Random Number Generators

Random number generation

Random number generation is a method by which, usually by means of an random number generator (RNG), a sequence of symbols or numbers that can't be reliably predictable better than the random chance is generated. This means that the particular sequence that is generated will have patterns detectable in hindsight but impossible to see in the future. In reality, random number generators can be hardware random-number generators(HRNGS) that produce random numbers. Each generation is a function of the current value of the physical environment's attribute , which changes constantly in a manner that is practically impossible to model. This would be in contrast to so-called "random number generations" done by pseudorandom number generators (PRNGs) that generate numbers that only look random but are in fact pre-determined--these generations can be reproduced simply by knowing the state of the PRNG.

Different applications of randomness have led to the creation of various methods for producing random data. Certain of these techniques have been used since antiquity, there are many popular "classic" examples, including the rolling of dice, coin flipping, the shuffling of playing cards, the use of yarrow stalks (for the purpose of divination) inside the I Ching, as well as numerous other methods. Because of their mechanical character of techniques the creation of large quantities of numbers that were sufficiently random (important in the field of statistics) took a lot of effort and time. This meant that the results might be compiled and distributed in random number tables.

A variety of algorithms that generate pseudorandom numbers exist. However, none of them meet the notion of real randomness, although they may have a chance to pass, but with varying degrees of success, some of the tests that are that are designed to gauge the extent to which their results can be unpredictable (that is, to what degree their patterns are discernible). This generally makes them unusable to be used in applications such as the cryptographic field. However, thoughtfully designed cryptographically secure pseudorandom number generators (CSPRNGS) also exist, and have functions specifically designed to be used in cryptography.

Practical applications and uses[editPractical applications and uses[edit

Original article The applications for randomness

Random number generators have applications that are used in games of chance, statistical sampling and computer simulation, cryptography entirely randomized design, and other areas where an unpredictability of the outcome is desirable. In general, for applications that have unpredictable outcomes as their primary feature such as security applications, hardware generators are preferred over pseudorandom algorithmswhen they are feasible.

Pseudorandom generation tools are useful when developing Monte-Carlo simulations, as testing is facilitated by the capability to run the identical number of random sequences again beginning with exactly the same random seed. They also are used in cryptography as long as it is ensured that the seed is kept secret. Both receivers and senders can generate the identical set of numbers to be used as keys.

The generation of pseudorandom numbers is a crucial and often used task in computer programming. While cryptography and specific mathematical algorithms require a high level in apparent randomness, many other processes require only a modest amount of unpredictability. Some simple examples might be showing a user the "random quote of the day", or determining which way a computer-controlled adversary might move in a computer gaming. A less pronounced form of randomness is utilized in hash algorithms, as well as in the development of amortized searching or sorting techniques.

Some programs that appear on first sight to be suitable for randomization however, they aren't quite so simple. For instance, a system which "randomly" selects music tracks for use as a background music system must only seem random, and may even contain ways to regulate the selection of music A true random system is not restricted to the same item appearing several times in succession.