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Finite difference schemes, using Backward Differentiation Formula (BDF), are studied for the approximation of one-dimensional diffusion equations with an obstacle term, of the form $$\min(v_t - a(t,x) v_{xx} + b(t,x) v_x + r(t,x) v, v-…

Numerical Analysis · Mathematics 2021-05-14 Olivier Bokanowski , Kristian Debrabant

The efficient and reliable approximation of convection-dominated problems continues to remain a challenging task. To overcome the difficulties associated with the discretization of convection-dominated equations, stabilization techniques…

Numerical Analysis · Mathematics 2022-12-15 Marius Paul Bruchhäuser , Kristina Schwegler , Markus Bause

In this work we study the stability regions of linear multistep or multiderivative multistep methods for initial-value problems by using techniques that are straightforward to implement in modern computer algebra systems. In many…

Numerical Analysis · Mathematics 2024-12-20 Lajos Lóczi

We study a second order BDF (Backward Differentiation Formula) scheme for the numerical approximation of parabolic HJB (Hamilton-Jacobi-Bellman) equations. The scheme under consideration is implicit, non-monotone, and second order accurate…

Numerical Analysis · Mathematics 2018-02-21 Olivier Bokanowski , Athena Picarelli , Christoph Reisinger

We introduce a new numerical method for the time-dependent Maxwell equations on unstructured meshes in two space dimensions. This relies on the introduction of a new mesh, which is the barycentric-dual cellular complex of the starting…

Computational Physics · Physics 2023-02-13 Bernard Kapidani , Lorenzo Codecasa , Joachim Schöberl

In order to be convergent, linear multistep methods must be zero stable. While constant step size theory was established in the 1950's, zero stability on nonuniform grids is less well understood. Here we investigate zero stability on…

Numerical Analysis · Mathematics 2022-04-21 Gustaf Söderlind , Imre Fekete , István Faragó

Spectral Deferred Correction (SDC) is an iterative method for the numerical solution of ordinary differential equations. It works by refining the numerical solution for an initial value problem by approximately solving differential…

Numerical Analysis · Mathematics 2025-09-09 Thomas Saupe , Sebastian Götschel , Thibaut Lunet , Daniel Ruprecht , Robert Speck

The stability and generalization of stochastic gradient-based methods provide valuable insights into understanding the algorithmic performance of machine learning models. As the main workhorse for deep learning, stochastic gradient descent…

Machine Learning · Statistics 2021-02-24 Tao Sun , Dongsheng Li , Bao Wang

Anomalous diffusion is often modelled in terms of the subdiffusion equation, which can involve a weakly singular source term. For this case, many predominant time stepping methods, including the correction of high-order BDF schemes [{\sc…

Numerical Analysis · Mathematics 2023-06-27 Jiankang Shi , Minghua Chen

The Feynman-Kac equation governs the distribution of the statistical observable -- functional, having wide applications in almost all disciplines. After overcoming challenges from the time-space coupled nonlocal operator and the possible…

Numerical Analysis · Mathematics 2020-11-11 Jing Sun , Daxin Nie , Weihua Deng

The Barzilai-Borwein (BB) step sizes have a profound impact on gradient descent methods. In this work, we propose two new gradient step sizes: one longer than the original long BB step size, and the other shorter than the original short BB…

Optimization and Control · Mathematics 2025-08-19 Xin Xu

In this paper, we propose and analyze an efficient implicit--explicit (IMEX) second order in time backward differentiation formulation (BDF2) scheme with variable time steps for gradient flow problems using the scalar auxiliary variable…

Numerical Analysis · Mathematics 2022-04-04 Dianming Hou , Zhonghua Qiao

In this paper, we innovatively develop uniform/variable-time-step weighted and shifted BDF2 (WSBDF2) methods for the anisotropic Cahn-Hilliard (CH) model, combining the scalar auxiliary variable (SAV) approach with two types of stabilized…

Numerical Analysis · Mathematics 2024-06-18 Meng Li , Jingjiang Bi , Nan Wang

We propose a quantitative direct method to prove the local stability of a stationary solution for a rough differential equation and its regular discretization scheme. Using Doss-Sussmann technique and stopping time analysis, we provide…

Dynamical Systems · Mathematics 2025-09-24 Luu Hoang Duc , Phan Thanh Hong , Nguyen Dinh Cong

For backward differentiation formulae (BDF) applied to gradient flows of semiconvex functions, quadratic stability implies the existence of a Lyapunov functional. We compute the maximum time step which can be derived from quadratic…

Dynamical Systems · Mathematics 2020-02-11 Morgan Pierre

We interpret a wide range of flavors of Spectral Deferred Corrections (SDC) as Runge-Kutta methods (RKM). Using Butcher series, we show that the considered class of SDC methods achieve at least order p after p iterations compared to the…

Numerical Analysis · Mathematics 2026-04-06 Eugen Bronasco , Joscha Fregin , Daniel Ruprecht , Gilles Vilmart

An implicit variable-step BDF2 scheme is established for solving the space fractional Cahn-Hilliard equation, involving the fractional Laplacian, derived from a gradient flow in the negative order Sobolev space $H^{-\alpha}$,…

Numerical Analysis · Mathematics 2023-06-26 Xuan Zhao , Zhongqin Xue

Recently, a new class of BDF schemes proposed in [F. Huang and J. Shen, SIAM J Numer. Anal., 62.4, 1609--1637] for the parabolic type equations are studied in this paper. The basic idea is based on the Taylor expansions at time…

Numerical Analysis · Mathematics 2025-07-10 Xiaoyi Li , Aijie Cheng , Zhengguang Liu

Spectral deferred corrections (SDC) are a class of iterative methods for the numerical solution of ordinary differential equations. SDC can be interpreted as a Picard iteration to solve a fully implicit collocation problem, preconditioned…

Numerical Analysis · Mathematics 2024-05-15 Ikrom Akramov , Sebastian Götschel , Michael Minion , Daniel Ruprecht , Robert Speck

The purpose of this work is to introduce a new idea of how to avoid the factorization of large matrices during the solution of stiff systems of ODEs. Starting from the general form of an explicit linear multistep method we suggest to…

Numerical Analysis · Mathematics 2019-08-22 Boris Faleichik