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Surrogate modeling of the CLIC final-focus system using artificial neural networks

Abstract:
Artificial neural networks can be used for creating surrogate models that can replace computationally expensive simulations. In this paper, a surrogate model was created for a subset of the Compact Linear Collider (CLIC) final-focus system. By training on simulation data, we created a model that maps sextupole offsets to luminosity and beam sizes, thus replacing computationally intensive tracking and beam-beam simulations. This model was then used for optimizing the parameters of a random walk procedure for sextupole alignment.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1088/1748-0221/16/05/P05012

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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
ORCID:
0000-0002-0888-1207


Publisher:
IOP Publishing
Journal:
Journal of Instrumentation More from this journal
Volume:
16
Issue:
5
Article number:
P05012
Publication date:
2021-05-12
Acceptance date:
2021-02-26
DOI:
EISSN:
1748-0221


Language:
English
Keywords:
Pubs id:
1184352
Local pid:
pubs:1184352
Deposit date:
2023-12-17

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