Nanodiamond quantum thermometry assisted with machine learning
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866913787422965760 |
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| author | Yamamoto, Kouki Ogawa, Kensuke Tsukamoto, Moeta Ashida, Yuto Sasaki, Kento Kobayashi, Kensuke |
| author_facet | Yamamoto, Kouki Ogawa, Kensuke Tsukamoto, Moeta Ashida, Yuto Sasaki, Kento Kobayashi, Kensuke |
| contents | Nanodiamonds (NDs) are quantum sensors that enable local temperature measurements, taking advantage of their small size. Though the model based analysis methods have been used for ND quantum thermometry, their accuracy has yet to be thoroughly investigated. Here, we apply model-free machine learning with the Gaussian process regression (GPR) to ND quantum thermometry and compare its capabilities with the existing methods. We prove that GPR provides more robust results than them, even for a small number of data points and regardless of the data acquisition methods. This study extends the range of applications of ND quantum thermometry with machine learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_07582 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nanodiamond quantum thermometry assisted with machine learning Yamamoto, Kouki Ogawa, Kensuke Tsukamoto, Moeta Ashida, Yuto Sasaki, Kento Kobayashi, Kensuke Quantum Physics Applied Physics Nanodiamonds (NDs) are quantum sensors that enable local temperature measurements, taking advantage of their small size. Though the model based analysis methods have been used for ND quantum thermometry, their accuracy has yet to be thoroughly investigated. Here, we apply model-free machine learning with the Gaussian process regression (GPR) to ND quantum thermometry and compare its capabilities with the existing methods. We prove that GPR provides more robust results than them, even for a small number of data points and regardless of the data acquisition methods. This study extends the range of applications of ND quantum thermometry with machine learning. |
| title | Nanodiamond quantum thermometry assisted with machine learning |
| topic | Quantum Physics Applied Physics |
| url | https://arxiv.org/abs/2504.07582 |