Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers
Linac driven free electron lasers (FELs) operating in the x-ray region require a high brightness electron beam in order to reach saturation within a reasonable distance in the undulator train or to enable sophisticated seeding schemes using external lasers. The beam dynamics optimization is usually...
| Main Authors: | , , |
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| פורמט: | Journal article |
| שפה: | English |
| יצא לאור: |
2012
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| _version_ | 1826277776588537856 |
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| author | Bartolini, R Apollonio, M Martin, I |
| author_facet | Bartolini, R Apollonio, M Martin, I |
| author_sort | Bartolini, R |
| collection | OXFORD |
| description | Linac driven free electron lasers (FELs) operating in the x-ray region require a high brightness electron beam in order to reach saturation within a reasonable distance in the undulator train or to enable sophisticated seeding schemes using external lasers. The beam dynamics optimization is usually a time consuming process in which many parameters of the accelerator and the compression system have to be controlled simultaneously. The requirements on the electron beam quality may also vary significantly with the particular application. For example, the beam dynamics optimization strategy for self-amplified spontaneous emission operation and seeded operation are rather different: seeded operation requires a more careful control of the beam uniformity over a relatively large portion of the longitudinal current distribution of the electron bunch and is therefore more challenging from an accelerator physics point of view. Multiobjective genetic algorithms are particularly well suited when the optimization of many parameters is targeting several objectives simultaneously, often with conflicting requirements. In this paper we propose a novel optimization strategy based on a combination of multiobjective optimization with a fast computation of the FEL performance. The application to the proposed UK's New Light Source is reported and the benefits of this method are highlighted. © 2012 American Physical Society. |
| first_indexed | 2024-03-06T23:34:00Z |
| format | Journal article |
| id | oxford-uuid:6d06cf7e-508f-4bdd-a808-f3167e3b29e6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:34:00Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:6d06cf7e-508f-4bdd-a808-f3167e3b29e62022-03-26T19:15:00ZMultiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasersJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:6d06cf7e-508f-4bdd-a808-f3167e3b29e6EnglishSymplectic Elements at Oxford2012Bartolini, RApollonio, MMartin, ILinac driven free electron lasers (FELs) operating in the x-ray region require a high brightness electron beam in order to reach saturation within a reasonable distance in the undulator train or to enable sophisticated seeding schemes using external lasers. The beam dynamics optimization is usually a time consuming process in which many parameters of the accelerator and the compression system have to be controlled simultaneously. The requirements on the electron beam quality may also vary significantly with the particular application. For example, the beam dynamics optimization strategy for self-amplified spontaneous emission operation and seeded operation are rather different: seeded operation requires a more careful control of the beam uniformity over a relatively large portion of the longitudinal current distribution of the electron bunch and is therefore more challenging from an accelerator physics point of view. Multiobjective genetic algorithms are particularly well suited when the optimization of many parameters is targeting several objectives simultaneously, often with conflicting requirements. In this paper we propose a novel optimization strategy based on a combination of multiobjective optimization with a fast computation of the FEL performance. The application to the proposed UK's New Light Source is reported and the benefits of this method are highlighted. © 2012 American Physical Society. |
| spellingShingle | Bartolini, R Apollonio, M Martin, I Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title | Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title_full | Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title_fullStr | Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title_full_unstemmed | Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title_short | Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| title_sort | multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers |
| work_keys_str_mv | AT bartolinir multiobjectivegeneticalgorithmoptimizationofthebeamdynamicsinlinacdriversforfreeelectronlasers AT apolloniom multiobjectivegeneticalgorithmoptimizationofthebeamdynamicsinlinacdriversforfreeelectronlasers AT martini multiobjectivegeneticalgorithmoptimizationofthebeamdynamicsinlinacdriversforfreeelectronlasers |