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Quantum Machine Learning
Entaglement-Based Quantum Mean Estimator Circuit
arXiv
Authors: Amanuel Tamirat
Year
2019
Paper ID
14451
Status
Preprint
Abstract Read
~2 min
Abstract Words
87
Citations
N/A
Abstract
This paper proposes a quantum circuit for computing the mean value from a given set of quantum states. The circuit consults a Quantum Random Access Memory to get the values of the set, and by using superposition, interference and entanglement phenomena, it can estimate the mean value in mathcal{O}\(frac{1}εlog{Nd}\) complexity. The proposed quantum mean-estimator circuit has been simulated on the IBM Q Experience and the results suggest that the proposed quantum circuit can have the potential to enhance many mean-based machine learning algorithms.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2019 reference point for readers tracking recent quantum research.
- This paper proposes a quantum circuit for computing the mean value from a given set of quantum states.
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