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Related papers: Spectral Methods for Numerical Relativity. The Ini…

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Numerical Relativity is a mature field with many applications in Astrophysics, Cosmology and even in Fundamental Physics. As such, we are entering a stage in which new sophisticated methods adapted to open problems are being developed. In…

Computational Physics · Physics 2020-02-27 Daniel Santos-Oliván , Carlos F. Sopuerta

Equations arising in General Relativity are usually too complicated to be solved analytically and one has to rely on numerical methods to solve sets of coupled partial differential equations. Among the possible choices, this paper focuses…

General Relativity and Quantum Cosmology · Physics 2016-06-22 Philippe Grandclement , Jérôme Novak

Current methods of evolving a spacetime containing one or more black holes are plagued by instabilities that prohibit long-term evolution. Some of these instabilities may be due to the numerical method used, traditionally finite…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Lawrence E. Kidder , Mark A. Scheel , Saul A. Teukolsky , Eric D. Carlson , Gregory B. Cook

We introduce a novel spectral, finite-dimensional approximation of general Sobolev spaces in terms of Chebyshev polynomials. Based on this polynomial surrogate model (PSM), we realise a variational formulation, solving a vast class of…

Numerical Analysis · Mathematics 2023-01-13 Juan-Esteban Suarez Cardona , Phil-Alexander Hofmann , Michael Hecht

Multivariate global polynomial approximations - such as polynomial chaos or stochastic collocation methods - are now in widespread use for sensitivity analysis and uncertainty quantification. The pseudospectral variety of these methods uses…

Numerical Analysis · Mathematics 2013-04-09 Paul G. Constantine , Michael S. Eldred , Eric T. Phipps

Spectral clustering is a popular method for effectively clustering nonlinearly separable data. However, computational limitations, memory requirements, and the inability to perform incremental learning challenge its widespread application.…

Machine Learning · Computer Science 2023-11-15 Jo-Chun Chen , Hung-Hsuan Chen

In this paper, we introduce a numerical solution of a stochastic partial differential equation (SPDE) of elliptic type using polynomial chaos along side with polynomial approximation at Sinc points. These Sinc points are defined by a…

Numerical Analysis · Mathematics 2019-04-08 Maha Youssef , Roland Pulch

Partial Set Cover (PSC) is a generalization of the well-studied Set Cover problem (SC). In PSC the input consists of an integer $k$ and a set system $(U,S)$ where $U$ is a finite set, and $S \subseteq 2^U$ is a collection of subsets of $U$.…

Data Structures and Algorithms · Computer Science 2019-07-11 Chandra Chekuri , Kent Quanrud , Zhao Zhang

In several application domains, high-dimensional observations are collected and then analysed in search for naturally occurring data clusters which might provide further insights about the nature of the problem. In this paper we describe a…

Machine Learning · Statistics 2012-03-07 Brian McWilliams , Giovanni Montana

This article begins with a brief introduction to numerical relativity aimed at readers who have a background in applied mathematics but not necessarily in general relativity. I then introduce and summarise my work on the problem of treating…

General Relativity and Quantum Cosmology · Physics 2014-07-29 Oliver Rinne

We discuss a numerical scheme to solve the continuum Kardar-Parisi-Zhang equation in generic spatial dimensions. It is based on a momentum-space discretization of the continuum equation and on a pseudo-spectral approximation of the…

Statistical Mechanics · Physics 2009-11-07 Lorenzo Giada , Achille Giacometti , Maurice Rossi

This work proposes and analyzes a generalized acceleration technique for decreasing the computational complexity of using stochastic collocation (SC) methods to solve partial differential equations (PDEs) with random input data. The SC…

Numerical Analysis · Mathematics 2015-05-05 Diego Galindo , Peter Jantsch , Clayton G. Webster , Guannan Zhang

The recent development of spectral method has been praised for its high-order convergence in simulating complex physical problems. The combination of embedded boundary method and spectral method becomes a mainstream way to tackle…

Numerical Analysis · Mathematics 2018-03-08 Po-Yi Wu , Cheng-Hong Robert Kao , Tony Wen-Hann Sheu

Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as…

Numerical Analysis · Mathematics 2013-06-05 Maziar Raissi , Padmanabhan Seshaiyer

In the last few years, large improvements in image clustering have been driven by the recent advances in deep learning. However, due to the architectural complexity of deep neural networks, there is no mathematical theory that explains the…

Computer Vision and Pattern Recognition · Computer Science 2021-08-30 Angel Villar-Corrales , Veniamin I. Morgenshtern

We prove convergence of the spectral element method for piecewise polynomial collocation applied to periodic boundary value problems for functional differential equations. In particular, we prove that the numerical collocation solution…

Numerical Analysis · Mathematics 2025-10-27 Alessia andò , Jan Sieber

Pseudospectral collocation methods and finite difference methods have been used for approximating an important family of soliton like solutions of the mKdV equation. These solutions present a structural instability which make difficult to…

Numerical Analysis · Mathematics 2011-09-29 Carlos Gorria , Miguel A. Alejo , Luis Vega

Elliptic partial differential equations must be solved numerically for many problems in numerical relativity, such as initial data for every simulation of merging black holes and neutron stars. Existing elliptic solvers can take multiple…

We present a new solver for coupled nonlinear elliptic partial differential equations (PDEs). The solver is based on pseudo-spectral collocation with domain decomposition and can handle one- to three-dimensional problems. It has three…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Harald P. Pfeiffer , Lawrence E. Kidder , Mark A. Scheel , Saul A. Teukolsky

A space-time collocation method (STCM) using asymptotically-constant basis functions is proposed and applied to the quantum Hamiltonian constraint for a loop-quantized treatment of the Schwarzschild interior. Canonically, these descriptions…

Computational Physics · Physics 2020-12-02 Alec Yonika , Alfa Heryudono , Gaurav Khanna
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