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  2. List of random number generators - Wikipedia

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

    A modification of Lagged-Fibonacci generators. A SWB generator is the basis for the RANLUX generator, widely used e.g. for particle physics simulations. Maximally periodic reciprocals: 1992 R. A. J. Matthews A method with roots in number theory, although never used in practical applications. KISS: 1993 G. Marsaglia

  3. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.

  4. Hardware random number generator - Wikipedia

    en.wikipedia.org/wiki/Hardware_random_number...

    A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a physical entropy ...

  5. Lavarand - Wikipedia

    en.wikipedia.org/wiki/Lavarand

    Lavarand, also known as the Wall of Entropy, was a hardware random number generator designed by Silicon Graphics that worked by taking pictures of the patterns made by the floating material in lava lamps, extracting random data from the pictures, and using the result to seed a pseudorandom number generator. [1]

  6. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    A pseudorandom number generator ( PRNG ), also known as a deterministic random bit generator ( DRBG ), [1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value ...

  7. Random.org - Wikipedia

    en.wikipedia.org/wiki/Random.org

    Random.org is distinguished from pseudo-random number generators, which use mathematical formulae to produce random-appearing numbers. The website was created in 1998 by Mads Haahr, a doctor and computer science professor at Trinity College in Dublin, Ireland. Random numbers are generated based on atmospheric noise captured by several radios ...

  8. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    To illustrate, imagine if a simple 32 bit linear congruential pseudo-random number generator of the type supplied with most programming languages (e.g., as the 'rand' or 'rnd' function) is used as a source of keys. There will only be some four billion possible values produced before the generator repeats itself.

  9. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    Random seed. A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator . For a seed to be used in a pseudorandom number generator, it does not need to be random. Because of the nature of number generating algorithms, so long as the original seed is ignored, the rest of the values that ...

  10. Counter-based random number generator - Wikipedia

    en.wikipedia.org/wiki/Counter-based_random...

    A counter-based random number generation ( CBRNG, also known as a counter-based pseudo-random number generator, or CBPRNG) is a kind of pseudorandom number generator that uses only an integer counter as its internal state. They are generally used for generating pseudorandom numbers for large parallel computations.

  11. Multiply-with-carry pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Multiply-with-carry...

    Multiply-with-carry pseudorandom number generator. In computer science, multiply-with-carry (MWC) is a method invented by George Marsaglia [1] for generating sequences of random integers based on an initial set from two to many thousands of randomly chosen seed values.