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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2512.21893 |
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| _version_ | 1866908732661694464 |
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| author | Aggarwal, Shruti Gupta, Trasha Agrawal, R. K. Indu, S. |
| author_facet | Aggarwal, Shruti Gupta, Trasha Agrawal, R. K. Indu, S. |
| contents | Quantum entanglement is a key resource in quantum computing and quantum information processing tasks. However, its quantification remains a major challenge since it cannot be directly extracted from physical observables. To address this issue, we study a few machine-learning based models to estimate the amount of entanglement in two-qubit as well as three-qubit systems. We use measurement outcomes as the input features and entanglement measures as the training labels. Our models predict entanglement without requiring the full state information. This demonstrates the potential of machine learning as an effcient and powerful tool for characterizing quantum entanglement |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_21893 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating Supervised Learning Approaches for Quantification of Quantum Entanglement Aggarwal, Shruti Gupta, Trasha Agrawal, R. K. Indu, S. Quantum Physics Quantum entanglement is a key resource in quantum computing and quantum information processing tasks. However, its quantification remains a major challenge since it cannot be directly extracted from physical observables. To address this issue, we study a few machine-learning based models to estimate the amount of entanglement in two-qubit as well as three-qubit systems. We use measurement outcomes as the input features and entanglement measures as the training labels. Our models predict entanglement without requiring the full state information. This demonstrates the potential of machine learning as an effcient and powerful tool for characterizing quantum entanglement |
| title | Evaluating Supervised Learning Approaches for Quantification of Quantum Entanglement |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2512.21893 |