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Motivated by the phase space analysis of Schr\"odinger evolution operators, in this paper we investigate how metaplectic operators are approximately diagonalized along the corresponding symplectic flows by exponentially localized Gabor wave…

Analysis of PDEs · Mathematics 2025-08-05 Elena Cordero , Gianluca Giacchi , Edoardo Pucci , Salvatore Ivan Trapasso

Investigating the performance of different methods is a fundamental problem in graph partitioning. In this paper, we estimate the so-called detectability threshold for the spectral method with both unnormalized and normalized Laplacians in…

Social and Information Networks · Computer Science 2015-06-10 Tatsuro Kawamoto , Yoshiyuki Kabashima

The paper deals with the distribution of eigenvalues of the compact fractal pseudodifferential operator $T^\mu_\tau$, \[ \big( T^\mu_\tau f\big)(x) = \int_{\mathbb{R}^n} e^{-ix\xi} \, \tau(x,\xi) \, \big( f\mu \big)^\vee (\xi) \, \mathrm{d}…

Functional Analysis · Mathematics 2024-05-28 Hans Triebel

A spectral theory of linear operators on a rigged Hilbert space is applied to Schr\"odinger operators with exponentially decaying potentials and dilation analytic potentials. The theory of rigged Hilbert spaces provides a unified approach…

Functional Analysis · Mathematics 2015-05-26 Hayato Chiba

The existing research on spectral algorithms, applied within a Reproducing Kernel Hilbert Space (RKHS), has primarily focused on general kernel functions, often neglecting the inherent structure of the input feature space. Our paper…

Machine Learning · Statistics 2024-03-08 Weichun Xia , Lei Shi

Covering ill-posed problems with compact and non-compact operators regarding the degree of ill-posedness is a never ending story written by many authors in the inverse problems literature. This paper tries to add a new narrative and some…

Numerical Analysis · Mathematics 2024-11-27 Frank Werner , Bernd Hofmann

The paper discusses a series of results concerning reproducing kernel Hilbert spaces, related to the factorization of their kernels. In particular, it is proved that for a large class of spaces isometric multipliers are trivial. One also…

Functional Analysis · Mathematics 2016-05-10 Rani Kumari , Jaydeb Sarkar , Srijan Sarkar , Dan Timotin

We study localization and derive stochastic estimates (in particular, Wegner and Minami estimates) for the eigenvalues of weakly correlated random discrete Schr\"odinger operators in the localized phase. We apply these results to obtain…

Mathematical Physics · Physics 2012-10-30 Frédéric Klopp

A unitarily invariant, complete Nevanlinna--Pick kernel $K$ on the unit ball determines a class of operators on Hilbert space called $K$-contractions. We study those $K$-contractions that are constrained, in the sense that they are…

Functional Analysis · Mathematics 2019-11-12 Raphaël Clouâtre , Edward J. Timko

Derivatives and integration operators are well-studied examples of linear operators that commute with scaling up to a fixed multiplicative factor; i.e., they are scale-invariant. Fractional order derivatives (integration operators) also…

Functional Analysis · Mathematics 2022-06-23 Arash Amini , Julien Fageot , Michael Unser

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 consider autocovariance operators of a stationary stochastic process on a Polish space that is embedded into a reproducing kernel Hilbert space. We investigate how empirical estimates of these operators converge along realizations of the…

Probability · Mathematics 2023-08-08 Mattes Mollenhauer , Stefan Klus , Christof Schütte , Péter Koltai

For time-frequency localization operators, related to the short-time Fourier transform, with symbol $R\Omega$, we work out the exact large $R$ eigenvalue behavior for rotationally invariant $\Omega$ and conjecture that the same relation…

Functional Analysis · Mathematics 2025-12-02 Simon Halvdansson

Traditional machine learning models, particularly neural networks, are rooted in finite-dimensional parameter spaces and nonlinear function approximations. This report explores an alternative formulation where learning tasks are expressed…

Machine Learning · Computer Science 2025-07-30 Andrew Kiruluta , Andreas Lemos , Priscilla Burity

We study location of eigenvalues of one-dimensional discrete Schr\"odinger operators with complex $\ell^{p}$-potentials for $1\leq p\leq \infty$. In the case of $\ell^{1}$-potentials, the derived bound is shown to be optimal. For $p>1$, two…

Spectral Theory · Mathematics 2019-10-28 Orif O. Ibrogimov , František Štampach

In this paper we study the concentration properties for the eigenvalues of kernel matrices, which are central objects in a wide range of kernel methods and, more recently, in network analysis. We present a set of concentration inequalities…

Machine Learning · Statistics 2020-10-27 Ernesto Araya Valdivia

Analyzing the structure of sampled features from an input data distribution is challenging when constrained by limited measurements in both the number of inputs and features. Traditional approaches often rely on the eigenvalue spectrum of…

Machine Learning · Computer Science 2025-02-11 Chanwoo Chun , SueYeon Chung , Daniel D. Lee

In this paper we study the small-$\lambda$ spectral asymptotics of an integral operator $\mathscr{K}$ defined on two multi-intervals $J$ and $E$, when the multi-intervals touch each other (but their interiors are disjoint). The operator…

Functional Analysis · Mathematics 2022-10-19 M. Bertola , E. Blackstone , A. Katsevich , A. Tovbis

We prove a characterization for the Peetre type $K$-functional on $\mathbb{M}$, a compact two-point homogeneous space, in terms the rate of approximation of a family of multipliers operator defined to this purpose. This extends the well…

Functional Analysis · Mathematics 2018-06-25 A. O. Carrijo , T. Jordão

The short-time Fourier transform (STFT) is a time-frequency representation widely used in applications, for example in audio signal processing. Recently it has been shown that not only the amplitude, but also the phase of this…

Functional Analysis · Mathematics 2015-11-20 Peter Balazs , Dominik Bayer , Florent Jaillet , Peter Søndergaard