Gauss-Legendre algorithm
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The Gauss-Legendre algorithm is an algorithm to compute the digits of π. It is notable for being rapidly convergent, with only 25 iterations producing 45 million correct digits of π. However, the drawback is that it is memory intensive and it is therefore sometimes not used over Machin-like formulas.
The method is based on the individual work of Carl Friedrich Gauss (1777-1855) and Adrien-Marie Legendre (1752-1833) combined with modern algorithms for multiplication and square roots. It repeatedly replaces two numbers by their arithmetic and geometric mean, in order to approximate their arithmetic-geometric mean.
The version presented below is also known as the Brent-Salamin (or Salamin-Brent) algorithm; it was independently discovered in 1975 by Richard Brent and Eugene Salamin. It was used to compute the first 206,158,430,000 decimal digits of π on September 18 to 20, 1999, and the results were checked with Borwein's algorithm.
1. Initial value setting:
2. Repeat the following instructions until the difference of and is within the desired accuracy:
- ,
- ,
- ,
- .
3. π is approximated with , and as:
- .
The first three iterations give:
The algorithm has second-order convergent nature, which essentially means that the number of correct digits doubles with each step of the algorithm.
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[edit] Mathematical background
[edit] Limits of the arithmetic-geometric mean
The arithmetic-geometric mean of two numbers, and , is found by calculating the limit of the sequences , , which both converge to the same limit. If and then the limit is where is the complete elliptic integral of the first kind
- .
If , . then
where be the complete elliptic integral of the second kind:
- .
Gauss knew of both of these results.[1]
[edit] Legendre’s Identity
For and such that Legendre proved the identity:
[edit] Gauss-Legendre Method
The values can be substituted into Legendre’s Identity and the approximations to K, E can be found by terms in the sequences for the arithmetic geometric mean with and .[1]
[edit] See also
[edit] References
- ^ a b c Brent, Richard, Traub, J F, ed., “Multiple-precision zero-finding methods and the complexity of elementary function evaluation”, Analytic Computational Complexity (New York: Academic Press): 151–176, <http://wwwmaths.anu.edu.au/~brent/pub/pub028.html>. Retrieved on 8 September 2007