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A solver for the Poisson equation for 1D, 2D and 3D regular grids is presented. The solver applies the convolution theorem in order to efficiently solve the Poisson equation in spectral space over a rectangular computational domain.…

Mathematical Software · Computer Science 2023-01-04 Joseph Saverin

There is currently a gap in theory for point patterns that lie on the surface of objects, with researchers focusing on patterns that lie in a Euclidean space, typically planar and spatial data. Methodology for planar and spatial data thus…

Statistics Theory · Mathematics 2020-02-11 Scott Ward , Edward A. K. Cohen , Niall Adams

We have developed in the past several algorithms with intrinsic complexity bounds for the problem of point finding in real algebraic varieties. Our aim here is to give a comprehensive presentation of the geometrical tools which are…

Algebraic Geometry · Mathematics 2009-11-23 B. Bank , M. Giusti , J. Heintz , M. Safey El Din , E. Schost

In some applications, one is interested in reconstructing a function $f$ from its Fourier series coefficients. The problem is that the Fourier series is slowly convergent if the function is non-periodic, or is non-smooth. In this paper, we…

Numerical Analysis · Mathematics 2020-04-14 David Levin

Gaussian process modulated Poisson processes provide a flexible framework for modelling spatiotemporal point patterns. So far this had been restricted to one dimension, binning to a pre-determined grid, or small data sets of up to a few…

Machine Learning · Statistics 2018-04-04 S. T. John , James Hensman

This paper presents an efficient approach to image segmentation that approximates the piecewise-smooth (PS) functional in [12] with explicit solutions. By rendering some rational constraints on the initial conditions and the final solutions…

Computer Vision and Pattern Recognition · Computer Science 2016-12-09 Huihui Song , Yuhui Zheng , Kaihua Zhang

This article proposes a new discrete framework for approximating solutions to shape optimization problems under convexity constraints. The numerical method, based on the support function or the gauge function, is guaranteed to generate…

Optimization and Control · Mathematics 2022-03-15 Beniamin Bogosel

This paper describes an efficient algorithm for computing steady two-dimensional surface gravity wave in irrotational motion. The algorithm complexity is O(N log N), N being the number of Fourier modes. The algorithm allows the arbitrary…

Classical Physics · Physics 2020-02-20 Didier Clamond , Denys Dutykh

We consider the problem of numerically integrating functions with hyperplane discontinuities over the entire Euclidean space in many dimensions. We describe a simple process through which the Euclidean space is partitioned into simplices on…

Numerical Analysis · Mathematics 2014-06-06 Vassilis Pandis

Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sample locations. Spectral methods address this challenge by exploiting the Fourier representation,…

Machine Learning · Statistics 2026-02-27 Arsalan Jawaid , Abdullah Karatas , Jörg Seewig

A convolution of the all-sky survey data with a smoothing function is crucial in calculating the smooth surface brightness of the sky survey data. The convolution is usually performed using a spherical version of the convolution theorem.…

Astrophysics · Physics 2007-05-23 Kwang-Il Seon

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale…

Numerical Analysis · Mathematics 2024-04-17 Miranda Boutilier , Konstantin Brenner , Victorita Dolean

We extend the Theory of Computation on real numbers, continuous real functions, and bounded closed Euclidean subsets, to compact metric spaces $(X,d)$: thereby generically including computational and optimization problems over higher types,…

Logic in Computer Science · Computer Science 2017-03-28 Chansu Park , Ji-Won Park , Sewon Park , Dongseong Seon , Martin Ziegler

The two-dimensional Helmholtz equation separates in elliptic coordinates based on two distinct foci, a limit case of which includes polar coordinate systems when the two foci coalesce. This equation is invariant under the Euclidean group of…

Mathematical Physics · Physics 2026-04-30 Kenan Uriostegui , Kurt Bernardo Wolf

In many applications data are measured or defined on a spherical manifold; spherical harmonic transforms are then required to access the frequency content of the data. We derive algorithms to perform forward and inverse spin spherical…

Astrophysics · Physics 2011-10-28 J. D. McEwen

This paper develops a correspondence relating convex hulls of fractional functions with those of polynomial functions over the same domain. Using this result, we develop a number of new reformulations and relaxations for fractional…

Optimization and Control · Mathematics 2024-06-18 Taotao He , Siyue Liu , Mohit Tawarmalani

This paper introduces an efficient algorithm for computing the general oscillatory matrix functions. These computations are crucial for solving second-order semi-linear initial value problems. The method is exploited using the scaling and…

Numerical Analysis · Mathematics 2024-06-11 Dongping Li , Xue Wang , Xiuying Zhang

The partition function and the one- and two-body distribution functions are evaluated for two hard spheres with different sizes constrained into a spherical pore. The equivalent problem for hard disks is addressed too. We establish a…

Statistical Mechanics · Physics 2010-05-07 Ignacio Urrutia

We propose a Fourier-based approach for optimization of several clustering algorithms. Mathematically, clusters data can be described by a density function represented by the Dirac mixture distribution. The density function can be smoothed…

Machine Learning · Computer Science 2019-09-24 Soheil Mehrabkhani