Quantum Computing for Pattern Classification

It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning research using the example of pattern classification. We present a quantum pattern classification algorithm that draws on Trugenberger’s proposal for measuring the Hamming distance on a quantum computer [CA Trugenberger, Phys Rev Let 87, 2001] and discuss its advantages using handwritten digit recognition.