Quantum coupon collector

We study how efficiently a k-element set S ? [n] can be learned from a uniform superposition |Si of its elements. One can think of |Si = Pi?S |ii/p|S| as the quantum version of a uniformly random sample over S, as in the classical analysis of the “coupon collector problem.” We show that if k is close to n, then we can learn S using asymptotically fewer quantum samples than random samples. In particular, if there are n - k = O(1) missing elements then O(k) copies of |Si suffice, in contrast to the T(k log k