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  2. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    A SWB generator is the basis for the RANLUX generator, [19] widely used e.g. for particle physics simulations. Maximally periodic reciprocals: 1992 R. A. J. Matthews [20] A method with roots in number theory, although never used in practical applications. KISS: 1993 G. Marsaglia [21] Prototypical example of a combination generator. Multiply ...

  3. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. The method represents one of the oldest and best-known pseudorandom number generator algorithms.

  4. Sobol sequence - Wikipedia

    en.wikipedia.org/wiki/Sobol_sequence

    Sobol’ sequences (also called LP τ sequences or (t, s) sequences in base 2) are a type of quasi-random low-discrepancy sequence. They were first introduced by the Russian mathematician Ilya M. Sobol’ (Илья Меерович Соболь) in 1967.

  5. Middle-square method - Wikipedia

    en.wikipedia.org/wiki/Middle-square_method

    To generate a sequence of n-digit pseudorandom numbers, an n-digit starting value is created and squared, producing a 2n-digit number. If the result has fewer than 2n digits, leading zeroes are added to compensate. The middle n digits of the result would be the next number in the sequence and returned as the result. This process is then ...

  6. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    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]} .

  7. Random sequence - Wikipedia

    en.wikipedia.org/wiki/Random_sequence

    Kolmogorov's definition of a random string was that it is random if it has no description shorter than itself via a universal Turing machine. [9] Three basic paradigms for dealing with random sequences have now emerged: [10] The frequency / measure-theoretic approach. This approach started with the work of Richard von Mises and Alonzo Church.

  8. Randomness test - Wikipedia

    en.wikipedia.org/wiki/Randomness_test

    The sequences they produce are called pseudo-random sequences. These generators do not always generate sequences which are sufficiently random, but instead can produce sequences which contain patterns. For example, the infamous RANDU routine fails many randomness tests dramatically, including the spectral test.

  9. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.