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In this paper, we develop two fast implicit difference schemes for solving a class of variable-coefficient time-space fractional diffusion equations with integral fractional Laplacian (IFL). The proposed schemes utilize the graded $L1$…

Numerical Analysis · Mathematics 2021-07-26 Xian-Ming Gu , Hai-Wei Sun , Yanzhi Zhang , Yong-Liang Zhao

We develop and analyze a numerical method for stochastic time-fractional diffusion driven by additive fractionally integrated Gaussian noise. The model involves two nonlocal terms in time, i.e., a Caputo fractional derivative of order…

Numerical Analysis · Mathematics 2018-10-04 Bangti Jin , Yubin Yan , Zhi Zhou

We study the hybridizable discontinuous Galerkin (HDG) method for the spatial discretization of time fractional diffusion models with Caputo derivative of order $0<\alpha<1$. For each time $t \in [0,T]$, the HDG approximations are taken to…

Numerical Analysis · Mathematics 2014-12-08 Kassem Mustapha , Maher Nour , Bernardo Cockburn

We develop unified and easy to use framework to study robust fully discrete numerical methods for nonlinear degenerate diffusion equations $$ \partial_t u-\mathfrak{L}[\varphi(u)]=f(x,t) \qquad\text{in}\qquad \mathbb{R}^N\times(0,T), $$…

Numerical Analysis · Mathematics 2018-10-17 Félix del Teso , Jørgen Endal , Espen R. Jakobsen

Stability and convergence of a time-weighted discrete scheme with nonuniform time steps are established for linear reaction-subdiffusion equations. The Caupto derivative is approximated at an offset point by using linear and quadratic…

Numerical Analysis · Mathematics 2022-01-05 Hong-lin Liao , William McLean , Jiwei Zhang

In this paper, we consider Maxwell's equations in linear dispersive media described by a single-pole Lorentz model for electronic polarization. We study two classes of commonly used spatial discretizations: finite difference methods (FD)…

Numerical Analysis · Mathematics 2019-06-26 Yan Jiang , Puttha Sakkaplangkul , Vrushali A. Bokil , Yingda Cheng , Fengyan Li

We review, implement, and compare numerical integration schemes for spatially bounded diffusions stopped at the boundary which possess a convergence rate of the discretization error with respect to the timestep $h$ higher than ${\cal…

Numerical Analysis · Mathematics 2016-09-21 Francisco Bernal , Juan A. Acebrón

In this article, we have studied the convergence behavior of the Dirichlet-Neumann and Neumann- Neumann waveform relaxation algorithms for time-fractional sub-diffusion and diffusion-wave equations in 1D & 2D for regular domains, where the…

Numerical Analysis · Mathematics 2022-12-26 Soura Sana , Bankim C. Mandal

The diffusion approximation of stochastic gradient descent (SGD) in current literature is only valid on a finite time interval. In this paper, we establish the uniform-in-time diffusion approximation of SGD, by only assuming that the…

Machine Learning · Statistics 2022-07-12 Lei Li , Yuliang Wang

We provide a preliminary comparison of the dispersion properties, specifically the time-amplification factor, the scaled group velocity and the error in the phase speed of four spatiotemporal discretization schemes utilized for solving the…

Numerical Analysis · Mathematics 2019-12-23 S. Singh , S. Sircar

A semidiscrete Galerkin finite element method applied to time-fractional diffusion equations with time-space dependent diffusivity on bounded convex spatial domains will be studied. The main focus is on achieving optimal error results with…

Numerical Analysis · Mathematics 2020-06-12 Kassem Mustapha

This paper provides a finite difference discretization for the backward Feynman-Kac equation, governing the distribution of functionals of the path for a particle undergoing both reaction and diffusion [Hou and Deng, J. Phys. A: Math.…

Numerical Analysis · Mathematics 2019-11-01 Daxin Nie , Jing Sun , Weihua Deng

Continuous-time random walks are generalisations of random walks frequently used to account for the consistent observations that many molecules in living cells undergo anomalous diffusion, i.e. subdiffusion. Here, we describe the…

Analysis of PDEs · Mathematics 2015-03-31 Hugues Berry , Thomas Lepoutre , Álvaro Mateos González

The numerical solution of a nonlinear and space-fractional anti-diffusive equation used to model dune morphodynamics is considered. Spatial discretization is effected using a finite element method whereas the Crank-Nicolson scheme is used…

Numerical Analysis · Mathematics 2016-09-01 Afaf Bouharguane

Several recent works have explored stochastic gradient methods for variational inference that exploit the geometry of the variational-parameter space. However, the theoretical properties of these methods are not well-understood and these…

Machine Learning · Statistics 2016-08-15 Mohammad Emtiyaz Khan , Reza Babanezhad , Wu Lin , Mark Schmidt , Masashi Sugiyama

We study solution techniques for parabolic equations with fractional diffusion and Caputo fractional time derivative, the latter being discretized and analyzed in a general Hilbert space setting. The spatial fractional diffusion is realized…

Numerical Analysis · Mathematics 2015-03-05 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

We present a numerical method for convergence acceleration for multifidelity models of parameterized ordinary differential equations. The hierarchy of models is defined as trajectories computed using different timesteps in a time…

Numerical Analysis · Mathematics 2018-08-13 Vahid Keshavarzzadeh , Robert M. Kirby , Akil Narayan

Two numerical methods with graded temporal grids are analyzed for fractional evolution equations. One is a low-order discontinuous Galerkin (DG) discretization in the case of fractional order $0<\alpha<1$, and the other one is a low-order…

Numerical Analysis · Mathematics 2020-03-09 Binjie Li , Tao Wang , Xiaoping Xie

We present a class of new explicit and stable numerical algorithms to solve the spatially discretized linear heat or diffusion equation. After discretizing the space and the time variables like conventional finite difference methods, we do…

Numerical Analysis · Mathematics 2021-04-27 Endre Kovács

Discrete flow models offer a powerful framework for learning distributions over discrete state spaces and have demonstrated superior performance compared to the discrete diffusion models. However, their convergence properties and error…

Statistics Theory · Mathematics 2026-05-27 Zhengyan Wan , Yidong Ouyang , Qiang Yao , Liyan Xie , Fang Fang , Hongyuan Zha , Guang Cheng