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==Background== The generation of random numbers has many uses, such as for [[sampling (statistics)|random sampling]], [[Monte Carlo methods]], [[board game]]s, or [[gambling]]. In [[physics]], however, most processes, such as gravitational acceleration, are deterministic, meaning that they always produce the same outcome from the same starting point. Some notable exceptions are [[radioactive decay]] and [[quantum measurement]], which are both modeled as being truly random processes in the underlying physics. Since these processes are not practical sources of random numbers, pseudorandom numbers are used, which ideally have the unpredictability of a truly random sequence, despite being generated by a deterministic process.<ref>{{cite book |title=Pseudorandomness|quote=pseudorandomness, the theory of efficiently generating objects that “look random” despite being constructed using little or no randomness|author=S. P. Vadhan |year=2012}}</ref> In many applications, the deterministic process is a [[algorithm|computer algorithm]] called a [[pseudorandom number generator]], which must first be provided with a number called a [[random seed]]. Since the same seed will yield the same sequence every time, it is important that the seed be well chosen and kept hidden, especially in [[computer security|security]] applications, where the pattern's unpredictability is a critical feature.<ref>{{cite news |newspaper=BBC |title=Web's random numbers are too weak, researchers warn |url=https://www.bbc.com/news/technology-33839925|author=Mark Ward |date=August 9, 2015}}</ref> In some cases where it is important for the sequence to be demonstrably unpredictable, physical sources of random numbers have been used, such as radioactive decay, atmospheric electromagnetic noise harvested from a radio tuned between stations, or intermixed timings of [[keystroke dynamics|keystrokes]].<ref name=RandomArticle_Phys.NYT2001/><ref name=RandomArticle.SS1998>{{cite magazine |magazine=Sun Server |title=Javatalk: Horseshoes, hand grenades and random numbers |author=Jonathan Knudson |date=January 1998 |pages=16–17}}</ref> The time investment needed to obtain these numbers leads to a compromise: using some of these physics readings as a seed for a pseudorandom number generator.
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