Quantum Embedding Search for Quantum Machine Learning

Quantum Embedding Search for Quantum Machine Learning

This paper introduces an automated search algorithm (QES, pronounced as “quest”), which derives optimal design of entangling layout for supervised quantum machine learning. First, we establish the connection between the structures of entanglement using CNOT gates and the repres...

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Bibliographic Details
Main Authors: Nam Nguyen, Kwang-Cheng Chen
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Ansatz optimization
quantum embeddings
quantum machine learning
quantum logic gates
quantum neural network
quantum computing
Online Access:https://ieeexplore.ieee.org/document/9757160/

Internet

https://ieeexplore.ieee.org/document/9757160/

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