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arXiv 2303.09098astro-ph.CO
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基于机器学习的$N$体模拟中暗物质晕结构形成分析

Analysis of Dark Matter Halo Structure Formation in $N$-body Simulations with Machine Learning

Jazhiel Chacón, Isidro Gómez-Vargas, Ricardo Menchaca Méndez, José Alberto Vázquez

AI总结:

本研究利用$N$-body模拟数据训练机器学习算法,实现暗物质粒子晕分类与晕质量函数重构,发现随机森林和神经网络表现最优,且无需大量训练数据即可获得良好拟合效果。

摘要:

初始条件中物质密度场的性质对当今观测到的宇宙大尺度结构特征具有决定性影响。这些性质需通过$N$-body模拟开展研究,该模拟是分析高密度坍缩区域形成暗物质晕的必要手段。本文利用$N$-body模拟的信息训练机器学习算法,以推断两项性质:一是暗物质粒子的晕归属分类,结合可追溯至初始条件的物质密度场特征实现晕形成预测;二是通过计算晕质量函数(Halo Mass Function, HMF)研究暗物质晕形成,该函数给出了满足给定阈值的暗物质晕的数密度。我们将物质密度场的初始条件映射为暗物质晕结构的分类标签,同时通过理论方法及训练得到的算法,计算并重构了模拟的晕质量函数。我们测试了多种机器学习技术,发现随机森林(Random Forest)和神经网络(Neural Networks)在宇宙学模拟中对暗物质粒子的分类表现更优。研究还表明,重构HMF无需使用大量数据训练算法,所得拟合函数对模拟结果和理论结果均能实现极佳的拟合效果。

英文摘要:

The properties of the matter density field in the initial conditions have a decisive impact on the features of the large-scale structure of the Universe as observed today. These need to be studied via $N$-body simulations, which are imperative to analyze high density collapsed regions into dark matter halos. In this paper, we train Machine Learning algorithms with information from N -body simulations to infer two properties: dark matter particle halo classification that leads to halo formation prediction with the characteristics of the matter density field traced back to the initial conditions, and dark matter halo formation by calculating the Halo Mass Function (HMF), which offers the number density of dark matter halos with a given threshold. We map the initial conditions of the matter density field into classification labels of dark matter halo structures. The Halo Mass Function of the simulations is calculated and reconstructed with theoretical methods as well as our trained algorithms. We test several Machine Learning techniques where we could find that the Random Forest and Neural Networks proved to be the better performing tools to classify dark matter particles in cosmological simulations. We also show that that it is not compulsory to use a high amount of data to train the algorithms in order to reconstruct the HMF, giving us a very good fitting function for both simulation and theoretical results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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