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An integer relation algorithm is an algorithm for finding integer relations. Specifically, given a set of real numbers known to a given precision, an integer relation algorithm will either find an integer relation between them, or will determine that no integer relation exists with coefficients whose magnitudes are less than a certain upper bound .
However, in the form that is often used in number theory (namely, as an algorithm for finding integer solutions to an equation + =, or, what is the same, for finding the quantities whose existence is assured by the Chinese remainder theorem) it first appears in the works of Āryabhaṭa (fifth to sixth centuries) as an algorithm called ...
When used to find integer relations, a typical input to the algorithm consists of an augmented identity matrix with the entries in the last column consisting of the elements (multiplied by a large positive constant to penalize vectors that do not sum to zero) between which the relation is sought. The LLL algorithm for computing a nearly ...
The Euclidean algorithm was the first integer relation algorithm, which is a method for finding integer relations between commensurate real numbers. Several novel integer relation algorithms have been developed, such as the algorithm of Helaman Ferguson and R.W. Forcade (1979) [49] and the LLL algorithm. [50] [51]
To find the needed , , , and the algorithm uses Floyd's cycle-finding algorithm to find a cycle in the sequence =, where the function: + is assumed to be random-looking and thus is likely to enter into a loop of approximate length after steps.
In number theory, the general number field sieve (GNFS) is the most efficient classical algorithm known for factoring integers larger than 10 100. Heuristically, its complexity for factoring an integer n (consisting of ⌊log 2 n ⌋ + 1 bits) is of the form
Using repeated squaring, the running time of this algorithm is O(k n 3), for an n-digit number, and k is the number of rounds performed; thus this is an efficient, polynomial-time algorithm. FFT-based multiplication, for example the Schönhage–Strassen algorithm, can decrease the running time to O(k n 2 log n log log n) = Õ(k n 2).
The 'Extract number' section shows an example where integer 0 has already been output and the index is at integer 1. 'Generate numbers' is run when all integers have been output. For a w -bit word length, the Mersenne Twister generates integers in the range [ 0 , 2 w − 1 ] {\displaystyle [0,2^{w}-1]} .