Quantum learning algorithms for quantum measurements
Quantum Physics
2011-08-31 v2
Abstract
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information.
Cite
@article{arxiv.1103.0480,
title = {Quantum learning algorithms for quantum measurements},
author = {Alessandro Bisio and Giacomo Mauro D'Ariano and Paolo Perinotti and Michal Sedlak},
journal= {arXiv preprint arXiv:1103.0480},
year = {2011}
}
Comments
13 pages, 2 figures