Entanglement detection with artificial neural networks
Abstract Quantum 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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-28745-3 |
| _version_ | 1811175893065793536 |
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| author | Naema Asif Uman Khalid Awais Khan Trung Q. Duong Hyundong Shin |
| author_facet | Naema Asif Uman Khalid Awais Khan Trung Q. Duong Hyundong Shin |
| author_sort | Naema Asif |
| collection | DOAJ |
| description | Abstract Quantum 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. |
| first_indexed | 2024-04-10T19:43:21Z |
| format | Article |
| id | doaj.art-a8b5f88e281647a792b91ecaa6f8526e |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-10T19:43:21Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-a8b5f88e281647a792b91ecaa6f8526e2023-01-29T12:11:23ZengNature PortfolioScientific Reports2045-23222023-01-011311810.1038/s41598-023-28745-3Entanglement detection with artificial neural networksNaema Asif0Uman Khalid1Awais Khan2Trung Q. Duong3Hyundong Shin4Department of Electronics and Information Convergence Engineering, Kyung Hee UniversityDepartment of Electronics and Information Convergence Engineering, Kyung Hee UniversityDepartment of Electronics and Information Convergence Engineering, Kyung Hee UniversitySchool of Electronics, Electrical Engineering and Computer Science, Queen’s UniversityDepartment of Electronics and Information Convergence Engineering, Kyung Hee UniversityAbstract Quantum 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.https://doi.org/10.1038/s41598-023-28745-3 |
| spellingShingle | Naema Asif Uman Khalid Awais Khan Trung Q. Duong Hyundong Shin Entanglement detection with artificial neural networks Scientific Reports |
| title | Entanglement detection with artificial neural networks |
| title_full | Entanglement detection with artificial neural networks |
| title_fullStr | Entanglement detection with artificial neural networks |
| title_full_unstemmed | Entanglement detection with artificial neural networks |
| title_short | Entanglement detection with artificial neural networks |
| title_sort | entanglement detection with artificial neural networks |
| url | https://doi.org/10.1038/s41598-023-28745-3 |
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