Quantum k-nearest neighbor machine learning algorithm

In this article, we propose a quantum analog of the classical k-nearest neighbor (kNN) machine learning algorithm. Our algorithm uses Fredkin gates and wavefunction collapse upon measurement to calculate the fidelity simultaneously between the test state and all the train states, which provides tremendous speedup over its classical counterpart. The quantum kNN algorithm presented here is capable of dealing with completely unknown test states encoded in quantum systems.