TensorFlow Hydrodynamics Analysis for Ly-α Simulations

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-07-01 DOI:10.1016/j.ascom.2024.100858

J. Ding , B. Horowitz , Z. Lukić

引用次数: 0

Abstract

We introduce the Python program THALAS (TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations), which maps baryon fields (baryon density, temperature, and velocity) to Ly $α$ optical depth fields in both real space and redshift space. Unlike previous Ly $α$ codes, THALAS is fully differentiable, enabling a wide variety of potential applications for general analysis of hydrodynamical simulations and cosmological inference. To demonstrate THALAS’s capabilities, we apply it to the Ly $α$ forest inversion problem: given a Ly $α$ optical depth field, we reconstruct the corresponding real-space dark matter density field. Such applications are relevant to both cosmological and three-dimensional tomographic analyses of Lyman Alpha forest data.

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用于 Ly-α 模拟的 TensorFlow 流体动力学分析

我们介绍了 Python 程序 THALAS（TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations），它将重子场（重子密度、温度和速度）映射到实际空间和红移空间的 Lyα 光学深度场。与以前的Lyα代码不同，THALAS是完全可微分的，因此可以广泛应用于流体力学模拟的一般分析和宇宙学推断。为了证明THALAS的能力，我们将其应用于Lyα森林反演问题：给定一个Lyα光学深度场，我们重建相应的真实空间暗物质密度场。这种应用与莱曼阿尔法森林数据的宇宙学和三维层析分析都有关系。

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

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

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