Complexity of Inverting the Euler Function

We present an algorithm to invert the Euler function $\phi(m)$. The algorithm, for a given $n \geq 1$, in polynomial time ``on average'', finds the set $\Psi(n)$ of all solutions $m$ to $\phi(m) = n$. In fact, in the worst case, $\Psi(n)$ is exponentially large, and cannot be computed in polynomial time. In the opposite direction, we show, under a widely accepted number theoretic conjecture, that there is a polynomial time reduction of the Partition Problem, an NP-complete problem, to the problem of deciding whether $\phi(m) = n$ has a solution for a small set of integers n. This shows that the problem of deciding whether a given finite set of integers S contains a totient is NP-complete. A totient is an integer n that lies in the image of the phi function; that is, an integer n for which there exists an integer m solving phi(m) = n. Finally, we establish close links between of inverting the Euler function and the integer factorization problem.