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In the last few decades, numerical simulation for nonlinear oscillators has received a great deal of attention, and many researchers have been concerned with the design and analysis of numerical methods for solving oscillatory problems. In…

Numerical Analysis · Mathematics 2020-12-25 Yu-Wen Li , Xinyuan Wu

Mixed-precision algorithms have been proposed as a way for scientific computing to benefit from some of the gains seen for artificial intelligence (AI) on recent high performance computing (HPC) platforms. A few applications dominated by…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-16 Aditya Kashi , Nicholson Koukpaizan , Hao Lu , Michael Matheson , Sarp Oral , Feiyi Wang

In this paper, we develop a class of robust numerical methods for solving dynamical systems with multiple time scales. We first represent the solution of a multiscale dynamical system as a transformation of a slowly varying solution. Then,…

Numerical Analysis · Mathematics 2019-09-11 Thomas Y. Hou , Zhongjian Wang , Zhiwen Zhang

Combinatorial optimization problems are computationally hard in general, but they are ubiquitous in our modern life. A coherent Ising machine (CIM) based on a multiple-pulse degenerate optical parametric oscillator (DOPO) is an alternative…

This work introduces a general framework for constructing high-order, linearly stable, partitioned solvers for multiphysics problems from a monolithic implicit-explicit Runge-Kutta (IMEX-RK) discretization of the semi-discrete equations.…

Numerical Analysis · Mathematics 2019-02-20 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr

A novel optimization procedure for the generation of stability polynomials of stabilized explicit Runge-Kutta methods is devised. Intended for semidiscretizations of hyperbolic partial differential equations, the herein developed approach…

Numerical Analysis · Mathematics 2024-03-19 Daniel Doehring , Gregor J. Gassner , Manuel Torrilhon

We consider adaptive finite element methods for solving a multiscale system consisting of a macroscale model comprising a system of reaction-diffusion partial differential equations coupled to a microscale model comprising a system of…

Numerical Analysis · Mathematics 2015-06-22 A. Johansson , J. H. Chaudry , V. Carey , D. Estep , V. Ginting , M. Larson , S. Tavener

Large-scale overlapping problems are prevalent in practical engineering applications, and the optimization challenge is significantly amplified due to the existence of shared variables. Decomposition-based cooperative coevolution (CC)…

Neural and Evolutionary Computing · Computer Science 2024-04-17 Maojiang Tian , Mingke Chen , Wei Du , Yang Tang , Yaochu Jin

In this paper we construct high order finite volume schemes on networks of hyperbolic conservation laws with coupling conditions involving ODEs. We consider two generalized Riemann solvers at the junction, one of Toro-Castro type and a…

Numerical Analysis · Mathematics 2016-11-23 Raul Borsche , Jochen Kall

Magnetic quadrupoles are essential components of particle accelerators like the Large Hadron Collider. In order to study numerically the stability of the particle beam crossing a quadrupole, a large number of particle revolutions in the…

Computational Engineering, Finance, and Science · Computer Science 2019-06-26 Abele Simona , Luca Bonaventura , Thomas Pugnat , Barbara Dalena

The Mixture-of-Experts (MoE) technique has proven to be a promising solution to efficiently scale the model size, which has been widely applied in recent LLM advancements. However, the substantial memory overhead of MoE models has made…

Machine Learning · Computer Science 2025-10-17 Ruijie Miao , Yilun Yao , Zihan Wang , Zhiming Wang , Bairen Yi , LingJun Liu , Yikai Zhao , Tong Yang

Model merging has emerged as an efficient method to combine multiple single-task fine-tuned models. The merged model can enjoy multi-task capabilities without expensive training. While promising, merging into a single model often suffers…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Akash Dhasade , Divyansh Jhunjhunwala , Milos Vujasinovic , Gauri Joshi , Anne-Marie Kermarrec

A semi-implicit-explicit (semi-IMEX) Runge-Kutta (RK) method is proposed for the numerical integration of ordinary differential equations (ODEs) of the form $\mathbf{u}' = \mathbf{f}(t,\mathbf{u}) + G(t,\mathbf{u}) \mathbf{u}$, where…

Numerical Analysis · Mathematics 2025-04-15 Lingyun Ding

Runge--Kutta (RK) methods are widely used techniques for solving a class of initial value problems. In this article, we introduce an adaptive multiquadratic (MQ) radial basis function (RBF)-based method to develop enhanced explicit RK…

Numerical Analysis · Mathematics 2025-07-08 Rajesh Yadav , Deepak Kumar Yadav , Alpesh Kumar

A new approach for the construction of high order A-stable explicit integrators for ordinary differential equations (ODEs) is theoretically studied. Basically, the integrators are obtained by splitting, at each time step, the solution of…

Numerical Analysis · Mathematics 2012-08-24 H. de la Cruz , R. J. Biscay , J. C. Jimenez , F. Carbonell

In current research, we analyse dissipation and dispersion characteristics of most accurate two and three stage Gauss-Legendre implicit Runge-Kutta (R-K) methods. These methods, known for their $A$-stability and immense accuracy, are…

Numerical Analysis · Mathematics 2019-06-25 Subhajit Giri , Shuvam Sen

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

Support for arithmetic in multiple precisions and number formats is becoming increasingly common in emerging high-performance architectures. From a computational scientist's perspective, our goal is to determine how and where we can safely…

Numerical Analysis · Mathematics 2026-02-05 Erin Claire Carson

Multiphysics systems are driven by multiple processes acting simultaneously, and their simulation leads to partitioned systems of differential equations. This paper studies the solution of partitioned systems of differential equations using…

Numerical Analysis · Mathematics 2019-12-04 Mahesh Narayanamurthi , Adrian Sandu

Most high order computational fluid dynamics (CFD) methods for compressible flows are based on Riemann solver for the flux evaluation and Runge-Kutta (RK) time stepping technique for temporal accuracy. The main advantage of this kind of…

Computational Physics · Physics 2018-01-17 Xing Ji , Fengxiang Zhao , Wei Shyy , Kun Xu