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pseudorandomness.md

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 # Pseudorandomness
 
-Pseudorandom data is [data](data.md) that appears (for example by its statistical properties) to have been generated by a [random](random.md) process despite in fact having been generated by a [deterministic](determinism.md) (i.e. non-random) process. I.e. it's a kind of "fake" but mostly [good enough](good_enough.md) randomness that arises from [chaotic](chaos.md) systems -- systems that behave without randomness, by strict rules, but which scramble, shuffle, twist and transform the numbers in such a complicated way that they eliminate obvious patterns and leave the data looking very "random", though the numbers would be scrambled exactly the same way if the process was repeated with the same conditions, i.e. it is possible (if we know how the generator works) to exactly predict which numbers will fall out of a pseudorandom generator. This is in contrast to "true randomness" that (at least to what most physicists probably think) appears in some processes in nature (most notably in [quantum physics](quantum.md)) and which are absolutely unpredictable, even in theory. Pseudorandomness is typically used to emulate true randomness in [computers](computer.md) because for many things ([games](game.md), [graphics](graphics.md), audio,  random sampling, ...) it is absolutely sufficient, it is easy to do AND the repeatability of a pseudorandom sequence is actually an advantage to engineers, e.g. in [debugging](debugging.md) in which we have to replicate bugs we find, or in programs that simply have to behave deterministic (e.g. many network games). True randomness is basically only ever needed for [cryptography](cryptography.md)/[security](security.md) (or possibly for rare applications where we absolutely NEED to ensure lack of any patterns in the data), it is a bit harder to achieve because we need some unbiased source of real-world random data. Pseudorandom generators are so common that in most contexts in programming the word "random" silently actually means just "pseudorandom".
+Pseudorandom data is [data](data.md) that appears (for example by its statistical properties) to have been generated by a [random](randomness.md) process despite in fact having been generated by a [deterministic](determinism.md) (i.e. non-random) process. I.e. it's a kind of "fake" but mostly [good enough](good_enough.md) randomness that arises from [chaotic](chaos.md) systems -- systems that behave without randomness, by strict rules, but which scramble, shuffle, twist and transform the numbers in such a complicated way that they eliminate obvious patterns and leave the data looking very "random", though the numbers would be scrambled exactly the same way if the process was repeated with the same conditions, i.e. it is possible (if we know how the generator works) to exactly predict which numbers will fall out of a pseudorandom generator. This is in contrast to "true randomness" that (at least to what most physicists probably think) appears in some processes in nature (most notably in [quantum physics](quantum.md)) and which are absolutely unpredictable, even in theory. Pseudorandomness is typically used to emulate true randomness in [computers](computer.md) because for many things ([games](game.md), [graphics](graphics.md), audio,  random sampling, ...) it is absolutely sufficient, it is easy to do AND the repeatability of a pseudorandom sequence is actually an advantage to engineers, e.g. in [debugging](debugging.md) in which we have to replicate bugs we find, or in programs that simply have to behave deterministic (e.g. many network games). True randomness is basically only ever needed for [cryptography](cryptography.md)/[security](security.md) (or possibly for rare applications where we absolutely NEED to ensure lack of any patterns in the data), it is a bit harder to achieve because we need some unbiased source of real-world random data. Pseudorandom generators are so common that in most contexts in programming the word "random" silently actually means just "pseudorandom".
 
 A saying about psedorandom numbers states that "randomness is a task too important to be left to chance".