Abstract

Imaging atmospheric Cherenkov telescopes are used to record images of extensive area showers caused by high-energy particles colliding with the upper atmosphere. The images are analyzed to determine events’ physical parameters, such as the type and the energy of the primary particles. The distributions of some of the physical parameters can be used as well, for example, to determine the properties of a gamma ray source. The key problem of any experiment is the calibration of experimental data. For this purpose, Monte Carlo simulated data with known values of the physical parameters are used. The main disadvantage of this method is its extremely high requirements for computing resources and the large amount of time spent on modelling. In this paper, we use an alternative approach: Cherenkov telescope images are simulated with conditional variational autoencoders. We compare the characteristics of both the individual images and their Hillas parameter distributions with those of the images generated by the Monte Carlo method.

中文翻译：

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使用条件变分自动编码器模拟 IACT 中的 EAS 图像

摘要

大气成像切伦科夫望远镜用于记录高能粒子与高层大气碰撞引起的大面积阵雨的图像。分析图像以确定事件的物理参数，例如初级粒子的类型和能量。例如，一些物理参数的分布也可用于确定伽马射线源的属性。任何实验的关键问题都是实验数据的校准。为此，使用具有已知物理参数值的蒙特卡罗模拟数据。该方法的主要缺点是对计算资源要求极高，建模需要花费大量时间。在本文中，我们使用另一种方法：用条件变分自动编码器模拟切伦科夫望远镜图像。我们将各个图像的特征及其 Hillas 参数分布与蒙特卡罗方法生成的图像的特征及其 Hillas 参数分布进行了比较。