Opposites Attract: Understanding O Notation in Math & CS

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The discussion clarifies the use of the O notation in mathematics and computer science, highlighting that the limit approaches differ: mathematics uses limits as x approaches 0, while computer science uses limits as x approaches infinity. Despite seeming contradictory, both interpretations are valid within their contexts. The key is to specify the limit when using O notation, as this determines the outcome. This distinction resolves the confusion regarding the application of O notation in different fields. Understanding these nuances is essential for accurate mathematical and computational analysis.
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Hi, I noticed in mathematics the O symbol is used in the following way:

A term T is in O(x^p), if lim x->0 T/x^p=c, for a constant c.

While in computer science the O symbol is used is this way:

A term T is in O(x^p), if lim x->∞ T/x^p is a constant.

What gives, these two notations seem to be the complete opposite of each other?
 
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The O symbol is valid in both cases. It is up to you to define what the x limit is.
 
mathman said:
The O symbol is valid in both cases. It is up to you to define what the x limit is.

But don't they contradict each other?

For example, in the first case x^7 is in O(x^5), but in the second case it is not.
 
No, they are just two distinct cases of a general concept. We should aways say "f(x)= O(g(x)) as x-> a and specify a. They are using two different values of a and so getting two different results.
 
HallsofIvy said:
No, they are just two distinct cases of a general concept. We should aways say "f(x)= O(g(x)) as x-> a and specify a. They are using two different values of a and so getting two different results.

Aha, thanks!
 
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