Search results
Results from the WOW.Com Content Network
In computational number theory, a variety of algorithms make it possible to generate prime numbers efficiently. These are used in various applications, for example hashing, public-key cryptography, and search of prime factors in large numbers. For relatively small numbers, it is possible to just apply trial division to each successive odd ...
A prime number is a natural number that has exactly two distinct natural number divisors: the number 1 and itself. To find all the prime numbers less than or equal to a given integer n by Eratosthenes' method: Create a list of consecutive integers from 2 through n: (2, 3, 4, ..., n). Initially, let p equal 2, the smallest prime number.
These numbers have been proved prime by computer with a primality test for their form, for example the Lucas–Lehmer primality test for Mersenne numbers. “!” is the factorial, “#” is the primorial, and () is the third cyclotomic polynomial, defined as + +.
The Euclidean algorithm is based on the principle that the greatest common divisor of two numbers does not change if the larger number is replaced by its difference with the smaller number. For example, 21 is the GCD of 252 and 105 (as 252 = 21 × 12 and 105 = 21 × 5) , and the same number 21 is also the GCD of 105 and 252 − 105 = 147 .
One of the two elements in the second level, which is a max (or odd) level, is the greatest element in the min-max heap Let x {\displaystyle x} be any node in a min-max heap. If x {\displaystyle x} is on a min (or even) level, then x . k e y {\displaystyle x.key} is the minimum key among all keys in the subtree with root x {\displaystyle x} .
What is the fastest algorithm for multiplication of two n-digit numbers? What is the lowest possible average-case time complexity of Shellsort with a deterministic fixed gap sequence? Can 3SUM be solved in strongly sub-quadratic time, that is, in time O(n 2−ϵ) for some ϵ>0?
Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!
Given a bipartite graph = (,), we are to find a maximum cardinality matching in , that is a matching that contains the largest possible number of edges. This problem can be transformed into a maximum flow problem by constructing a network N = ( X ∪ Y ∪ { s , t } , E ′ ) {\displaystyle N=(X\cup Y\cup \{s,t\},E')} , where