Easy-to-compile, high-order ODE solvers as C++ classes
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Updated
Jun 6, 2024 - C++
Easy-to-compile, high-order ODE solvers as C++ classes
Reproducibility repository for the paper "Multirate Time-Integration based on Dynamic ODE Partitioning through Adaptively Refined Meshes for Compressible Fluid Dynamics"
numpy-based implementation of Central WENO (CWENO) reconstructions
Aplicação dos métodos numéricos no sistema de equações diferenciais do atrator de Lorenz 🌀
Mathpaqs: a collection of mathematical packages in pure Ada
This gui program numerically solves the system of differential equations describing a swinging Atwood machine using the Runge-Kutta method of the 4th order.
Telegram bot that solves differential equations of the 1st and 2nd order using the Runge-Kutta method
Computing with B-series in Julia
When math and art came face to face. This is where I'll post attractors I've plotted using explicit Runge-Kutta methods
Runge-Kutta ODE Integrator Implemented in Cython and Numba
Arbitrary Precision Stability Polynomials by Second-Order Cones
A numerical integrator written in Elixir for the solution of sets of non-stiff ordinary differential equations (ODEs).
Physical simulation of a pendulum using second order Runge-Kutta method
Code for generating Optimal Stability Polynomials in Roots for Explicit time Integration.
I have tried to explain the multi-step-methods of solving ODEs via Adams-Bashforth and Adams-Moulton methods which are explicit and implicit methods respectively. I also have implemented them explicitly to solve for a system of ODEs, I have also done an explicit implementation of fourth order Runge-Kutta method in the process as it is needed.
A collection of functionality around rooted trees to generate order conditions for Runge-Kutta methods in Julia for differential equations and scientific machine learning (SciML)
Math solutions.
Numerical methods implementation in Python.
Numerical methods implementation in MATLAB.
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