# Runge-Kutta Method

The Runge-Kutta methods are iterative ways to calculate the solution of a differential equation. Starting from an initial condition, they calculate the solution forward step by step. The second-order formula (RK2) is:

\begin{equation} \begin{aligned} & k_1 = h f(x_n, y_n), \\ & k_2 = h f(x_n + \frac{h}{2}, y_n + \frac{k_1}{2}), \\ & y_{n+1} = y_n + k_2 + O(h^3). \\ \end{aligned} \end{equation} For the third-order formula, it holds:

\begin{equation} \begin{aligned} & k_1 = h f(x_n, y_n), \\ & k_2 = h f(x_n + \frac{h}{2}, y_n + \frac{k_1}{2}), \\ & k_3 = h f(x_n + h, y_n - k_1 + 2k_2), \\ & y_{n+1} = y_n + \frac{1}{6}(k_1 + 4k_2 + k_3) + O(h^4); \\ \end{aligned} \end{equation} and the forth-order formula (RK4) is:

\begin{equation} \begin{aligned} & k_1 = h f(x_n, y_n), \\ & k_2 = h f(x_n + \frac{h}{2}, y_n + \frac{k_1}{2}), \\ & k_3 = h f(x_n + \frac{h}{2}, y_n + \frac{k_2}{2}), \\ & k_4 = h f(x_n + h, y_n + k_3), \\ & y_{n+1} = y_n + \frac{1}{6}(k_1 + 2k_2 + 2k_3 + k_4) + O(h^5). \\ \end{aligned} \end{equation} This method is reasonably simple and robust and is a good general candidate for numerical solution of differential equations. It should be noted that the methods explained here are all explicit.

*The relevant Matlab codes can be downloaded using the following link:*

Matlab Codes Bank

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