Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems
In this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily in...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | Nuclear Fusion |
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| Online Access: | https://doi.org/10.1088/1741-4326/ad9ab5 |
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| _version_ | 1841558596725243904 |
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| author | E. Öztürk R. Akers S. Pamela P. Peers A. Ghosh The MAST Team |
| author_facet | E. Öztürk R. Akers S. Pamela P. Peers A. Ghosh The MAST Team |
| author_sort | E. Öztürk |
| collection | DOAJ |
| description | In this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily incorporate them into a non-linear optimisation framework. The efficiency of our method enables not only estimation of a physically plausible image of plasma, but also recovery of the neutral Deuterium distribution from imaging and midplane measurements alone. We demonstrate our method with three different levels of complexity showing first that a poloidal neutrals density distribution can be recovered from imaging alone, second that the distributions of neutral Deuterium, electron density and electron temperature can be recovered jointly, and finally, that this can be done in the presence of realistic imaging systems that incorporate sensor cropping and quantisation. |
| format | Article |
| id | doaj-art-a2c398b785ed412190d7ca85b446731d |
| institution | Kabale University |
| issn | 0029-5515 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Nuclear Fusion |
| spelling | doaj-art-a2c398b785ed412190d7ca85b446731d2025-01-06T08:46:51ZengIOP PublishingNuclear Fusion0029-55152025-01-0165202602010.1088/1741-4326/ad9ab5Inverse rendering of fusion plasmas: inferring plasma composition from imaging systemsE. Öztürk0https://orcid.org/0000-0002-4143-8725R. Akers1S. Pamela2P. Peers3A. Ghosh4The MAST Team5Department of Computing, Imperial College , Prince Consort Road, London SW7 2BZ, United Kingdom of Great Britain and Northern IrelandCulham Centre for Fusion Energy, Culham Science Centre , Abingdon OX14 3EB, United Kingdom of Great Britain and Northern IrelandCulham Centre for Fusion Energy, Culham Science Centre , Abingdon OX14 3EB, United Kingdom of Great Britain and Northern IrelandComputer Science Department, College of William & Mary , Williamsburg, VA 23187, United States of AmericaDepartment of Computing, Imperial College , Prince Consort Road, London SW7 2BZ, United Kingdom of Great Britain and Northern IrelandCulham Centre for Fusion Energy, Culham Science Centre , Abingdon OX14 3EB, United Kingdom of Great Britain and Northern IrelandIn this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily incorporate them into a non-linear optimisation framework. The efficiency of our method enables not only estimation of a physically plausible image of plasma, but also recovery of the neutral Deuterium distribution from imaging and midplane measurements alone. We demonstrate our method with three different levels of complexity showing first that a poloidal neutrals density distribution can be recovered from imaging alone, second that the distributions of neutral Deuterium, electron density and electron temperature can be recovered jointly, and finally, that this can be done in the presence of realistic imaging systems that incorporate sensor cropping and quantisation.https://doi.org/10.1088/1741-4326/ad9ab5inverse renderingpath tracingplasma reconstruction |
| spellingShingle | E. Öztürk R. Akers S. Pamela P. Peers A. Ghosh The MAST Team Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems Nuclear Fusion inverse rendering path tracing plasma reconstruction |
| title | Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems |
| title_full | Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems |
| title_fullStr | Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems |
| title_full_unstemmed | Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems |
| title_short | Inverse rendering of fusion plasmas: inferring plasma composition from imaging systems |
| title_sort | inverse rendering of fusion plasmas inferring plasma composition from imaging systems |
| topic | inverse rendering path tracing plasma reconstruction |
| url | https://doi.org/10.1088/1741-4326/ad9ab5 |
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