Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics
We propose a novel tomographic method, nonlinear Gaussian process tomography (nonlinear GPT), that uses the Laplace approximation to impose constraints on non-negative physical quantities, such as the emissivity in plasma optical diagnostics. While positive-valued posteriors have previously been int...
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| Format: | Article |
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IOP Publishing
2025-01-01
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| Series: | Machine Learning: Science and Technology |
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| Online Access: | https://doi.org/10.1088/2632-2153/adbbae |
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| author | Kenji Ueda Masaki Nishiura |
| author_facet | Kenji Ueda Masaki Nishiura |
| author_sort | Kenji Ueda |
| collection | DOAJ |
| description | We propose a novel tomographic method, nonlinear Gaussian process tomography (nonlinear GPT), that uses the Laplace approximation to impose constraints on non-negative physical quantities, such as the emissivity in plasma optical diagnostics. While positive-valued posteriors have previously been introduced through sampling-based approaches in the original GPT method, our alternative approach implements a logarithmic Gaussian process (log-GP) for faster computation and more natural enforcement of non-negativity. The effectiveness of the proposed log-GP tomography is demonstrated through a case study using the Ring Trap 1 device, where log-GPT outperforms existing methods, standard GPT, and the minimum Fisher information methods in terms of reconstruction accuracy. The results highlight the effectiveness of nonlinear GPT for imposing physical constraints in applications to an inverse problem. |
| format | Article |
| id | doaj-art-c52f5c401ae044f99bcaf2d3d1a3cc9a |
| institution | DOAJ |
| issn | 2632-2153 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Machine Learning: Science and Technology |
| spelling | doaj-art-c52f5c401ae044f99bcaf2d3d1a3cc9a2025-08-20T02:57:53ZengIOP PublishingMachine Learning: Science and Technology2632-21532025-01-016101506110.1088/2632-2153/adbbaeNonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnosticsKenji Ueda0https://orcid.org/0000-0002-6479-049XMasaki Nishiura1https://orcid.org/0000-0002-2752-3333National Institute for Fusion Science , Gifu 509-5292, JapanNational Institute for Fusion Science , Gifu 509-5292, Japan; Graduate School of Frontier Sciences, The University of Tokyo , Chiba 277-8561, JapanWe propose a novel tomographic method, nonlinear Gaussian process tomography (nonlinear GPT), that uses the Laplace approximation to impose constraints on non-negative physical quantities, such as the emissivity in plasma optical diagnostics. While positive-valued posteriors have previously been introduced through sampling-based approaches in the original GPT method, our alternative approach implements a logarithmic Gaussian process (log-GP) for faster computation and more natural enforcement of non-negativity. The effectiveness of the proposed log-GP tomography is demonstrated through a case study using the Ring Trap 1 device, where log-GPT outperforms existing methods, standard GPT, and the minimum Fisher information methods in terms of reconstruction accuracy. The results highlight the effectiveness of nonlinear GPT for imposing physical constraints in applications to an inverse problem.https://doi.org/10.1088/2632-2153/adbbaetomographyplasma diagnosticsGaussian process |
| spellingShingle | Kenji Ueda Masaki Nishiura Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics Machine Learning: Science and Technology tomography plasma diagnostics Gaussian process |
| title | Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics |
| title_full | Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics |
| title_fullStr | Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics |
| title_full_unstemmed | Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics |
| title_short | Nonlinear Gaussian process tomography with imposed non-negativity constraints on physical quantities for plasma diagnostics |
| title_sort | nonlinear gaussian process tomography with imposed non negativity constraints on physical quantities for plasma diagnostics |
| topic | tomography plasma diagnostics Gaussian process |
| url | https://doi.org/10.1088/2632-2153/adbbae |
| work_keys_str_mv | AT kenjiueda nonlineargaussianprocesstomographywithimposednonnegativityconstraintsonphysicalquantitiesforplasmadiagnostics AT masakinishiura nonlineargaussianprocesstomographywithimposednonnegativityconstraintsonphysicalquantitiesforplasmadiagnostics |