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Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods…

Numerical Analysis · Mathematics 2022-04-05 Yiannis Hadjimichael , David Ketcheson , Lajos Lóczi , Adrián Németh

The general synthetic iterative scheme (GSIS) has proven its efficacy in modeling rarefied gas dynamics, where the steady-state solutions are obtained after dozens of iterations of the Boltzmann equation, with minimal numerical dissipation…

Computational Physics · Physics 2024-07-10 Liyan Luo , Lei Wu

In this paper, we extend the implicit-explicit (IMEX) methods of Peer type recently developed in [Lang, Hundsdorfer, J. Comp. Phys., 337:203--215, 2017] to a broader class of two-step methods that allow the construction of super-convergent…

Numerical Analysis · Mathematics 2018-06-08 Moritz Schneider , Jens Lang , Willem Hundsdorfer

We propose a generalization of the recently developed system identification method called Sign-Perturbed Sums (SPS). The proposed construction is based on the instrumental variables estimate and, unlike the original SPS, it can construct…

Methodology · Statistics 2015-09-17 Valerio Volpe , Balázs Cs. Csáji , Algo Carè , Erik Weyer , Marco C. Campi

For the simulations of unsteady flow, the global time step becomes really small with a large variation of local cell size. In this paper, an implicit high-order gas-kinetic scheme (HGKS) is developed to remove the restrictions on the time…

Numerical Analysis · Mathematics 2024-03-04 Yaqing Yang , Liang Pan , Kun Xu

Stochastic MPECs have found increasing relevance for modeling a broad range of settings in engineering and statistics. Yet, there seem to be no efficient first/zeroth-order schemes equipped with non-asymptotic rate guarantees for resolving…

Optimization and Control · Mathematics 2022-06-23 Shisheng Cui , Uday V. Shanbhag , Farzad Yousefian

The rigorous stability analysis of high-order implicit-explicit multistep (IEMS) methods for nonlinear parabolic equations by using discrete energy arguments is a long standing open issue due to their non-A-stable property. A novel…

Numerical Analysis · Mathematics 2026-05-08 Hong-lin Liao , Chaoyu Quan , Tao Tang , Tao Zhou

Stiff systems of ordinary differential equations (ODEs) are pervasive in many science and engineering fields, yet standard neural ODE approaches struggle to learn them. This limitation is the main barrier to the widespread adoption of…

Numerical Analysis · Mathematics 2024-10-10 Colby Fronk , Linda Petzold

The increasing number of applications requiring the solution of large scale singular value problems have rekindled interest in iterative methods for the SVD. Some promising recent ad- vances in large scale iterative methods are still…

Mathematical Software · Computer Science 2017-01-25 Lingfei Wu , Eloy Romero , Andreas Stathopoulos

In contrast to the prevailing view in the literature, it is shown that even extremely stiff sets of ordinary differential equations may be solved efficiently by explicit methods if limiting algebraic solutions are used to stabilize the…

Solar and Stellar Astrophysics · Physics 2016-08-01 Mike Guidry

We address a numerical methodology for the computation of coarse-grained stable and unstable manifolds of saddle equilibria/stationary states of multiscale/stochastic systems for which a "good" macroscopic description in the form of…

Dynamical Systems · Mathematics 2019-09-10 Constantinos Siettos , Lucia Russo

Forecasting physical signals in long time range is among the most challenging tasks in Partial Differential Equations (PDEs) research. To circumvent limitations of traditional solvers, many different Deep Learning methods have been…

Machine Learning · Computer Science 2023-06-09 Leon Migus , Julien Salomon , Patrick Gallinari

Time-series imputation benchmarks employ uniform random masking and shape-agnostic metrics (MSE, RMSE), implicitly weighting evaluation by regime prevalence. In systems with a dominant attractor -- homeostatic physiology, nominal industrial…

Machine Learning · Computer Science 2026-02-18 Amirreza Dolatpour Fathkouhi , Alireza Namazi , Heman Shakeri

High-order discretizations of partial differential equations (PDEs) necessitate high-order time integration schemes capable of handling both stiff and nonstiff operators in an efficient manner. Implicit-explicit (IMEX) integration based on…

Numerical Analysis · Mathematics 2022-01-19 Steven Roberts , Arash Sarshar , Adrian Sandu

The Residual Smooting Scheme (RSS) have been introduced in \cite{AverbuchCohenIsraeli} as a backward Euler's method with a simplified implicit part for the solution of parabolic problems. RSS have stability properties comparable to those of…

Numerical Analysis · Mathematics 2015-06-24 Brachet Matthieu , Chehab Jean-Paul

In this study, an implicit scheme for the gas-kinetic scheme (GKS) on the unstructured hybrid mesh is proposed. The Spalart-Allmaras (SA) one equation turbulence model is incorporated into the implicit gas-kinetic scheme (IGKS) to predict…

Computational Physics · Physics 2017-09-05 Dongxin Pan , Chengwen Zhong , Congshan Zhuo

We present an implicit-explicit (IMEX) scheme for semilinear wave equations with strong damping. By treating the nonlinear, nonstiff term explicitly and the linear, stiff part implicitly, we obtain a method which is not only unconditionally…

Numerical Analysis · Mathematics 2024-07-01 Daniel Eckhardt , Marlis Hochbruck , Barbara Verfürth

In order to treat the multiple time scales of ocean dynamics in an efficient manner, the baroclinic-barotropic splitting technique has been widely used for solving the primitive equations for ocean modeling. Based on the framework of strong…

Numerical Analysis · Mathematics 2022-03-14 Rihui Lan , Lili Ju , Zhu Wang , Max Gunzburger , Philip Jones

We study the sample complexity of the Sign-Perturbed Sums (SPS) method, which constructs exact, non-asymptotic confidence regions for the true system parameters under mild statistical assumptions, such as independent and symmetric noise…

Machine Learning · Statistics 2024-09-04 Szabolcs Szentpéteri , Balázs Csanád Csáji

A preceding paper demonstrated that explicit asymptotic methods generally work much better for extremely stiff reaction networks than has previously been shown in the literature. There we showed that for systems well removed from…

Solar and Stellar Astrophysics · Physics 2022-10-19 M. W. Guidry , J. A. Harris