Tudor Alexandru Calafeteanu, Paula Gina Isar, Emil Ioan Sluşanschi
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引用次数: 0
摘要
超高能宇宙射线(UHECRs)是宇宙中普通物质中极为罕见的高能粒子,在到达地球大气层之前会飞行天文数字的距离。当原生宇宙射线与大气核相互作用时,就会产生次级基本粒子的级联大范围空气阵雨(EAS)。无线电探测器已被证明是重建 EAS 特性的可靠方法,如气雨的轴线、能量和最大值(Xmax)。这有助于理解基本的天体物理现象,如活动星系核和伽玛射线暴。与此同时,数据科学已成为 UHECR 研究中不可或缺的部分。通过将统计、计算和深度学习方法应用于真实世界和模拟无线电数据,研究人员可以提取见解并做出预测。我们介绍了一种卷积神经网络(CNN)架构,旨在将模拟的气雨事件分类为由质子或铁核产生。该分类的测试误差稳定在 10%,准确度和 F1 分数分别为 0.9 和 0.8。这些指标表明,基于皮埃尔-奥格天文台(包括无线电天线、水切伦科夫探测器和荧光望远镜)这一世界上最大的地球宇宙射线实验的探测器所能收集到的数据,对 UHECR 的核组成具有很强的预测能力。
Convolutional Neural Network Processing of Radio Emission for Nuclear Composition Classification of Ultra-High-Energy Cosmic Rays
Ultra-high-energy cosmic rays (UHECRs) are extremely rare energetic particles of ordinary matter in the Universe, traveling astronomical distances before reaching the Earth’s atmosphere. When primary cosmic rays interact with atmospheric nuclei, cascading extensive air showers (EASs) of secondary elementary particles are developed. Radio detectors have proven to be a reliable method for reconstructing the properties of EASs, such as the shower’s axis, its energy, and its maximum (Xmax). This aids in understanding fundamental astrophysical phenomena, like active galactic nuclei and gamma-ray bursts. Concurrently, data science has become indispensable in UHECR research. By applying statistical, computational, and deep learning methods to both real-world and simulated radio data, researchers can extract insights and make predictions. We introduce a convolutional neural network (CNN) architecture designed to classify simulated air shower events as either being generated by protons or by iron nuclei. The classification achieved a stable test error of 10%, with Accuracy and F1 scores of 0.9 and an MCC of 0.8. These metrics indicate strong prediction capability for UHECR’s nuclear composition, based on data that can be gathered by detectors at the world’s largest cosmic rays experiment on Earth, the Pierre Auger Observatory, which includes radio antennas, water Cherenkov detectors, and fluorescence telescopes.
UniversePhysics and Astronomy-General Physics and Astronomy
CiteScore
4.30
自引率
17.20%
发文量
562
审稿时长
24.38 days
期刊介绍:
Universe (ISSN 2218-1997) is an international peer-reviewed open access journal focused on fundamental principles in physics. It publishes reviews, research papers, communications, conference reports and short notes. Our aim is to encourage scientists to publish their research results in as much detail as possible. There is no restriction on the length of the papers.