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Quantum Machine Learning

Quantum Physics 2018-05-14 v2 Strongly Correlated Electrons Machine Learning

Abstract

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce counter-intuitive patterns believed not to be efficiently produced by classical systems, it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement concrete quantum software that offers such advantages. Recent work has made clear that the hardware and software challenges are still considerable but has also opened paths towards solutions.

Keywords

Cite

@article{arxiv.1611.09347,
  title  = {Quantum Machine Learning},
  author = {Jacob Biamonte and Peter Wittek and Nicola Pancotti and Patrick Rebentrost and Nathan Wiebe and Seth Lloyd},
  journal= {arXiv preprint arXiv:1611.09347},
  year   = {2018}
}

Comments

24 pages, 2 figures

R2 v1 2026-06-22T17:07:07.739Z