Heun's methodIn mathematics and computational science, Heun's method may refer to the improved or modified Euler's method (that is, the explicit trapezoidal rule), or a similar two-stage Runge–Kutta method. It is named after Karl Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. Both variants can be seen as extensions of the Euler method into two-stage second-order Runge–Kutta methods.
Jacobi methodIn numerical linear algebra, the Jacobi method (a.k.a. the Jacobi iteration method) is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations. Each diagonal element is solved for, and an approximate value is plugged in. The process is then iterated until it converges. This algorithm is a stripped-down version of the Jacobi transformation method of matrix diagonalization. The method is named after Carl Gustav Jacob Jacobi.
Wurtz reactionIn organic chemistry, the Wurtz reaction, named after Charles Adolphe Wurtz, is a coupling reaction whereby two alkyl halides are treated with sodium metal to form a higher alkane. 2 R−X + 2 Na → R−R + 2 NaX The reaction is of little value except for intramolecular versions. A related reaction, which combines alkyl halides with aryl halides is called the Wurtz–Fittig reaction. The reaction proceeds by an initial metal–halogen exchange, which is described with the following idealized stoichiometry: R−X + 2 M → RM + MX This step may involve the intermediacy of radical species R·.
Newton's methodIn numerical analysis, Newton's method, also known as the Newton–Raphson method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function. The most basic version starts with a single-variable function f defined for a real variable x, the function's derivative f′, and an initial guess x0 for a root of f. If the function satisfies sufficient assumptions and the initial guess is close, then is a better approximation of the root than x0.
