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midpoint method : ウィキペディア英語版
midpoint method

In numerical analysis, a branch of applied mathematics, the midpoint method is a one-step method for numerically solving the differential equation,
: y'(t) = f(t, y(t)), \quad y(t_0) = y_0 .
The explicit midpoint method is given by the formula
: y_ = y_n + hf\left(t_n+\frac,y_n+\fracf(t_n, y_n)\right), \qquad\qquad (1e)
the implicit midpoint method by
: y_ = y_n + hf\left(t_n+\frac,\frac12 (y_n+y_)\right), \qquad\qquad (1i)
for n=0, 1, 2, \dots Here, h is the ''step size'' — a small positive number, t_n=t_0 + n h, and y_n is the computed approximate value of y(t_n). The explicit midpoint method is also known as the modified Euler method, the implicit method is the most simple collocation method, and, applied to Hamiltionian dynamics, a symplectic integrator.
The name of the method comes from the fact that in the formula above the function f giving the slope of the solution is evaluated at t=t_n+h/2, which is the midpoint between t_n at which the value of ''y''(''t'') is known and t_ at which the value of ''y''(''t'') needs to be found.
The local error at each step of the midpoint method is of order O\left(h^3\right), giving a global error of order O\left(h^2\right). Thus, while more computationally intensive than Euler's method, the midpoint method's error generally decreases faster as h \to 0.
The methods are examples of a class of higher-order methods known as Runge-Kutta methods.
==Derivation of the midpoint method==

The midpoint method is a refinement of the Euler's method
: y_ = y_n + hf(t_n,y_n),\,
and is derived in a similar manner.
The key to deriving Euler's method is the approximate equality
: y(t+h) \approx y(t) + hf(t,y(t)) \qquad\qquad (2)
which is obtained from the slope formula
: y'(t) \approx \frac \qquad\qquad (3)
and keeping in mind that y' = f(t, y).
For the midpoint methods, one replaces (3) with the more accurate
: y'\left(t+\frac\right) \approx \frac
when instead of (2) we find
: y(t+h) \approx y(t) + hf\left(t+\frac,y\left(t+\frac\right)\right). \qquad\qquad (4)
One cannot use this equation to find y(t+h) as one does not know y at t+h/2. The solution is then to use a Taylor series expansion exactly as if using the Euler method to solve for y(t+h/2):
:y\left(t + \frac\right) \approx y(t) + \fracy'(t)=y(t) + \fracf(t, y(t)),
which, when plugged in (4), gives us
:y(t + h) \approx y(t) + hf\left(t + \frac, y(t) + \fracf(t, y(t))\right)
and the explicit midpoint method (1e).
The implicit method (1i) is obtained by approximating the value at the half step t+h/2 by the midpoint of the line segment from y(t) to y(t+h)
:y\left(t+\frac h2\right)\approx \frac12\bigl(y(t)+y(t+h)\bigr)
and thus
:\frac\approx y'\left(t+\frac h2\right)\approx k=f\left(t+\frac h2,\frac12\bigl(y(t)+y(t+h)\bigr)\right)
Inserting the approximation y_n+h\,k for y(t_n+h)
results in the implicit Runge-Kutta method
:\begin
k&=f\left(t_n+\frac h2,y_n+\frac h2 k\right)\\
y_&=y_n+h\,k
\end
which contains the implicit Euler method with step size h/2 as its first part.
Because of the time symmetry of the implicit method, all
terms of even degree in h of the local error cancel, so that the local error is automatically of order \mathcal O(h^3). Replacing the implicit with the explicit Euler method in the determination of k results again in the explicit midpoint method.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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