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2. Linear multistep method - Wikipedia

   en.wikipedia.org/wiki/Linear_multistep_method

   The first Dahlquist barrier states that a zero-stable and linear q-step multistep method cannot attain an order of convergence greater than q + 1 if q is odd and greater than q + 2 if q is even. If the method is also explicit, then it cannot attain an order greater than q ( Hairer, Nørsett & Wanner 1993 , Thm III.3.5).

3. Newton's method - Wikipedia

   en.wikipedia.org/wiki/Newton's_method

   For example, for Newton's method as applied to a function f to oscillate between 0 and 1, it is only necessary that the tangent line to f at 0 intersects the x-axis at 1 and that the tangent line to f at 1 intersects the x-axis at 0. [17] This is the case, for example, if f(x) = x 3 − 2x + 2.

4. Conjugate gradient method - Wikipedia

   en.wikipedia.org/wiki/Conjugate_gradient_method

   A comparison of the convergence of gradient descent with optimal step size (in green) and conjugate vector (in red) for minimizing a quadratic function associated with a given linear system. Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2).

5. MacCormack method - Wikipedia

   en.wikipedia.org/wiki/MacCormack_method

   The application of MacCormack method to the above equation proceeds in two steps; a predictor step which is followed by a corrector step. Predictor step: In the predictor step, a "provisional" value of u {\displaystyle u} at time level n + 1 {\displaystyle n+1} (denoted by u i p {\displaystyle u_{i}^{p}} ) is estimated as follows

6. Relaxation (iterative method) - Wikipedia

   en.wikipedia.org/wiki/Relaxation_(iterative_method)

   Relaxation methods are used to solve the linear equations resulting from a discretization of the differential equation, for example by finite differences. [ 2 ] [ 3 ] [ 4 ] Iterative relaxation of solutions is commonly dubbed smoothing because with certain equations, such as Laplace's equation , it resembles repeated application of a local ...

7. Jacobi method - Wikipedia

   en.wikipedia.org/wiki/Jacobi_method

   In 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.

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9. Lax–Wendroff method - Wikipedia

   en.wikipedia.org/wiki/Lax–Wendroff_method

   What follows is the Richtmyer two-step Lax–Wendroff method. The first step in the Richtmyer two-step Lax–Wendroff method calculates values for f(u(x, t)) at half time steps, t n + 1/2 and half grid points, x i + 1/2. In the second step values at t n + 1 are calculated using the data for t n and t n + 1/2.