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  2. Integer factorization records - Wikipedia

    en.wikipedia.org/wiki/Integer_factorization_records

    Integer factorization is the process of determining which prime numbers divide a given positive integer.Doing this quickly has applications in cryptography.The difficulty depends on both the size and form of the number and its prime factors; it is currently very difficult to factorize large semiprimes (and, indeed, most numbers that have no small factors).

  3. Factorization - Wikipedia

    en.wikipedia.org/wiki/Factorization

    In mathematics, factorization (or factorisation, see English spelling differences) or factoring consists of writing a number or another mathematical object as a product of several factors, usually smaller or simpler objects of the same kind. For example, 3 × 5 is an integer factorization of 15, and (x2)(x + 2) is a polynomial ...

  4. Integer factorization - Wikipedia

    en.wikipedia.org/wiki/Integer_factorization

    A general-purpose factoring algorithm, also known as a Category 2, Second Category, or Kraitchik family algorithm, [10] has a running time which depends solely on the size of the integer to be factored. This is the type of algorithm used to factor RSA numbers. Most general-purpose factoring algorithms are based on the congruence of squares method.

  5. Aiken code - Wikipedia

    en.wikipedia.org/wiki/Aiken_code

    The Aiken code (also known as 2421 code) [1] [2] is a complementary binary-coded decimal (BCD) code. A group of four bits is assigned to the decimal digits from 0 to 9 according to the following table. The code was developed by Howard Hathaway Aiken and is still used today in digital clocks, pocket calculators and similar devices [citation needed].

  6. Lehmer random number generator - Wikipedia

    en.wikipedia.org/wiki/Lehmer_random_number_generator

    The Lehmer random number generator [1] (named after D. H. Lehmer), sometimes also referred to as the Park–Miller random number generator (after Stephen K. Park and Keith W. Miller), is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is

  7. Fermat number - Wikipedia

    en.wikipedia.org/wiki/Fermat_number

    This is useful in computer science, since most data structures have members with 2 X possible values. For example, a byte has 256 (2 8) possible values (0–255). Therefore, to fill a byte or bytes with random values, a random number generator that produces values 1–256 can be used, the byte taking the output value −1.

  8. Table of divisors - Wikipedia

    en.wikipedia.org/wiki/Table_of_divisors

    a perfect number equals the sum of its proper divisors; that is, s(n) = n; an abundant number is lesser than the sum of its proper divisors; that is, s(n) > n; a highly abundant number has a sum of positive divisors that is greater than any lesser number; that is, σ(n) > σ(m) for every positive integer m < n.

  9. RSA numbers - Wikipedia

    en.wikipedia.org/wiki/RSA_numbers

    The first RSA numbers generated, from RSA-100 to RSA-500, were labeled according to their number of decimal digits. Later, beginning with RSA-576, binary digits are counted instead. An exception to this is RSA-617, which was created before the change in the numbering scheme.