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While implicit Runge--Kutta methods possess high order accuracy and important stability properties, implementation difficulties and the high expense of solving the coupled algebraic system at each time step are frequently cited as…

Numerical Analysis · Mathematics 2020-07-01 Patrick E. Farrell , Robert C. Kirby , Jorge Marchena-Menendez

Using a computationally inexpensive frozen phonon approach we have developed a technique which can be used to screen large unit cell materials and systems for enhanced superconducting critical temperatures. The method requires only density…

Superconductivity · Physics 2024-05-07 Oliver A. Dicks , Kateryna Foyevtsova , Ilya Elfimov , Rohit Prasankumar , George Sawatzky

The aim of this chapter is to show how option prices in jump-diffusion models can be computed using meshless methods based on Radial Basis Function (RBF) interpolation. The RBF technique is demonstrated by solving the partial…

Computational Finance · Quantitative Finance 2011-10-26 Ron T. L. Chan , Simon Hubbert

This work constructs and analyzes new efficient high-order two-derivative diagonally implicit Runge--Kutta (TDDIRK) schemes with optimized phase errors. Specifically, we present a convergence result for TDDIRK methods and investigate their…

Numerical Analysis · Mathematics 2025-12-18 Julius Ehigie , Vu Thai Luan

Many problems in applied mathematics require root finding algorithms. Unfortunately, root finding methods have limitations. Firstly, regarding the convergence, there is a trade-off between the size of it's domain and it's rate. Secondly the…

Numerical Analysis · Mathematics 2023-09-06 Komi Agbalenyo , Vincent Cailliez , Jonathan Cailliez

Deriving analytical solutions of ordinary differential equations is usually restricted to a small subset of problems and numerical techniques are considered. Inevitably, a numerical simulation of a differential equation will then always be…

Numerical Analysis · Mathematics 2021-05-12 Said Ouala , Laurent Debreu , Ananda Pascual , Bertrand Chapron , Fabrice Collard , Lucile Gaultier , Ronan Fablet

In this paper we propose a new efficient interpolation tool, extremely suitable for large scattered data sets. The partition of unity method is used and performed by blending Radial Basis Functions (RBFs) as local approximants and using…

Numerical Analysis · Mathematics 2016-04-18 R. Cavoretto , A. De Rossi , E. Perracchione

Stochastic Hamiltonian partial differential equations, which possess the multi-symplectic conservation law, are an important and fairly large class of systems. The multi-symplectic methods inheriting the geometric features of stochastic…

Numerical Analysis · Mathematics 2022-08-10 Jialin Hong , Baohui Hou , Qiang Li , Liying Sun

We present a systematic algorithm for the perturbative computation of soft functions that are defined in terms of two light-like Wilson lines. Our method is based on a universal parametrisation of the phase-space integrals, which we use to…

High Energy Physics - Phenomenology · Physics 2019-09-04 Guido Bell , Rudi Rahn , Jim Talbert

By combining the two-particle-irreducible (2PI) effective action common in non-equilibrium quantum field theory with the classical Martin-Siggia-Rose formalism, self-consistent equations of motion for the first and second cumulants of…

Disordered Systems and Neural Networks · Physics 2022-05-31 Tim Bode

Obtaining exact solutions to the Schr\"odinger equation in complex quantum systems poses significant challenges. In this context, numerical methods emerge as valuable tools for analyzing such systems. This article proposes a numerical…

The identification of pipe roughnesses in a water distribution network is formulated as nonlinear system of algebraic equations which turns out to be demanding to solve under real-world circumstances. This paper proposes an enhanced…

Systems and Control · Electrical Eng. & Systems 2019-11-05 Stefan Kaltenbacher , Martin Steinberger , Martin Horn

An error analysis is presented for explicit partitioned Runge-Kutta methods and multirate methods applied to conservation laws. The interfaces, across which different methods or time steps are used, lead to order reduction of the schemes.…

Numerical Analysis · Mathematics 2013-10-29 Willem Hundsdorfer , David I. Ketcheson , Igor Savostianov

Learning dynamical systems through purely data-driven methods is challenging as they do not learn the underlying conservation laws that enable them to correctly generalize. Existing port-Hamiltonian neural network methods have recently been…

Machine Learning · Computer Science 2026-02-18 Maximino Linares , Guillaume Doras , Thomas Hélie

Explicit Runge-Kutta schemes with large stable step sizes are developed for integration of high order spectral difference spatial discretization on quadrilateral grids. The new schemes permit an effective time step that is substantially…

Numerical Analysis · Mathematics 2013-07-16 M. Parsani , D. I. Ketcheson , W. Deconinck

Differential equations arise in mathematics, physics,medicine, pharmacology, communications, image processing and animation, etc. An Ordinary Differential Equation (ODE) is a differential equation if it involves derivatives with respect to…

Mathematical Software · Computer Science 2015-12-31 A. O. Anidu , S. A. Arekete , A. O. Adedayo , A. O. Adekoya

The main two algorithms for computing the numerical radius are the level-set method of Mengi and Overton and the cutting-plane method of Uhlig. Via new analyses, we explain why the cutting-plane approach is sometimes much faster or much…

Numerical Analysis · Mathematics 2022-06-07 Tim Mitchell

This paper introduces a new method for solving quadratic programs using primal-dual interior-point methods. Instead of handling complementarity as an explicit equation in the Karush-Kuhn-Tucker (KKT) conditions, we ensure that…

Optimization and Control · Mathematics 2026-04-02 Jon Arrizabalaga , Zachary Manchester

The Douglas-Rachford splitting method is a classical and widely used algorithm for solving monotone inclusions involving the sum of two maximally monotone operators. It was recently shown to be the unique frugal, no-lifting…

Optimization and Control · Mathematics 2025-12-12 Max Nilsson , Anton Åkerman , Pontus Giselsson

We extend Robust Optimization to fractional programming, where both the objective and the constraints contain uncertain parameters. Earlier work did not consider uncertainty in both the objective and the constraints, or did not use Robust…

Optimization and Control · Mathematics 2015-08-21 Bram L. Gorissen