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Quantum Machine Learning
Quantum memristors for neuromorphic quantum machine learning
arXiv
Authors: Lucas Lamata
Year
2024
Paper ID
56969
Status
Preprint
Abstract Read
~2 min
Abstract Words
70
Citations
N/A
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.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- Quantum machine learning may permit to realize more efficient machine learning calculations with near-term quantum devices.
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