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The main application of SRA lies in finding the [[Root (mathematics)|zeros]] of [[secular function|secular functions]]. A divide-and-conquer algorithm to find the [[eigenvalues]] and [[eigenvectors]] for various kinds of [[matrices]] is well-known in [[numerical analysis]]. In a strict sense, SRA implies a specific [[interpolation]] using simple rational functions as a part of the divide-and-conquer algorithm. Since such secular functions consist of a series of rational functions with simple poles, SRA is the best candidate to interpolate the zeros of the secular function. Moreover, based on previous researches, a simple zero that lies between two adjacent poles can be considerably well interpolated by using a two-dominant-pole rational function as an approximating function.
==Halley's
The origin of the interpolation with rational functions can be found in the previous work done by [[Edmond Halley]]. The Helley's
:<math>h(z)=\frac{a}{z+b}+c.</math>
We can determine a, b, and c so that
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Then solving <math>\,h(z)=0</math> yields the iteration
:<math>x_{n+1}=x_{n}-\frac{f(x_n)}{f'(x_n)} \left({\frac{1}{1-\frac{f(x_n)f''(x_n)}{2(f'(x_n))^2}}}\right).</math>
This is referred to as Helley's
This ''geometrical interpretation'' was derived by Gander(1978), where the equivalent iteration also was derived by apply Newton's method to
:<math>g(x)=\frac{f(x)}{\sqrt{f'(x)}}=0.</math>
We call this ''algebraic interpretation'' of Halley's formula.
Similarly, we can
:<math>h(z)=\frac{a}{z+b}.</math>
Then we need to evaluate
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