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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.

Original publication

DOI

10.1088/1748-0221/16/05/P05012

Type

Journal article

Journal

Journal of Instrumentation

Publication Date

01/05/2021

Volume

16