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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.
However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.
Random.org (stylized as RANDOM.ORG) is a website that produces random numbers based on atmospheric noise. In addition to generating random numbers in a specified range and subject to a specified probability distribution, which is the most commonly done activity on the site, it has free tools to simulate events such as flipping coins, shuffling cards, and rolling dice.
Hardware random number generator. In computing, a hardware random number generator ( HRNG ), true random number generator ( TRNG ), non-deterministic random bit generator ( NRBG ), [1] or physical random number generator [2] [3] is a device that generates random numbers from a physical process capable of producing entropy (in other words, the ...
Applications of randomness. Randomness has many uses in science, art, statistics, cryptography, gaming, gambling, and other fields. For example, random assignment in randomized controlled trials helps scientists to test hypotheses, and random numbers or pseudorandom numbers help video games such as video poker .
Mersenne Twister. The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto [ ja] (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length.
In mathematics and statistics, a random number is either Pseudo-random or a number generated for, or part of, a set exhibiting statistical randomness. Algorithms and implementations [ edit ] A 1964-developed algorithm [1] is popularly known as the Knuth shuffle or the Fisher–Yates shuffle (based on work they did in 1938).
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.
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