Author:
Asif Naema,Khalid Uman,Khan Awais,Duong Trung Q.,Shin Hyundong
Abstract
AbstractQuantum entanglement is one of the essential resources involved in quantum information processing tasks. However, its detection for usage remains a challenge. The Bell-type inequality for relative entropy of coherence serves as an entanglement witness for pure entangled states. However, it does not perform reliably for mixed entangled states. This paper constructs a classifier by employing the relationship between coherence and entanglement for supervised machine learning methods. This method encodes multiple Bell-type inequalities for the relative entropy of coherence into an artificial neural network to detect the entangled and separable states in a quantum dataset.
Funder
National Research Foundation of Korea
Institute for Information & Communications Technology Planning and Evaluation, South Korea
Publisher
Springer Science and Business Media LLC
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