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The research on spectral inequalities for discrete Schrodinger Operators has proved fruitful in the last decade. Indeed, several authors analysed the operator's canonical relation to a tridiagonal Jacobi matrix operator. In this paper, we…

Functional Analysis · Mathematics 2013-12-09 Arman Sahovic

In arXiv:1306.2914 a method for approximate solution of Sturm-Liouville equations and related spectral problems was presented based on the construction of the Delsarte transmutation operators. The problem of numerical approximation of…

Classical Analysis and ODEs · Mathematics 2016-09-06 Vladislav V. Kravchenko , Sergii M. Torba

In this paper, we establish various maximal principles and develop the direct moving planes and sliding methods for equations involving the physically interesting (nonlocal) pseudo-relativistic Schr\"{o}dinger operators…

Analysis of PDEs · Mathematics 2020-04-07 Wei Dai , Guolin Qin , Dan Wu

The eikonal approximation for moderately small scattering amplitudes is considered. With the purpose of using for their numerical estimations, the formulas are derived which contain no Bessel functions, and, hence, no rapidly oscillating…

Mathematical Physics · Physics 2016-09-21 A. V. Kisselev

Given a finite set $X\subseteq\R$ we characterize the diagonals of self-adjoint operators with spectrum $X$. Our result extends the Schur-Horn theorem from a finite dimensional setting to an infinite dimensional Hilbert space analogous to…

Functional Analysis · Mathematics 2014-05-29 Marcin Bownik , John Jasper

We present a method for improving a Non Local Means operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original Non Local Means operator. This results in an…

Computer Vision and Pattern Recognition · Computer Science 2014-12-08 Victor May , Yosi Keller , Nir Sharon , Yoel Shkolnisky

We develop a general technique for finding self-adjoint extensions of a symmetric operator that respect a given set of its symmetries. Problems of this type naturally arise when considering two- and three-dimensional Schr\"odinger operators…

Mathematical Physics · Physics 2010-12-14 D. M. Gitman , A. G. Smirnov , I. V. Tyutin , B. L. Voronov

We consider one dimensional Schr\"{o}dinger operators $H_\lambda=-\frac{d^2}{dx^2}+U+ \lambda V_\lambda$ with nonlinear dependence on the parameter $\lambda$ and study the small $\lambda$ behaviour of eigenvalues. The potentials $U$ and…

Spectral Theory · Mathematics 2021-12-14 Yuriy Golovaty

This text is a survey of recent results obtained by the author and collaborators on different problems for non-self-adjoint operators. The topics are: Kramers-Fokker-Planck type operators, spectral asymptotics in two dimensions and Weyl…

Spectral Theory · Mathematics 2008-04-24 Johannes Sjoestrand

This note aims to give prominence to some new results on the absence and localization of eigenvalues for the Dirac and Klein-Gordon operators, starting from known resolvent estimates already established in the literature combined with the…

Spectral Theory · Mathematics 2022-08-22 Piero D'Ancona , Luca Fanelli , David Krejcirik , Nico Michele Schiavone

We consider the eigenvalue problem $K x = \lambda x$. Our analysis focuses on the convergence rates of eigenvalue and spectral subspace approximations for compact linear integral operator $K$ with Green's kernels. By employing orthogonal…

Numerical Analysis · Mathematics 2026-02-19 Shashank K. Shukla , Gobinda Rakshit , Akshay S. Rane

We present a novel deep learning method for computing eigenvalues of the fractional Schr\"odinger operator. Our approach combines a newly developed loss function with an innovative neural network architecture that incorporates prior…

Numerical Analysis · Mathematics 2023-08-29 Yixiao Guo , Pingbing Ming

We consider non-selfadjoint operators of the kind arising in linearized NLS and prove dispersive bounds for the time-evolution without assuming that the edges of the essential spectrum are regular. Our approach does not depend on any…

Analysis of PDEs · Mathematics 2007-05-23 Mehmet Burak Erdogan , Wilhelm Schlag

The eigenvalues of a self-adjoint nxn matrix A can be put into a decreasing sequence $\lambda=(\lambda_1,...,\lambda_n)$, with repetitions according to multiplicity, and the diagonal of A is a point of $R^n$ that bears some relation to…

Operator Algebras · Mathematics 2007-05-23 William Arveson , Richard V. Kadison

Given an operator L acting on a function space, the J-matrix method consists of finding a sequence y_n of functions such that the operator L acts tridiagonally on y_n with respect to n. Once such a tridiagonalization is obtained, a number…

Classical Analysis and ODEs · Mathematics 2014-03-13 Mourad E. H. Ismail , Erik Koelink

We consider the question of whether the high-energy eigenfunctions of certain Schr\"odinger operators on the $d$-dimensional hyperbolic space of constant curvature $-\kappa^2$ are flexible enough to approximate an arbitrary solution of the…

Spectral Theory · Mathematics 2022-02-07 Alberto Enciso , Alba García-Ruiz , Daniel Peralta-Salas

Small-amplitude weakly coupled oscillators of the Klein-Gordon lattices are approximated by equations of the discrete nonlinear Schrodinger type. We show how to justify this approximation by two methods, which have been very popular in the…

Dynamical Systems · Mathematics 2016-09-21 D. Pelinovsky , T. Penati , S. Paleari

Closed operators in Hilbert space defined by a non-self-adjoint resolution of the identity $\{X(\lambda)\}_{\lambda\in {\mb R}}$, whose adjoints constitute also a resolution of the identity, are studied . In particular, it is shown that a…

Functional Analysis · Mathematics 2014-01-15 A. Inoue , C. Trapani

This paper proposes a tractable family of remainder-form mixed-monotone decomposition functions that are useful for over-approximating the image set of nonlinear mappings in reachability and estimation problems. Our approach applies to a…

Optimization and Control · Mathematics 2024-06-25 Mohammad Khajenejad , Sze Zheng Yong

Submodular function minimization is well studied, and existing algorithms solve it exactly or up to arbitrary accuracy. However, in many applications, such as structured sparse learning or batch Bayesian optimization, the objective function…

Machine Learning · Computer Science 2022-03-10 Marwa El Halabi , Stefanie Jegelka