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In this paper we consider discrete gradient methods for approximating the solution and preserving a first integral (also called a constant of motion) of autonomous ordinary differential equations. We prove under mild conditions for a large…

Numerical Analysis · Mathematics 2013-01-22 Richard A. Norton , G. R. W. Quispel

We introduce a class of first-order methods for smooth constrained optimization that are based on an analogy to non-smooth dynamical systems. Two distinctive features of our approach are that (i) projections or optimizations over the entire…

Optimization and Control · Mathematics 2025-04-15 Michael Muehlebach , Michael I. Jordan

Approximation theory for Lyapunov and Sacker-Sell spectra based upon QR techniques is used to analyze the stability of a one-step method solving a time-dependent, linear, ordinary differential equation (ODE) initial value problem in terms…

Numerical Analysis · Mathematics 2017-09-08 Andrew J. Steyer , Erik S. Van Vleck

We introduce an arbitrary order, stabilized finite element method for solving a unique continuation problem subject to the time-harmonic elastic wave equation with variable coefficients. Based on conditional stability estimates we prove…

Numerical Analysis · Mathematics 2023-04-25 Erik Burman , Janosch Preuss

A time discretization method is called strongly stable, if the norm of its numerical solution is nonincreasing. It is known that, even for linear semi-negative problems, many explicit Runge--Kutta (RK) methods fail to preserve this…

Numerical Analysis · Mathematics 2019-12-30 Zheng Sun , Chi-Wang Shu

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

Problems that feature significantly different time scales, where the stiff time-step restriction comes from a linear component, implicit-explicit (IMEX) methods alleviate this restriction if the concern is linear stability. However, where…

Numerical Analysis · Mathematics 2019-04-16 Leah Isherwood , Zachary J. Grant , Sigal Gottlieb

The article is devoted to the construction of explicit one-step strong numerical methods with the orders 2.0 and 2.5 of convergence for Ito stochastic differential equations with multidimensional non-commutative noise. We consider the…

Probability · Mathematics 2022-09-13 Dmitriy F. Kuznetsov

In this paper we investigate the stability properties of the so-called gBBKS and GeCo methods, which belong to the class of nonstandard schemes and preserve the positivity as well as all linear invariants of the underlying system of…

Numerical Analysis · Mathematics 2023-04-04 Thomas Izgin , Stefan Kopecz , Angela Martiradonna , Andreas Meister

We investigate a high-order, fully explicit, asymptotic-preserving scheme for a kinetic equation with linear relaxation, both in the hydrodynamic and diffusive scalings in which a hyperbolic, resp. parabolic, limiting equation exists. The…

Numerical Analysis · Mathematics 2014-05-21 Pauline Lafitte , Annelies Lejon , Giovanni Samaey

We present fifth order Runge-Kutta-Nystr\"om methods, where we allow the timestep coefficients to assume complex values. Among the methods with complex timesteps, we focus on the ones with the coefficients that have positive real parts.…

Numerical Analysis · Mathematics 2012-03-16 M. Atakan Gürkan

We present a methodology to construct efficient high-order in time accurate numerical schemes for a class of gradient flows with appropriate Lipschitz continuous nonlinearity. There are several ingredients to the strategy: the exponential…

Numerical Analysis · Mathematics 2021-02-23 Wenbin Chen , Shufen Wang , Xiaoming Wang

We consider split-step Milstein methods for the solution of stiff stochastic differential equations with an emphasis on systems driven by multi-channel noise. We show their strong order of convergence and investigate mean-square stability…

Numerical Analysis · Mathematics 2014-11-27 V. Reshniak , A. Q. M. Khaliq , D. A. Voss , G. Zhang

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig

A scheme for stabilizing stochastic approximation iterates by adaptively scaling the step sizes is proposed and analyzed. This scheme leads to the same limiting differential equation as the original scheme and therefore has the same…

Probability · Mathematics 2010-07-28 Sameer Kamal

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. The proposed methods are based on a specific subset of explicit one-step…

Numerical Analysis · Mathematics 2019-04-16 Vu Thai Luan , Rujeko Chinomona , Daniel R. Reynolds

The simulation of chemical kinetics involving multiple scales constitutes a modeling challenge (from ordinary differential equations to Markov chain) and a computational challenge (multiple scales, large dynamical systems, time step…

Numerical Analysis · Mathematics 2021-06-18 Assyr Abdulle , Lia Gander , Giacomo Rosilho de Souza

This work focuses on the construction of a new class of fourth-order accurate methods for multirate time evolution of systems of ordinary differential equations. We base our work on the Recursive Flux Splitting Multirate (RFSMR) version of…

Numerical Analysis · Mathematics 2019-08-26 Jean M. Sexton , Daniel R. Reynolds

This paper is concerned with the theory, construction and application of implicit Peer two-step methods that are super-convergent for variable stepsizes, i.e., preserve their classical order achieved for uniform stepsizes when applied to…

Optimization and Control · Mathematics 2024-04-23 Jens Lang , Bernhard A. Schmitt

We randomize the implicit two-stage Runge-Kutta scheme in order to improve the rate of convergence (with respect to a deterministic scheme) and stability of the approximate solution (with respect to the solution generated by the explicit…

Numerical Analysis · Mathematics 2025-01-17 Tomasz Bochacik , Paweł Przybyłowicz
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