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Presented here is a matrix inversion method utilizing quantum searching algorithm. In this method, huge Hilbert space as a whole spanned by myriad of eigen states is searched and evaluated efficiently by sequential reduction in dimension…

Quantum Physics · Physics 2007-05-23 Atsushi Miyauchi

In this paper, we are interested in matrix valued orthogonal polynomials on the real line with respect to exponential weights. We obtain strong asymptotics as the degree tends to infinity in different regions of the complex plane, as well…

Classical Analysis and ODEs · Mathematics 2026-04-21 Alfredo Deaño , Pablo Román

We present an accelerated, or 'look-ahead' version of the Newton-Dinkelbach method, a well-known technique for solving fractional and parametric optimization problems. This acceleration halves the Bregman divergence between the current…

Data Structures and Algorithms · Computer Science 2021-05-24 Daniel Dadush , Zhuan Khye Koh , Bento Natura , László A. Végh

We propose a new method for preconditioning Kaczmarz method by sketching. Kaczmarz method is a stochastic method for solving overdetermined linear systems based on a sampling of matrix rows. The standard approach to speed up convergence of…

Numerical Analysis · Computer Science 2019-03-06 Alexandr Katrutsa , Ivan Oseledets

In this paper, we extend the method proposed by Cochelin and Vergez [A high order purely frequency-based harmonic balance formulation for continuation of periodic solutions, Journal of Sound and Vibration, 324 (2009) 243-262] to the case of…

Classical Physics · Physics 2012-11-29 Sami Karkar , Bruno Cochelin , Christophe Vergez

We study the problem of space and time efficient evaluation of a nonparametric estimator that approximates an unknown density. In the regime where consistent estimation is possible, we use a piecewise multivariate polynomial interpolation…

Statistics Theory · Mathematics 2020-11-11 Paxton Turner , Jingbo Liu , Philippe Rigollet

The Asymptotic Iteration Method (AIM) is a technique for solving analytically and approximately the linear second-order differential equation, especially the eigenvalue problems that frequently appear in theoretical and mathematical…

Mathematical Physics · Physics 2020-03-17 Mourad E. H. Ismail , Nasser Saad

This paper presents an iterative method suitable for inverting semilinear problems which are important kernels in many numerical applications. The primary idea is to employ a parametrization that is able to reduce semilinear problems into…

Numerical Analysis · Mathematics 2019-08-02 Prosper Torsu

We study an iterative Galerkin method for quasilinear elliptic problems in the Browder-Minty setting. The resulting discrete nonlinear systems are solved by linearization via a (damped) Zarantonello iteration. Unlike prior work, adaptive…

Numerical Analysis · Mathematics 2026-05-25 Maximilian Brunner , Gregor Gantner , Christoph Lietz , Dirk Praetorius

We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed…

Machine Learning · Computer Science 2015-10-28 Masahiro Yukawa

In this paper we investigate all-at-once versus reduced regularization of dynamic inverse problems on finite time intervals $(0,T)$. In doing so, we concentrate on iterative methods and nonlinear problems, since they have already been shown…

Numerical Analysis · Mathematics 2019-10-16 Barbara Kaltenbacher

In this letter, we present a fast and well-conditioned spectral method based on the Chebyshev polynomials for computing the continuous part of the nonlinear Fourier spectrum. The algorithm achieves a complexity of $O(N_{\text{iter.}}N\log…

Computational Physics · Physics 2019-09-10 Vishal Vaibhav

We revisit the classical polygonal line simplification problem and study it using the Hausdorff distance and Fr\'echet distance. Interestingly, no previous authors studied line simplification under these measures in its pure form, namely:…

Computational Geometry · Computer Science 2018-03-28 Marc van Kreveld , Maarten Löffler , Lionov Wiratma

The theory of orthogonal polynomials on the unit circle is developed for a general class of weights leading to systems of recurrence relations and derivatives of the polynomials and their associated functions, and to functional-difference…

Mathematical Physics · Physics 2007-05-23 P. J. Forrester , N. S. Witte

We obtain exact, simple and very compact expressions for the linearization coefficients of the products of orthogonal polynomials; both the conventional Clebsch-Gordan-type and the modified version. The expressions are general depending…

Classical Analysis and ODEs · Mathematics 2023-06-09 A. D. Alhaidari

We consider scalar semilinear elliptic PDEs where the nonlinearity is strongly monotone, but only locally Lipschitz continuous. We formulate an adaptive iterative linearized finite element method (AILFEM) which steers the local mesh…

Numerical Analysis · Mathematics 2023-05-24 Roland Becker , Maximilian Brunner , Michael Innerberger , Jens Markus Melenk , Dirk Praetorius

This paper introduces a new method for constructing approximate solutions to a class of Wiener--Hopf equations. This is particularly useful since exact solutions of this class of Wiener--Hopf equations, at the moment, cannot be obtained.…

Analysis of PDEs · Mathematics 2017-03-27 Anastasia V. Kisil

Suppose we have a Nikishin system of $p$ measures with the $k$th generating measure of the Nikishin system supported on an interval $\Delta_k\subset\er$ with $\Delta_k\cap\Delta_{k+1}=\emptyset$ for all $k$. It is well known that the…

Classical Analysis and ODEs · Mathematics 2023-08-30 Steven Delvaux , Abey López García , Guillermo López Lagomasino

Associated to a finite measure on the real line with finite moments are recurrence coefficients in a three-term formula for orthogonal polynomials with respect to this measure. These recurrence coefficients are frequently inputs to modern…

Numerical Analysis · Mathematics 2021-02-01 Zexin Liu , Akil Narayan

Stochastic iterative algorithms such as the Kaczmarz and Gauss-Seidel methods have gained recent attention because of their speed, simplicity, and the ability to approximately solve large-scale linear systems of equations without needing to…

Numerical Analysis · Mathematics 2019-01-10 Anna Ma , Deanna Needell , Aaditya Ramdas