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Quantum memristors for neuromorphic quantum machine learning

Quantum Physics 2024-12-30 v1 Neural and Evolutionary Computing

Abstract

Quantum machine learning may permit to realize more efficient machine learning calculations with near-term quantum devices. Among the diverse quantum machine learning paradigms which are currently being considered, quantum memristors are promising as a way of combining, in the same quantum hardware, a unitary evolution with the nonlinearity provided by the measurement and feedforward. Thus, an efficient way of deploying neuromorphic quantum computing for quantum machine learning may be enabled.

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Cite

@article{arxiv.2412.18979,
  title  = {Quantum memristors for neuromorphic quantum machine learning},
  author = {Lucas Lamata},
  journal= {arXiv preprint arXiv:2412.18979},
  year   = {2024}
}

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R2 v1 2026-06-28T20:48:51.878Z