Quantum Minimal Learning Machine: A Fidelity-Based Approach to Error Mitigation
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866910045215653888 |
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| author | Lindner, Clemens Hämäläinen, Joonas Raasakka, Matti |
| author_facet | Lindner, Clemens Hämäläinen, Joonas Raasakka, Matti |
| contents | We introduce the concept of quantum minimal learning machine (QMLM), a supervised similarity-based learning algorithm. The algorithm is conceptually based on a classical machine learning model and adopted to work with quantum data. We will motivate the theory and run the model as an error mitigation method for various parameters. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_07532 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quantum Minimal Learning Machine: A Fidelity-Based Approach to Error Mitigation Lindner, Clemens Hämäläinen, Joonas Raasakka, Matti Quantum Physics We introduce the concept of quantum minimal learning machine (QMLM), a supervised similarity-based learning algorithm. The algorithm is conceptually based on a classical machine learning model and adopted to work with quantum data. We will motivate the theory and run the model as an error mitigation method for various parameters. |
| title | Quantum Minimal Learning Machine: A Fidelity-Based Approach to Error Mitigation |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2603.07532 |