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Machine Learning in Fast Beam Diagnositcs
In accelerator physics, detailed studies of beam often require disruptive measurement and take a long time to perform. This includes the measurement of the emittance where a quadruple scan is needed. In this report, a method using machine learning of fast emittance estimation is introduced. Using th...
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Lenguaje: | eng |
Publicado: |
2019
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Acceso en línea: | http://cds.cern.ch/record/2686696 |
_version_ | 1780963553609515008 |
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author | Ling, Jerry |
author_facet | Ling, Jerry |
author_sort | Ling, Jerry |
collection | CERN |
description | In accelerator physics, detailed studies of beam often require disruptive measurement and take a long time to perform. This includes the measurement of the emittance where a quadruple scan is needed. In this report, a method using machine learning of fast emittance estimation is introduced. Using the image of the beam and the machine settings of the experiment, one can achieve a single % error estimation of emittance across a large range. The study is conducted using simulation data from ASTRA. |
id | cern-2686696 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2019 |
record_format | invenio |
spelling | cern-26866962019-09-30T06:29:59Zhttp://cds.cern.ch/record/2686696engLing, JerryMachine Learning in Fast Beam DiagnositcsAccelerators and Storage RingsIn accelerator physics, detailed studies of beam often require disruptive measurement and take a long time to perform. This includes the measurement of the emittance where a quadruple scan is needed. In this report, a method using machine learning of fast emittance estimation is introduced. Using the image of the beam and the machine settings of the experiment, one can achieve a single % error estimation of emittance across a large range. The study is conducted using simulation data from ASTRA.CERN-STUDENTS-Note-2019-059oai:cds.cern.ch:26866962019-08-15 |
spellingShingle | Accelerators and Storage Rings Ling, Jerry Machine Learning in Fast Beam Diagnositcs |
title | Machine Learning in Fast Beam Diagnositcs |
title_full | Machine Learning in Fast Beam Diagnositcs |
title_fullStr | Machine Learning in Fast Beam Diagnositcs |
title_full_unstemmed | Machine Learning in Fast Beam Diagnositcs |
title_short | Machine Learning in Fast Beam Diagnositcs |
title_sort | machine learning in fast beam diagnositcs |
topic | Accelerators and Storage Rings |
url | http://cds.cern.ch/record/2686696 |
work_keys_str_mv | AT lingjerry machinelearninginfastbeamdiagnositcs |