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The double exponential formula was introduced for calculating definite integrals with singular point oscillation functions and Fourier integral. The double exponential transformation is not only useful for numerical computations but it is…

General Mathematics · Mathematics 2017-04-20 Arezoo Khatibi , Omid Khatibi

The optical interferometry has been widely used in various high precision applications. Usually, the minimum precision of an interferometry is limited by various technique noises in practice. To suppress such kind of noises, we propose a…

Optics · Physics 2018-06-20 Chen Fang , Jing-Zheng Huang , Guihua Zeng

We study an expansion method for high-dimensional parabolic PDEs which constructs accurate approximate solutions by decomposition into solutions to lower-dimensional PDEs, and which is particularly effective if there are a low number of…

Analysis of PDEs · Mathematics 2016-11-08 Christoph Reisinger , Rasmus Wissmann

We present a simple, PDE-based proof of the result [M. Johnson, 2001] that the error estimates of [J. Duchon, 1978] for thin plate spline interpolation can be improved by $h^{1/2}$. We illustrate that ${\mathcal H}$-matrix techniques can…

Numerical Analysis · Mathematics 2018-08-20 M. Loehndorf , J. M. Melenk

This paper presents high-order numerical methods for solving boundary value problems associated with the Lane-Emden equation, which frequently arises in astrophysics and various nonlinear models. A major challenge in studying this equation…

Numerical Analysis · Mathematics 2025-08-28 Dang Quang A , Nguyen Thanh Huong , Vu Vinh Quang

We present a numerical method for rigorous over-approximation of a reachable set of differential inclusions. The method gives high-order error bounds for single step approximations and a uniform bound on the error over the finite time…

Classical Analysis and ODEs · Mathematics 2012-06-29 Sanja Gonzalez Zivanovic , Pieter Collins

We prove a finiteness principle for interpolation of data by nonnegative Cm functions. Our result raises the hope that one can start to understand constrained interpolation problems in which e.g. the interpolating function F is required to…

Classical Analysis and ODEs · Mathematics 2016-03-09 Charles Fefferman , Arie Israel , Garving K. Luli

Radial basis functions (RBFs) are prominent examples for reproducing kernels with associated reproducing kernel Hilbert spaces (RKHSs). The convergence theory for the kernel-based interpolation in that space is well understood and optimal…

Classical Analysis and ODEs · Mathematics 2023-09-15 Thomas Hangelbroek , Christian Rieger

In this paper a general theory for interpolation methods on a rectangular grid is introduced. By the use of this theory an efficient B-spline based interpolation method for spectral codes is presented. The theory links the order of the…

Computational Physics · Physics 2012-01-20 M. A. T. van Hinsberg , J. H. M. ten Thije Boonkkamp , F. Toschi , H. J. H. Clercx

This paper deals with the solving of variational inequality problem where the constrained set is given as the intersection of a number of fixed-point sets. To this end, we present an extrapolated sequential constraint method. At each…

Optimization and Control · Mathematics 2020-06-30 Mootta Prangprakhon , Nimit Nimana

The main result in this paper is an error estimate for interpolation biharmonic polysplines in an annulus $A\left( r_{1},r_{N}\right) $, with respect to a partition by concentric annular domains $A\left( r_{1} ,r_{2}\right) ,$ ....,…

Numerical Analysis · Mathematics 2022-01-19 Ognyan Kounchev , Hermann Render , Tsvetomir Tsachev

A computer-assisted proof is proposed for the Laplacian eigenvalue minimization problems over triangular domains under diameter constraints. The proof utilizes recently developed guaranteed computation methods for both eigenvalues and…

Numerical Analysis · Mathematics 2022-09-30 Ryoki Endo , Xuefeng Liu

Based on a new Taylor-like formula, we derived an improved interpolation error estimate in $W^{1,p}$. We compare it with the classical error estimates based on the standard Taylor formula, and also with the corresponding interpolation error…

Numerical Analysis · Mathematics 2023-10-31 Joel Chaskalovic , Franck Assous

Interpolation models are critical for a wide range of applications, from numerical optimization to artificial intelligence. The reliability of the provided interpolated value is of utmost importance, and it is crucial to avoid the…

Numerical Analysis · Mathematics 2023-08-15 Daniele Peri

We describe methods for proving bounds on infinite-time averages in differential dynamical systems. The methods rely on the construction of nonnegative polynomials with certain properties, similarly to the way nonlinear stability can be…

Dynamical Systems · Mathematics 2021-06-25 David Goluskin

Consider the Poisson equation with the Dirichlet boundary condition on a three-dimensional polyhedral domain. For singular solutions from the non-smoothness of the domain boundary, we propose new anisotropic tetrahedral mesh refinement…

Numerical Analysis · Mathematics 2016-12-21 Hengguang Li

We study $W^{1,p}$ Lagrange interpolation error estimates for general quadrilateral $\mathcal{Q}_{k}$ finite elements with $k\ge 2$. For the most standard case of $p=2$ it turns out that the constant $C$ involved in the error estimate can…

Numerical Analysis · Mathematics 2015-07-07 Acosta Gabriel , Monzon Gabriel

This paper is devoted to the Lin-Ni conjecture for a semi-linear elliptic equation with a super-linear, sub-critical nonlinearity and homogeneous Neumann boundary conditions. We establish a new rigidity result, that is, we prove that the…

Analysis of PDEs · Mathematics 2016-07-04 Jean Dolbeault , Michal Kowalczyk

This work establishes the exact exponents for the soft-covering phenomenon of a memoryless channel under the total variation metric when random (i.i.d. and constant-composition) channel codes are used. The exponents, established herein, are…

Information Theory · Computer Science 2019-06-26 Semih Yagli , Paul Cuff

Many modern machine learning models are trained to achieve zero or near-zero training error in order to obtain near-optimal (but non-zero) test error. This phenomenon of strong generalization performance for "overfitted" / interpolated…

Machine Learning · Statistics 2018-10-29 Mikhail Belkin , Daniel Hsu , Partha Mitra