator on a bi complex Hilbert space is…

Functional Analysis · Mathematics 2024-09-17 Akshay Rane

The eigenvalues of the transmission matrix provide the basis for a full description of the statistics of steady-state transmission and conductance. At the same time, the ability to excite the sample with the waveform of specific…

Disordered Systems and Neural Networks · Physics 2015-11-25 Zhou Shi , Azriel Z. Genack

The goal of this paper is to develop numerical methods computing a few smallest elasticity transmission eigenvalues, which are of practical importance in inverse scattering theory. The problem is challenging since it is nonlinear,…

Numerical Analysis · Mathematics 2018-02-13 Xia Ji , Peijun Li , Jiguang Sun

The properties of eigenvalues of large dimensional random matrices have received considerable attention. One important achievement is the existence and identification of the limiting spectral distribution of the empirical spectral…

Combinatorics · Mathematics 2009-06-12 Wenxue Du , Xueliang Li , Yiyang Li

A discrete analog is considered for the inverse transmission eigenvalue problem, having applications in acoustics. We provide a well-posed inverse problem statement, develop a constructive procedure for solving this problem, prove…

Spectral Theory · Mathematics 2021-11-01 Natalia P. Bondarenko , Vjacheslav A. Yurko

This review presents an account of the major works done on spectra of adjacency matrices drawn on networks and the basic understanding attained so far. We have divided the review under three sections: (a) extremal eigenvalues, (b) bulk part…

Disordered Systems and Neural Networks · Physics 2018-12-20 Camellia Sarkar , Sarika Jalan

The purpose of this paper is to investigate some spectral properties of Sturm-Liouville type problems with interior singularities. Some of the mathematical aspects necessary for developing own technique presented. By applying this technique…

Classical Analysis and ODEs · Mathematics 2013-03-28 K. Aydemir , O. Sh. Mukhtarov

Random matrix theory allows one to deduce the eigenvalue spectrum of a large matrix given only statistical information about its elements. Such results provide insight into what factors contribute to the stability of complex dynamical…

Disordered Systems and Neural Networks · Physics 2025-01-30 Joseph W. Baron , Thomas Jun Jewell , Christopher Ryder , Tobias Galla

We study the spectral properties of infinitely smooth multivariate kernel matrices when the nodes form a single cluster. We show that the geometry of the nodes plays an important role in the scaling of the eigenvalues of these kernel…

Numerical Analysis · Mathematics 2026-01-12 Nuha Diab , Dmitry Batenkov

We give a characterisation of the spectral properties of linear differential operators with constant coefficients, acting on functions defined on a bounded interval, and determined by general linear boundary conditions. The boundary…

Spectral Theory · Mathematics 2013-03-22 David Andrew Smith , Beatrice Pelloni

Let $H$ be a Schr\"odinger type operator with long-range perturbation. We study the wave front set of the distribution kernel of $(H-\lambda\mp i0)^{-1}$, where $\lambda$ is in the absolutely continous spectrumof $H$.The result is a…

Analysis of PDEs · Mathematics 2016-04-26 Shu Nakamura

We study the spectrum of unbounded J-self-adjoint block operator matrices. In particular, we prove enclosures for the spectrum, provide a sufficient condition for the spectrum being real and derive variational principles for certain real…

Spectral Theory · Mathematics 2017-03-27 Matthias Langer , Michael Strauss

We consider several intriguingly connected topics in the theory of wave propagation: geometrical characterizations of radiationless sources, non-radiating incident waves, interior transmission eigenfunctions, and their applications to…

Analysis of PDEs · Mathematics 2021-03-23 Emilia Blåsten , Hongyu Liu

This article is devoted to the spectral analysis of the electro-magnetic Schr\"odinger operator on the Euclidean plane. In the semiclassical limit, we derive a pseudo-differential effective operator that allows us to describe the spectrum…

Spectral Theory · Mathematics 2022-01-26 Léo Morin , Nicolas Raymond , San Vu Ngoc

We present eigenvalue decay estimates of integral operators associated with compositional dot-product kernels. The estimates improve on previous ones established for power series kernels on spheres. This allows us to obtain the volumes of…

Machine Learning · Statistics 2021-03-01 Meyer Scetbon , Zaid Harchaoui