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We solve the Cauchy problem of the Ward model in light-cone coordinates using the inverse spectral (scattering) method. In particular we show that the solution can be constructed by solving a $2\times 2$ local matrix Riemann-Hilbert problem…

High Energy Physics - Theory · Physics 2007-05-23 A. S. Fokas , T. A. Ioannidou

Defect detection by ultrasonic method is limited by the pulse width. Resolution can be improved through a deconvolution process with a priori information of the pulse or by its estimation. In this paper a regularization of the Wiener filter…

Information Theory · Computer Science 2012-05-17 Roberto H. Herrera , Eduardo Moreno , Héctor Calas , Rubén Orozco

With the example of the spherically symmetric scalar wave equation on Minkowski space-time we demonstrate that a fully pseudospectral scheme (i.e. spectral with respect to both spatial and time directions) can be applied for solving…

General Relativity and Quantum Cosmology · Physics 2010-11-05 Jörg Hennig , Marcus Ansorg

This paper is concerned with solution in H\"{o}lder spaces of the Cauchy problem for linear and semi-linear backward stochastic partial differential equations (BSPDEs) of super-parabolic type. The pair of unknown variables are viewed as…

Analysis of PDEs · Mathematics 2016-02-10 Shanjian Tang , Wenning Wei

This research presents a comprehensive assessment of pan-sharpening techniques for satellite imagery, focusing on the critical aspects of spectral fidelity and spatial enhancement. Motivated by the need for informed algorithm selection in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Abdul Aziz A. B , A. B Abdul Rahim

Spatial confounding is a fundamental issue in spatial regression models which arises because spatial random effects, included to approximate unmeasured spatial variation, are typically not independent of covariates in the model. This can…

Methodology · Statistics 2025-07-15 Emiko Dupont , Isa Marques , Thomas Kneib

We demonstrate that accurate computation of the spectral proper orthogonal decomposition (SPOD) critically depends on the choice of frequency resolution. Using both artificially generated data and large-eddy simulation data of a turbulent…

Fluid Dynamics · Physics 2024-02-27 Liam Heidt , Tim Colonius

The spectral/hp element method combines the geometric flexibility of the classical h-type finite element technique with the desirable numerical properties of spectral methods, employing high-degree piecewise polynomial basis functions on…

We consider nearest neighbor spacing distributions of composite ensembles of levels. These are obtained by combining independently unfolded sequences of levels containing only few levels each. Two problems arise in the spectral analysis of…

Data Analysis, Statistics and Probability · Physics 2009-11-07 A. Y. Abul-Magd , H. L. Harney , M. H. Simbel , H. A. Weidenmueller

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

This proceeding is intended to be a first introduction to spectral methods. It is written around some simple problems that are solved explicitly and in details and that aim at demonstrating the power of those methods. The mathematical…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Philippe Grandclement

Consider a singularly perturbed system $$\epsilon u_t=\epsilon^2 u_{xx} + f(u,x,\epsilon),\quad u\in {\Bbb R}^n,x\in{\Bbb R},t\geq 0. $$ Assume that the system has a sequence of regular and internal layers occurring alternatively along the…

patt-sol · Physics 2008-02-03 Xiao-Biao Lin

No imaging apparatus can produce perfect images: spatial resolution is limited by the Rayleigh diffraction bound that is a consequence of the imager's finite spatial extent. We show some N-photon strategies that permit resolution of details…

Quantum Physics · Physics 2009-02-25 Vittorio Giovannetti , Seth Lloyd , Lorenzo Maccone , Jeffrey H. Shapiro

Permutation synchronization is an important problem in computer science that constitutes the key step of many computer vision tasks. The goal is to recover $n$ latent permutations from their noisy and incomplete pairwise measurements. In…

Statistics Theory · Mathematics 2024-05-13 Duc Nguyen , Anderson Ye Zhang

Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine a…

Computational Engineering, Finance, and Science · Computer Science 2016-11-18 Zheng Zhang , Tarek A. El-Moselhy , Ibrahim , M. Elfadel , Luca Daniel

The Fast Diffusion Equation (FDE) $u_t= \Delta u^m$, with $m\in (0,1)$, is an important model for singular nonlinear (density dependent) diffusive phenomena. Here, we focus on the Cauchy-Dirichlet problem posed on smooth bounded Euclidean…

Analysis of PDEs · Mathematics 2023-08-17 Matteo Bonforte , Alessio Figalli

Fast decoders that achieve strong error suppression are essential for fault-tolerant quantum computation (FTQC) from both practical and theoretical perspectives. The union-find (UF) decoder for the surface code is widely regarded as a…

Quantum Physics · Physics 2026-05-07 Satoshi Yoshida , Ethan Lake , Hayata Yamasaki

We study the Cauchy problem for the quasi-geostrophic equations in a unit ball of the two dimensional space with the homogeneous Dirichlet boundary condition. We show the existence, the uniqueness of the strong solution in the framework of…

Analysis of PDEs · Mathematics 2021-09-17 Tsukasa Iwabuchi

As commonly understood, the noise spectroscopy problem---characterizing the statistical properties of a noise process affecting a quantum system by measuring its response---is ill-posed. Ad-hoc solutions assume implicit structure which is…

Convergence rates in spectral regularization methods quantify the approximation error in inverse problems as a function of the noise level or the number of sampling points. Classical strong convergence rate results typically rely on source…

Numerical Analysis · Mathematics 2025-12-05 Sabrina Guastavino , Gabriele Santin , Francesco Marchetti , Federico Benvenuto