论文标题
使用人工神经网络对CLIC最终聚焦系统的替代建模
Surrogate Modeling of the CLIC Final-Focus System using Artificial Neural Networks
论文作者
论文摘要
人工神经网络可用于创建可以替代计算昂贵的模拟的替代模型。在本文中，为紧凑型线性对撞机（CLIC）最终对焦系统的子集创建了一个替代模型。通过对仿真数据进行培训，我们创建了一个模型，该模型将六重奏偏移到光度和梁尺寸，从而替换计算密集型跟踪和梁梁模拟。然后，该模型用于优化六极对齐的随机步行过程的参数。
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.
