https://github.com/abhibsws/high_wso_erk_methods

https://github.com/abhibsws/high_wso_erk_methods

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
    Links to: arxiv.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: abhibsws
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 3.24 MB
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme

README.md

Explicit Runge-Kutta Methods that Alleviate Order Reduction

Authors: Abhijit Biswas, David Ketcheson, Steven Roberts, Benjamin Seibold, and David Shirokoff

This repository contains all the code used to generate the figures in the manuscript https://arxiv.org/abs/2310.02817. To reproduce the figures and obtain the coefficients of the ERK methods with high weak stage order, follow these steps:

  • Clone the repository. Inside the cloned repository, you will find a folder named 'ConvgPlotFrom_Data'.
  • In the 'ConvgPlotFromData' folder, locate and run the notebook named 'PlotConvergencefromData.ipynb'. This notebook will generate all the figures presented in the manuscript.
  • To generate the data required for these figures, you can run various test cases provided in different folders with appropriate names.
  • For information on all the newly discovered explicit Runge-Kutta Methods with high weak stage orders, refer to the 'ERK_Coefficients.md' file.

Owner

  • Login: abhibsws
  • Kind: user

GitHub Events

Total
Last Year