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In this article, we propose an implicit finite difference scheme for a two-dimensional parabolic stochastic partial differential equation (SPDE) of Zakai type. The scheme is based on a Milstein approximation to the stochastic integral and…

Numerical Analysis · Mathematics 2018-11-29 Christoph Reisinger , Zhenru Wang

The key difficulty to develop efficient high-order methods for integrating stochastic differential equations lies in the calculations of the multiple stochastic integrals. This letter suggests a scheme to compute the stochastic integrals…

Chemical Physics · Physics 2019-09-30 Shuanglin Sun , Yun-An Yan

Recent applications (e.g. active gels and self-assembly of elastic sheets) motivate the need to efficiently simulate the dynamics of thin elastic sheets. We present semi-implicit time stepping algorithms to improve the time step constraints…

Computational Physics · Physics 2019-10-23 Silas Alben , Alex A. Gorodetsky , Donghak Kim , Robert D. Deegan

We give an algorithm for efficient step size control in numerical integration of non-stiff initial value problems, based on a formula tailormade to methods where the numerical solution is compared with a solution of lower order.

Numerical Analysis · Mathematics 2025-10-20 Lars Petter Endresen

Many interfacial phenomena in physical and biological systems are dominated by high order geometric quantities such as curvature. Here a semi-implicit method is combined with a level set jet scheme to handle stiff nonlinear advection…

Numerical Analysis · Mathematics 2016-08-22 Guhan Velmurugan , Ebrahim M. Kolahdouz , David Salac

This paper develops validated computational methods for studying infinite dimensional stable manifolds at equilibrium solutions of parabolic PDEs, synthesizing disparate errors resulting from numerical approximation. To construct our…

Dynamical Systems · Mathematics 2021-07-08 Jan Bouwe van den Berg , Jonathan Jaquette , J. D. Mireles James

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

The multiplicative Newton-like method developed by the author et al. is extended to the situation where the dynamics is restricted to the orthogonal group. A general framework is constructed without specifying the cost function. Though the…

Machine Learning · Computer Science 2007-05-23 Toshinao Akuzawa

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

This paper presents a first-order convex splitting hybridizable/embedded discontinuous Galerkin method for the phase field crystal equation written in mixed form. Since the sixth-order phase field crystal equation is rewritten as a…

Numerical Analysis · Mathematics 2026-03-03 Giselle Saylor , Tamas L. Horvath , Natasha S. Sharma

A practical and efficient scheme for the higher order integration of the Landau-Lifschitz-Gilbert (LLG) equation is presented. The method is based on extrapolation of the two-step explicit midpoint rule and incorporates adaptive time step…

Computational Physics · Physics 2017-06-22 Lukas Exl , Norbert J. Mauser , Thomas Schrefl , Dieter Suess

We develop a stochastic algorithm for independent component analysis that incorporates multi-trial supervision, which is available in many scientific contexts. The method blends a proximal gradient-type algorithm in the space of invertible…

Machine Learning · Computer Science 2025-08-29 Ronak Mehta , Mateus Piovezan Otto , Noah Stanis , Azadeh Yazdan-Shahmorad , Zaid Harchaoui

It is well known that in the first-discretize-then-optimize approach in the control of ordinary differential equations the adjoint method may converge under additional order conditions only. For Peer two-step methods we derive such adjoint…

Numerical Analysis · Mathematics 2020-02-28 Jens Lang , Bernhard A. Schmitt

Algorithmic differentiation (AD) has become increasingly capable and straightforward to use. However, AD is inefficient when applied directly to solvers, a feature of most engineering analyses. We can leverage implicit differentiation to…

Optimization and Control · Mathematics 2023-06-28 Andrew Ning , Taylor McDonnell

In this paper we devise and analyze an unconditionally stable, second-order-in-time numerical scheme for the Cahn-Hilliard equation in two and three space dimensions. We prove that our two-step scheme is unconditionally energy stable and…

Numerical Analysis · Mathematics 2014-11-20 Amanda E. Diegel , Cheng Wang , Steven M. Wise

A sequential quadratic programming method is designed for solving general smooth nonlinear stochastic optimization problems subject to expectation equality constraints. We consider the setting where the objective and constraint function…

Optimization and Control · Mathematics 2026-03-17 Haoming Shen , Yang Zeng , Baoyu Zhou

Considered herein is a modified Newton method for the numerical solution of nonlinear equations where the Jacobian is approximated using a complex-step derivative approximation. We show that this method converges for sufficiently small…

Numerical Analysis · Mathematics 2024-10-03 Dimitrios Mitsotakis

In this paper, we construct efficient schemes based on the scalar auxiliary variable (SAV) block-centered finite difference method for the modified phase field crystal (MPFC) equation, which is a sixth-order nonlinear damped wave equation.…

Numerical Analysis · Mathematics 2020-04-10 Xiaoli Li , Jie Shen

This paper introduces alternating-direction implicit (ADI) solvers of higher order of time-accuracy (orders two to six) for the compressible Navier-Stokes equations in two- and three-dimensional curvilinear domains. The higher-order…

Computational Physics · Physics 2018-01-11 Oscar Bruno , Max Cubillos

We provide new gradient-based methods for efficiently solving a broad class of ill-conditioned optimization problems. We consider the problem of minimizing a function $f : \mathbb{R}^d \rightarrow \mathbb{R}$ which is implicitly…

Optimization and Control · Mathematics 2021-11-08 Jonathan Kelner , Annie Marsden , Vatsal Sharan , Aaron Sidford , Gregory Valiant , Honglin Yuan
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