LYCOS RETRIEVER 
Pseudorandom Number Generator: Seeds
built 783 days ago
Given an initial starting point, called a seed, pseudorandom number generators are completely deterministic. In many cases it is desirable to locally or globally set the seed for a random number generator to obtain a constant sequence of "random" values. If set globally, the seed will affect future pseudorandom numbers unless a new seed is explicitly set. If set locally, the seed will only affect random number and element generation within the localized code.
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Sets the seed for this pseudorandom number generator. As described above, two instances of the same random class, starting with the same seed, should produce the same results, if the same methods are called. The implementation for java.util.Random is:
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When Mathematica starts up, it takes the time of day (measured in small fractions of a second) as the seed for the pseudorandom number generator. Two different Mathematica sessions will therefore almost always give different sequences of pseudorandom numbers.
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[One] approach is to use a pseudorandom number generator fed by a random seed. Since these are deterministic algorithms, it is important to find one that is cryptographically secure and ... to use a truly random seed; the generator effectively acts as an "expander" from the seed to a larger amount of pseudorandom data. The seed must be sufficiently variable to deter attacks based on trying all possible seeds.
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Pseudorandom number generators algorithmically create numbers that have some apparent level of randomness. Methods for pseudorandom number generation typically use a recurrence relation to generate a number from the current state and to establish a new state from which the next number will be generated. The state can be set by seeding the generator with an integer that will be used to initialize the recurrence relation in the algorithm.
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This class generates pseudorandom numbers. It uses the same algorithm as the original JDK-class, so that your programs behave exactly the same way, if started with the same seed. The algorithm is described in The Art of Computer Programming, Volume 2 by Donald Knuth in Section 3.2.1. It is a 48-bit seed, linear congruential formula. If two instances of this class are created with the same seed and the same calls to these classes are made, they behave exactly the same way. This should be even true for foreign implementations (like this), so every port must use the same algorithm as described here.
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Seeds