Emulating baryons from dark matter simulations

IF 12.9 1区物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS

Nature Astronomy Pub Date : 2025-03-18 DOI:10.1038/s41550-025-02520-y

Lindsay Oldham

引用次数: 0

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从暗物质模拟中模拟重子

暗物质和重子物质在宇宙时间中的相互作用是复杂的，高度非线性的，是对多个天体物理过程的关键探测。宇宙流体动力学模拟推动了我们对这种动态的理解，但它们在计算上很昂贵，并且在体积和分辨率之间存在权衡。Mauro Bernardini和他的同事提出了一种新的深度学习框架，通过模拟暗物质分布预测高分辨率的气体特性，以很小的计算成本来解决这些困难。该框架EMBER-2使用条件生成对抗网络实现了这种映射，并通过调制具有全局红移信息的基本卷积核有效地结合了时间依赖性。当对来自现实环境反馈（FIRE）项目的红移z = 6的模拟数据进行训练时，该软件能够准确地模拟二维总气体表面密度、径向速度和温度，以及基于暗物质投影表面密度和径向速度的H i表面密度。模拟的全局分布将质量保持在5%（总气体）和10% （H i）之间，最大的误差是由于密度最高的区域缺乏训练信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Astronomy Physics and Astronomy-Astronomy and Astrophysics

CiteScore

19.50

自引率

2.80%

发文量

252

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