标题： TensorFlow 流体力学分析用于 Ly-$α$模拟 显示英文标题

标题： TensorFlow Hydrodynamics Analysis for Ly-$α$ Simulations

摘要： 我们引入了Python程序THALAS（TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations），该程序将重子场（重子密度、温度和速度）映射到真实空间和红移空间中的Ly$\alpha$光学深度场。 与之前的Ly$\alpha$代码不同，THALAS是完全可微的，使得其能够广泛应用于流体动力学模拟和宇宙学推断的一般分析。 为了展示THALAS的功能，我们将它应用于Ly$\alpha$森林反问题：给定一个Ly$\alpha$光学深度场，我们重建相应的真实空间暗物质密度场。 此类应用对于Lyman Alpha森林数据的宇宙学和三维层析分析都具有相关性。 显示英文摘要

摘要： We introduce the Python program THALAS (TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations), which maps baryon fields (baryon density, temperature, and velocity) to Ly$\alpha$ optical depth fields in both real space and redshift space. Unlike previous Ly$\alpha$ 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$\alpha$ forest inversion problem: given a Ly$\alpha$ 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.