A Case for Noisy Shallow Gate-based Circuits in Quantum Machine Learning

Patrick Selig, Niall Murphy, Ashwin Sundareswaran R, David Redmond,Simon Caton

2021 International Conference on Rebooting Computing (ICRC)(2021)

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摘要
There is increasing interest in the development of gate- based quantum circuits for the training of machine learning models. Yet, little is understood concerning the parameters of circuit design, and the effects of noise and other measurement errors on the performance of quantum machine learning models. In this paper, we explore the practical implications of key circuit design parameters (number o...
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关键词
Training,Circuit topology,Measurement errors,Machine learning algorithms,Design methodology,Qubit,Machine learning
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