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The midpoint method computes + so that the red chord is approximately parallel to the tangent line at the midpoint (the green line). In numerical analysis , a branch of applied mathematics , the midpoint method is a one-step method for numerically solving the differential equation ,
If = (+) / for all i, the method is the midpoint rule [2] [3] and gives a middle Riemann sum. If f ( x i ∗ ) = sup f ( [ x i − 1 , x i ] ) {\displaystyle f(x_{i}^{*})=\sup f([x_{i-1},x_{i}])} (that is, the supremum of f {\textstyle f} over [ x i − 1 , x i ] {\displaystyle [x_{i-1},x_{i}]} ), the method is the upper rule and gives an upper ...
The Gauss–Legendre method of order two is the implicit midpoint rule. Its Butcher tableau is: 1/2: ... The method of order 2 is just an implicit midpoint method.
A loose rule of thumb dictates that stiff differential equations require the use of implicit schemes, whereas non-stiff problems can be solved more efficiently with explicit schemes. The so-called general linear methods (GLMs) are a generalization of the above two large classes of methods.
Simpson's rule, which is based on a polynomial of order 2, is also a Newton–Cotes formula. Quadrature rules with equally spaced points have the very convenient property of nesting . The corresponding rule with each interval subdivided includes all the current points, so those integrand values can be re-used.
In calculus, the trapezoidal rule (also known as the trapezoid rule or trapezium rule) [a] is a technique for numerical integration, i.e., approximating the definite integral: (). The trapezoidal rule works by approximating the region under the graph of the function f ( x ) {\displaystyle f(x)} as a trapezoid and calculating its area.
Calculus of variations is concerned with variations of functionals, which are small changes in the functional's value due to small changes in the function that is its argument. The first variation [ l ] is defined as the linear part of the change in the functional, and the second variation [ m ] is defined as the quadratic part.
This formula can be obtained by Taylor series expansion: (+) = + ′ ()! ″ ()! () +. The complex-step derivative formula is only valid for calculating first-order derivatives. A generalization of the above for calculating derivatives of any order employs multicomplex numbers , resulting in multicomplex derivatives.