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# Chaos
In [mathematics](math.md) chaos is a phenomenon that makes it extremely difficult to predict, even approximately, the outcome of some process even if we completely know how the process works and what state it starts in. In more technical terms chaos is a property of a [nonlinear](nonlinear.md) [deterministic](determinism.md) [system](system.md) in which even a very small change in input creates a great change in the output, i.e. the system is very sensitive to [initial conditions](initial_condition.md). Chaos is a topic studied by the field called **chaos theory** and is important in all [science](science.md). In [computer science](compsci.md) it is important for example for the generation of [pseudorandom](pseudorandom.md) numbers or in [cryptography](cryptography.md). Every programmer should be familiar with the existence of chaotic behavior because in mathematics (programming) it emerges very often, it may pose a problem but, of course, it may be taken advantage of as well.
In [mathematics](math.md) chaos is a phenomenon that makes it extremely difficult to predict, even [approximately](approximation.md), the outcome of some process even if we completely know how the process works and what state it starts in. In more technical terms chaos is a property of a [nonlinear](nonlinear.md) [deterministic](determinism.md) [system](system.md) in which even a very small change in input creates a great change in the output, i.e. the system is very sensitive to [initial conditions](initial_condition.md). Chaos is a topic studied by the field called **chaos theory** and is important in all [science](science.md). In [computer science](compsci.md) it is important for example for the generation of [pseudorandom](pseudorandom.md) numbers or in [cryptography](cryptography.md). Every programmer should be familiar with the existence of chaotic behavior because in mathematics (programming) it emerges very often, it may pose a problem but, of course, it may be taken advantage of as well.
Perhaps the most important point is that a chaotic system is difficult to predict NOT because of [randomness](randomness.md), lack of information about it or even its incomprehensible complexity (many chaotic systems are defined extremely simply), but because of its inherent structure that greatly amplifies any slight nudge to the system and gives any such nudge a great significance. This may be caused by things such as [feedback loops](feedback_loop.md) and [domino effects](domino_effect.md). Generally we describe this behavior as so called **[butterfly effect](butterfly_effect.md)** -- we liken this to the fact that a butterfly flapping its wings somewhere in a forest can trigger a sequence of events that may lead to causing a tornado in a distant city a few days later.