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Optics corrections using machine learning in the LHC
Optics corrections in the LHC are based on a response matrix between available correctors and observables. Supervised learning has been applied to optics correction in the LHC demonstrating promising results on simulations and demonstrating the ability to reach acceptably low $\beta$-beating. A comp...
| Autores principales: | , , , |
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| Lenguaje: | eng |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.18429/JACoW-IPAC2019-THPRB077 http://cds.cern.ch/record/2690544 |