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Surrogate modeling of the CLIC final-focus system using artificial neural networks
Journal of Instrumentation ( IF 1.3 ) Pub Date : 2021-05-12 , DOI: 10.1088/1748-0221/16/05/p05012
J. gren 1 , C. Gohil 1, 2 , D. Schulte 1
Affiliation  

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.



中文翻译:

使用人工神经网络对 CLIC 最终焦点系统进行代理建模

人工神经网络可用于创建替代模型,以替代计算成本高昂的模拟。在本文中,为紧凑型线性对撞机 (CLIC) 最终聚焦系统的一个子集创建了一个替代模型。通过对模拟数据进行训练,我们创建了一个模型,将六极偏移映射到光度和光束大小,从而取代了计算密集型跟踪和光束模拟。然后使用该模型优化随机游走程序的参数以进行六极对齐。

更新日期:2021-05-12
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