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Given a 64-bit hash function that takes arbitrary inputs, what is the probability that feeding 10 million inputs into the hash function will outputs 10 million unique outputs. I've came up with this: $$ \begin{aligned} P(10,000,000)&=1\times\left(\frac{2^{64}-1}{2^{64}}\right)\times\left(\frac{2^{64}-2}{2^{64}}\right)\times\cdots\times\left(\frac{2^{64}-9,999,999}{2^{64}}\right)\\ &=\frac{2^{64}!}{(2^{64})^{10,000,000}(2^{64}-10,000,000)!} \end{aligned} $$ However the numbers are too big for a standard calculator to handle, what are the better ways to calculate this for a arbitrary $n$ other than 10 million? Please explain how they work.

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  • $\begingroup$ $10,000,000$ is so small compared to $2^{64}$ that I think you can assume that the probability is 1. You run into issues when at the order of the square root of $2^{64} = 2^{32} \approx 1,000,000,000 >> 10,000,000$. Think the birthday paradox. $\endgroup$ – stuart stevenson Feb 1 '18 at 10:32
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Wikipedia's birthday problem article gives various approximations for the probability of no collisions (better at the top, simpler at the bottom)

  • $\exp\left(-\frac{n(n-1)}{2d}\right)$
  • $\exp\left(-\frac{n^2}{2d}\right)$
  • $1-\frac{n^2}{2d}$

Here $n=10^7$ and $d = 2^{64}$ and all of these are about $0.9999972895$

By comparison, the more familiar case of $n=23$ and $d=365$ would give approximations of $0.5000,$ $0.4845$ and $0.2753$ when the true value should be about $0.4927$

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