Quantum machine learning
<p >"<b>Quantum machine learning</b> is an emerging interdisciplinary research area at the intersection of <a href="https://en.wikipedia.org/wiki/Quantum_physics" class="mw-redirect" title="Quantum physics">quantum physics</a> and <a href="https://en.wikipedia.org/wiki/Machine_learning" title="Machine learning">machine learning</a>.<sup id="cite_ref-1" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-1">[1]</a></sup><sup id="cite_ref-2" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-2">[2]</a></sup><sup id="cite_ref-3" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-3">[3]</a></sup><sup id="cite_ref-4" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-4">[4]</a></sup> One can distinguish four different ways of merging the two parent disciplines.<sup id="cite_ref-AimeurEtAl_2006_5-0" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-AimeurEtAl_2006-5">[5]</a></sup><sup id="cite_ref-DunjkoTaylorBriegel_6-0" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-DunjkoTaylorBriegel-6">[6]</a></sup> Quantum machine learning algorithms can use the advantages of <a href="https://en.wikipedia.org/wiki/Quantum_computing" title="Quantum computing">quantum computation</a> in order to improve classical methods of machine learning, for example by developing efficient implementations of expensive classical algorithms on a <a href="https://en.wikipedia.org/wiki/Quantum_computer" class="mw-redirect" title="Quantum computer">quantum computer</a>.<sup id="cite_ref-Nathan_Wiebe_2014_7-0" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-Nathan_Wiebe_2014-7">[7]</a></sup><sup id="cite_ref-8" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-8">[8]</a></sup><sup id="cite_ref-9" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-9">[9]</a></sup> 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.<sup id="cite_ref-10" class="reference"><a href="https://en.wikipedia.org/wiki/Quantum_machine_learning#cite_note-10">[10]</a>"</sup>
<sup id="cite_ref-10" class="reference">source:: <a href="https://en.wikipedia.org/wiki/Quantum_machine_learning">https://en.wikipedia.org/wiki/Quantum_machine_learning</a></sup></p>