Learning Simon's quantum algorithm
Quantum Physics
2018-06-28 v1
Abstract
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.
Cite
@article{arxiv.1806.10448,
title = {Learning Simon's quantum algorithm},
author = {Kwok Ho Wan and Feiyang Liu and Oscar Dahlsten and M. S. Kim},
journal= {arXiv preprint arXiv:1806.10448},
year = {2018}
}