# Magnitude and distribution of largest prime factor?

Erdos-Kac law state a typical number of magnitude $$n$$ has $$\log\log n$$ prime factors.

1. What is magnitude and distribution of largest prime factor of typical magnitude $$n$$ natural number?

2. What is magnitude and distribution of largest and second largest prime factor of typical magnitude $$n$$ natural number given than there is a prime factor $$p|n$$ of size $$n^{0.25\pm\epsilon}$$?

Assume $$\epsilon\in(0,0.25)$$ is fixed.

I am also interested in 1. and 2. for square-free scenario.

• I'm no number theorist nor analyst, but my back-of-the-envelope calculation suggests that as long as $\alpha \leq 1$ is not too small, the probability that all prime factors of $n$ are $\leq n^\alpha$ should be about $\alpha$. – Tim Campion Jun 17 at 2:03
• @TimCampion It might be a good heuristic. Mind elaborating? – Turbo Jun 17 at 2:04
• Assuming that the events $p \mid n$ are independent for different primes, we want to calculate ($p$ ranging over primes) $\prod_{n^\alpha \leq p \leq n} (1-1/p) = \exp(\sum_{n^\alpha \leq p \leq n} \log(1-1/p)) \approx \exp(\int_{n^\alpha}^n (dx/\log x) \log(1-1/x))$. Keeping only the first (!) term of the Taylor expansion for $\log(1-1/x)$, $\alpha$ is the result, as long as I haven't made an elementary calculus mistake (which I wouldn't discount!). Even if one accepts the integral approximation, the Taylor approximation may well be losing a $\log \alpha$ factor or something. – Tim Campion Jun 17 at 2:11
• What? No, there is no sense whatsoever in which this is a proof of anything. The independence assumption doesn't even literally make sense, since there's not really such a thing as "the probability that $n$ is prime". – Tim Campion Jun 17 at 2:44
• @TimCampion: That guess is very much off base. The chance that a number $n$ has all prime factors below $n^{1/u}$ is given by the Dickman-de Bruijn function $\rho(u)$, which for large $u$ is about $u^{-u(1+o(1))}$. Thus this is very different from $1/u$ which the naive heuristic would suggest. The same story holds for the distribution of lengths of cycles in a random permutation. Google "smooth numbers". – Lucia Jun 17 at 3:32