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Revisionist integral deferred correction (RIDC) methods are a family of parallel--in--time methods to solve systems of initial values problems. The approach is able to bootstrap lower order time integrators to provide high order…

Mathematical Software · Computer Science 2017-01-09 Benjamin Ong , Ronald Haynes , Kyle Ladd

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

In this paper, we further develop a family of parallel time integrators known as Revisionist Integral Deferred Correction methods (RIDC) to allow for the semi-implicit solution of time dependent PDEs. Additionally, we show that our…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-20 Benjamin Ong , Andrew Melfi , Andrew Christlieb

Traditional step size controllers make the tacit assumption that the cost of a time step is independent of the step size. This is reasonable for explicit and implicit integrators that use direct solvers. In the context of exponential…

Numerical Analysis · Mathematics 2022-08-18 Pranab Jyoti Deka , Lukas Einkemmer

The automatic selection of an appropriate time step size has been considered extensively in the literature. However, most of the strategies developed operate under the assumption that the computational cost (per time step) is independent of…

Numerical Analysis · Mathematics 2018-08-14 Lukas Einkemmer

In this paper, we introduce a method for adapting the step-sizes of temporal difference (TD) learning. The performance of TD methods often depends on well chosen step-sizes, yet few algorithms have been developed for setting the step-size…

Machine Learning · Computer Science 2018-04-11 Alex Kearney , Vivek Veeriah , Jaden B. Travnik , Richard S. Sutton , Patrick M. Pilarski

Spectral deferred corrections (SDC) is an iterative approach for constructing higher- order accurate numerical approximations of ordinary differential equations. SDC starts with an initial approximation of the solution defined at a set of…

Computational Engineering, Finance, and Science · Computer Science 2017-06-14 R. W. Grout , H. Kolla , M. L. Minion , J. B. Bell

We implement an adaptive step size method for the Hybrid Monte Carlo a lgorithm. The adaptive step size is given by solving a symmetric error equation. An integr ator with such an adaptive step size is reversible. Although we observe…

High Energy Physics - Lattice · Physics 2009-10-28 Philippe de Forcrand , Tetsuya Takaishi

Matrix differential Riccati equation (DRE) typically exhibits transient and steady-state phases, posing challenges for fixed-step time integration methods, which may lack accuracy during transients or oversample in steady regimes. In this…

Numerical Analysis · Mathematics 2026-03-30 Jinyi Li , Dongping Li , Hua Yang

The computation time required by standard finite difference methods with fixed timesteps for solving fractional diffusion equations is usually very large because the number of operations required to find the solution scales as the square of…

Numerical Analysis · Mathematics 2024-06-28 Santos B. Yuste , Joaquin Quintana-Murillo

Integral deferred correction (IDC) methods have been shown to be an efficient way to achieve arbitrary high order accuracy and possess good stability properties. In this paper, we construct high order operator splitting schemes using the…

Numerical Analysis · Mathematics 2015-05-20 Andrew J. Christlieb , Yuan Liu , Zhengfu Xu

We investigate a local incremental stationary scheme for the numerical solution of rate-independent systems. Such systems are characterized by a (possibly) non-convex energy and a dissipation potential, which is positively homogeneous of…

Numerical Analysis · Mathematics 2022-04-13 Merlin Andreia , Christian Meyer

The Deferred Correction (DeC) is an iterative procedure, characterized by increasing accuracy at each iteration, which can be used to design numerical methods for systems of ODEs. The main advantage of such framework is the automatic way of…

Numerical Analysis · Mathematics 2023-11-09 Lorenzo Micalizzi , Davide Torlo

Spectral deferred correction (SDC) methods are an attractive approach to iteratively computing collocation solutions to an ODE by performing so-called sweeps with a low-order time stepping method. SDC allows to easily construct high order…

Numerical Analysis · Mathematics 2016-03-18 Robert Speck , Daniel Ruprecht , Michael Minion , Matthew Emmett , Rolf Krause

We consider a generic convex-concave saddle point problem with separable structure, a form that covers a wide-ranged machine learning applications. Under this problem structure, we follow the framework of primal-dual updates for saddle…

Machine Learning · Statistics 2015-06-15 Zhanxing Zhu , Amos J. Storkey

A posteriori error estimates based on residuals can be used for reliable error control of numerical methods. Here, we consider them in the context of ordinary differential equations and Runge-Kutta methods. In particular, we take the…

Numerical Analysis · Mathematics 2024-09-25 Hendrik Ranocha , Jan Giesselmann

The problem of designing adaptive stepsize sequences for the gradient descent method applied to convex and locally smooth functions is studied. We take an adaptive control perspective and design update rules for the stepsize that make use…

Optimization and Control · Mathematics 2025-08-27 Andrea Iannelli

Semi-Lagrangian schemes with various splitting methods, and with different reconstruction/interpolation strategies have been applied to kinetic simulations. For example, the order of spatial accuracy of the algorithms proposed in {[Qiu and…

Numerical Analysis · Mathematics 2015-06-17 Andrew Christlieb , Wei Guo , Maureen Morton , Jing-Mei Qiu

As supercomputers grow in hardware complexity, their susceptibility to faults increases and measures need to be taken to ensure the correctness of results. Some numerical algorithms have certain characteristics that allow them to recover…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-16 Thomas Saupe , Sebastian Götschel , Thibaut Lunet , Daniel Ruprecht , Robert Speck

This paper considers the robust phase retrieval, which can be cast as a nonsmooth and nonconvex composite optimization problem. We propose two first-order algorithms with adaptive step sizes: the subgradient algorithm (AdaSubGrad) and the…

Optimization and Control · Mathematics 2026-02-10 Zhong Zheng , Necdet Serhat Aybat , Shiqian Ma , Lingzhou Xue
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