I'm trying to prove that c2n = o((loglog n)n) (That's little-o) for any constant c. I understand that we can prove one function grows at a smaller rate than the other by taking the limit as n approaches infinity, and I can very easily pick some arbitrary integer value for c and show that indeed ((loglog n)n) grows at a faster rate. But how do I prove this to be true for any constant c?
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1This question appears to be off-topic because it is about math, not programming. Try math.stackexchange.com. – Barmar Sep 02 '14 at 00:21
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3This question appears to be off-topic because it is about CS theory, rather than programming. It might be a better fit on cs.stackexchange.com . – Jim Lewis Sep 02 '14 at 00:24
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You want to prove that for any choice of c, the value of
limn → ∞ (c2n / (log log n)n) = 0
Notice that for any choice of c that
limn → ∞ (c2n / (log log n)n)
= limn → ∞ (c2 / log log n)n
This limit is 0 because once log log n > c2, you're raising a value less than one to the power of n, which will quickly drop to zero.
Hope this helps!

templatetypedef
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To be pedantic, I think we just need to prove that the limit is less than 1 rather than equal to 0, although proving that it's equal to 0 has proven that it's less than 1. – wookie919 Sep 02 '14 at 01:02
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@wookie919 From what I recall, it's not sufficient to prove that the limit is less than one. For example, the limit of n / 2n as n tends to infinity is 1 / 2, but n != o(2n). – templatetypedef Sep 02 '14 at 01:06
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