Quantum machine learning

Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning. One can distinguish four different ways of merging the two parent disciplines. Quantum machine learning algorithms can use the advantages of quantum computation in order to improve classical methods of machine learning, for example by developing efficient implementations of expensive classical algorithms on a quantum computer. On the other hand, one can apply classical methods of machine learning to analyse quantum systems. Most generally, one can consider situations wherein both the learning device and the system under study are fully quantum.

A related branch of research explores methodological and structural similarities between certain physical systems and learning systems, in particular neural networks, which has revealed, for example, that certain mathematical and numerical techniques from quantum physics carry over to classical deep learning.