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The multiples of a given prime are generated as a sequence of numbers starting from that prime, with constant difference between them that is equal to that prime. [1] This is the sieve's key distinction from using trial division to sequentially test each candidate number for divisibility by each prime. [ 2 ]
A prime sieve works by creating a list of all integers up to a desired limit and progressively removing composite numbers (which it directly generates) until only primes are left. This is the most efficient way to obtain a large range of primes; however, to find individual primes, direct primality tests are more efficient [citation needed].
The following is pseudocode which combines Atkin's algorithms 3.1, 3.2, and 3.3 [1] by using a combined set s of all the numbers modulo 60 excluding those which are multiples of the prime numbers 2, 3, and 5, as per the algorithms, for a straightforward version of the algorithm that supports optional bit-packing of the wheel; although not specifically mentioned in the referenced paper, this ...
The above obscure-but-commonly-implemented Python version of the Sieve of Sundaram hides the true complexity of the algorithm due to the following reasons: The range for the outer i looping variable is much too large, resulting in redundant looping that cannot perform any composite number culling; the proper range is to the array indices that ...
Because the set of primes is a computably enumerable set, by Matiyasevich's theorem, it can be obtained from a system of Diophantine equations. Jones et al. (1976) found an explicit set of 14 Diophantine equations in 26 variables, such that a given number k + 2 is prime if and only if that system has a solution in nonnegative integers: [7]
While a safe prime ensures that almost any element of the group has a large order, the period of the generator is specifically the order of b. For small moduli, more computationally expensive methods can be used to find multipliers a where the period is ab/2 − 1. The following are again maximum values of a of various sizes.
In Boolean algebra, Petrick's method [1] (also known as Petrick function [2] or branch-and-bound method) is a technique described by Stanley R. Petrick (1931–2006) [3] [4] in 1956 [5] [6] for determining all minimum sum-of-products solutions from a prime implicant chart. [7]
Blum Blum Shub takes the form + =, where M = pq is the product of two large primes p and q.At each step of the algorithm, some output is derived from x n+1; the output is commonly either the bit parity of x n+1 or one or more of the least significant bits of x n+1.