  We consider whether trainable quantum unitaries can be used to discover
quantum speed-ups for classical problems. Using methods recently developed for
training quantum neural nets, we consider Simon's problem, for which there is a
known quantum algorithm which performs exponentially faster in the number of
bits, relative to the best known classical algorithm. We give the problem to a
randomly chosen but trainable unitary circuit, and find that the training
recovers Simon's algorithm as hoped.
