[论文解读] TORRCH: Tomographic reconstruction of the reionization of cosmic hydrogen with Ly$α$ emitters and non-Ly$α$-selected galaxies

Soumak Maitra, Girish S. Kulkarni+6 more|arXiv (Cornell University)|Jan 22, 2026

Galaxies: Formation, Evolution, Phenomena被引用 0

一句话总结

TORRCH trains a deterministic 3D U-Net to reconstruct the neutral-hydrogen fraction field during reionization from LAEs and non-Lyα-selected galaxies, validated on diverse mock surveys at z=7.14 (and z=6.6), recovering large-scale morphology and cross-correlations.

ABSTRACT

Tomographic reconstruction of reionization is a long-sought goal. It would move the field beyond global summary statistics, such as the volume-averaged ionised fraction, to direct, field-level constraints on the ionization topology. With this in mind, we present TORRCH (TOmographic Reconstruction of the Reionization of Cosmic Hydrogen), a deep-learning framework that reconstructs the neutral-hydrogen fraction field during the epoch of reionization from the spatial distributions of Ly$α$ emitters (LAEs) and non-Ly$α$-selected galaxies (NLSGs) at luminosity limits comparable to current surveys. Using hydrodynamical simulations post-processed with radiative transfer, we train a deterministic 3D U-Net on mock surveys spanning diverse reionization scenarios and predict the neutral-fraction field. We find that TORRCH recovers the large-scale ionization morphology from synthetic data comparable to current surveys with high fidelity, and reproduces both the one-point distribution and the 2D power spectrum of projected neutral fractions. The predicted galaxy-IGM cross-correlation is also captured well, including the expected small-scale anti-correlation and its decline towards zero at large separations. Reconstruction quality depends on tracer completeness, with deep joint LAE+NLSG samples yielding the most accurate morphology, while LAE-only selections retain bubble-scale topology but with reduced fidelity. Robustness tests show that the method is stable to variations in ionization conditions between training and test data, and to realistic redshift uncertainties. Our results suggest that galaxy-based tomography can potentially deliver reliable reionization maps across realistic survey redshift windows.

研究动机与目标

• 推动超越全球标量探针，获得EoR期间电离拓扑的场级约束。
• 开发一个多追踪体层层成像框架，将Lyα发射体与非Lyα筛选星系结合，绘制 x_HI(r)。
• 证明学习的3D U‑Net能够从现实的模拟数据中恢复大尺度的电离形态。
• 评估对离子化历史变化与红移不确定性的鲁棒性。
• 提供一个将星系基础成像与其他再电离探针结合的平台。

提出的方法

• 利用 Sherwood-Relics 水动力学模拟，并通过 aton-he 进行后处理辐射传输，生成多样的再电离场景。
• 用将暗晶质量与UV 光度联系起来的前向建模对LAEs进行填充，然后分配原位Lyα等效宽度并沿LOS Skewers计算CGM/IGM的透射率。
• 构建具有深度截断的观测LAE目录（LAE+NLSG 和 LAE-only 配置），以模拟大视场 surveys。
• 在模拟小体积上训练一个确定性3D U‑Net（无潜在瓶颈），将LAE/NLSG分布映射到 x_HI(r)。
• 通过场级比较以及一阶/二阶统计（包括与星系的交叉相关性）评估重建质量。

实验结果

研究问题

• RQ1 LAE与NLSG的空间分布是否能联合还原再电离时期的3D电离场？
• RQ2 重建保真度如何依赖追踪器的完备性（LAE+NLSG 与 LAE-only）？
• RQ3 recovered x_HI场对离子化历史变化和红移不确定性有多鲁棒？
• RQ4 方法在一点分布、二维投影功率谱以及星系–IGM 交叉相关性方面的再现程度如何？

主要发现

• TORRCH在与当前观测调查相当的综合数据上，能够高保真地恢复大尺度电离形态。
• 该方法能够再现x_HI的一点分布以及投影的中性分数的二维功率频谱。
• 预测的星系–IGM 交叉相关性被较好捕捉，包括小尺度的负相关及其在大距离处的衰减。
• 与LAE-only选择相比，深度耦合的LAE+NLSG样本可提升重建质量。
• 鲁棒性测试显示对训练集与测试集之间的不同离子化条件及现实的红移不确定性具有稳定性。
• 基于星系的成像有潜力在现实调查的红移窗口内提供可靠的再电离地图。