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Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially…

Numerical Analysis · Mathematics 2018-03-08 K. Mustapha , K. Furati , O. M. Knio , O. Le Maitre

We propose a novel and simple spectral method based on the semi-discrete Fourier transforms to discretize the fractional Laplacian $(-\Delta)^\frac{\alpha}{2}$. Numerical analysis and experiments are provided to study its performance. Our…

Numerical Analysis · Mathematics 2024-06-18 Shiping Zhou , Yanzhi Zhang

An efficient numerical method to compute solitary wave solutions to the free surface Euler equations is reported. It is based on the conformal mapping technique combined with an efficient Fourier pseudo-spectral method. The resulting…

Fluid Dynamics · Physics 2020-02-20 Denys Dutykh , Didier Clamond

Usual modal analysis techniques are based on the Fourier transform. Due to the Delta T . Delta f limitation, they perform poorly when the modal overlap mu exceeds 30%. A technique based on a high-resolution analysis algorithm and an…

Data Analysis, Statistics and Probability · Physics 2013-11-04 Kerem Ege , Xavier Boutillon , Bertrand David

Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders their practical applications. While recent efforts have…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jiaqi Xu , Wenbo Li , Haoze Sun , Fan Li , Zhixin Wang , Long Peng , Jingjing Ren , Haoran Yang , Xiaowei Hu , Renjing Pei , Pheng-Ann Heng

We study the Euler equations describing the motion of an incompressible fluid on the cubic torus with real initial data. We construct solutions on the Fourier side which display a sudden loss of regularity within finite time even for highly…

Analysis of PDEs · Mathematics 2024-03-18 Henrik Ueberschaer

The article is devoted to the construction of explicit one-step numerical methods with the strong orders of convergence 2.0, 2,5, and 3.0 for Ito stochastic differential equations with multidimensional non-commutative noise. We consider the…

Probability · Mathematics 2022-08-18 Dmitriy F. Kuznetsov

The ultraspherical spectral method features high accuracy and fast solution. In this article, we determine the sources of error arising from the ultraspherical spectral method and derive its effective condition number, which explains why…

Numerical Analysis · Mathematics 2024-05-21 Lu Cheng , Kuan Xu

In this work we investigate the statistical mechanics of a family of two dimensional (2D) fluid flows, described by the generalized Euler equations, or $\alpha$-models. These models describe both nonlocal and local dynamics, with one…

Fluid Dynamics · Physics 2020-01-29 Giovanni Conti , Gualtiero Badin

The classical development of neural networks has primarily focused on learning mappings between finite-dimensional Euclidean spaces. Recently, this has been generalized to neural operators that learn mappings between function spaces. For…

Pseudospectral time domain (PSTD) methods are widely used in many branches of acoustics for the numerical solution of the wave equation, including biomedical ultrasound and seismology. The use of the Fourier collocation spectral method in…

Computational Physics · Physics 2020-12-03 E. S. Wise , J. Jaros , B. T. Cox , B. E. Treeby

We formulate a smoothed-particle hydrodynamics numerical method, traditionally used for the Euler equations for fluid dynamics in the context of astrophysical simulations, to solve the non-linear Schrodinger equation in the Madelung…

Computational Physics · Physics 2016-11-09 Philip Mocz , Sauro Succi

This paper proposes a squared smoothing Newton method via the Huber smoothing function for solving semidefinite programming problems (SDPs). We first study the fundamental properties of the matrix-valued mapping defined upon the Huber…

Optimization and Control · Mathematics 2024-10-10 Ling Liang , Defeng Sun , Kim-Chuan Toh

A collection of algorithms is described for numerically computing with smooth functions defined on the unit sphere. Functions are approximated to essentially machine precision by using a structure-preserving iterative variant of Gaussian…

Numerical Analysis · Mathematics 2016-04-05 Alex Townsend , Heather Wilber , Grady B. Wright

This paper presents a Fourier integral pseudospectral (FIPS) method for a general class of nonlinear, periodic optimal control (OC) problems with equality and/or inequality constraints and sufficiently smooth solutions. In this scheme, the…

Optimization and Control · Mathematics 2023-11-14 Kareem T. Elgindy

A spectral method is considered for approximating the fractional Laplacian and solving the fractional Poisson problem in 2D and 3D unit balls. The method is based on the explicit formulation of the eigenfunctions and eigenvalues of the…

Numerical Analysis · Mathematics 2018-12-21 Kailai Xu , Eric Darve

In this paper we study strong approximation of the solution of a scalar stochastic differential equation (SDE) at the final time in the case when the drift coefficient may have discontinuities in space. Recently it has been shown in…

Probability · Mathematics 2019-04-22 Thomas Müller-Gronbach , Larisa Yaroslavtseva

Quasi-periodic trajectories with two or more incommensurate frequencies are ubiquitous in nonlinear dynamics, yet the classical Fourier-based time-spectral method is tied to strictly periodic responses. We introduce a torus time-spectral…

Numerical Analysis · Mathematics 2025-12-16 Sicheng He , Hang Li , Kivanc Ekici

The simulation of fluid flow problems, specifically incompressible flows governed by the Navier-Stokes equations (NSE), holds fundamental significance in a range of scientific and engineering applications. Traditional numerical methods…

Computational Physics · Physics 2024-09-10 Abdullah Abukhwejah , Pankaj Jagad , Ravi Samtaney , Peter Schmid

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