莱曼-阿尔法森林全息术：从一维测量得到的三维预测
Lyman-$α$ forest holography: 3D predictions from 1D measurements
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中文总结 AI 辅助
本研究提出ForestFlow模拟器，将莱曼-阿尔法森林的一维与三维聚类分析结合，利用DESI数据得到三维聚类模型预测，验证了方法并揭示两种探测的互补约束能力。
中文摘要 AI 辅助
莱曼-阿尔法（Lyα）森林聚类的宇宙学分析，要么依赖于沿单个视线方向的一维关联，要么依赖于不同视线方向之间的三维关联。由于这些可观测量探测的是不同尺度上的物质分布，传统上它们是被独立分析的。本研究中，我们利用ForestFlow弥合这一差距，ForestFlow是一个基于一组宇宙学流体动力学模拟训练得到的模拟器，可提供从线性到非线性尺度的莱曼-阿尔法森林聚类的统一描述。该框架使我们能够确定与DESI一维流量功率谱（P₁D）兼容的三维聚类模型的范围。所得预测成功复现了DESI重子声学振荡（BAO）分析测得的大尺度聚类，并为非线性聚类提供了具有物理动机的先验，这些先验将用于一篇配套论文，该论文将呈现DESI DR2莱曼-阿尔法森林的全形状分析。我们利用大体积、高分辨率流体动力学模拟ACCEL-2验证了我们的方法，证明在所有考虑的尺度范围内都具有极好的一致性。最后，我们结合了P₁D和BAO分析对参数组合b_δσ₈和b_ηfσ₈的约束，发现这两种探测手段提供了相当的约束能力，同时表现出互补的参数简并性。我们的结果通过ForestFlow建立了一维和三维莱曼-阿尔法森林测量之间的直接联系，我们将这种方法称为莱曼-阿尔法全息术，其类比于从低维信息重建高维结构的过程。
英文摘要
Cosmological analyses of Lyman-$α$ forest clustering rely on either one-dimensional correlations along individual sightlines or three-dimensional correlations between different sightlines. Because these observables probe the matter distribution on very different scales, they have traditionally been analyzed independently. In this work, we bridge this gap using ForestFlow, an emulator trained on a suite of cosmological hydrodynamical simulations that provides a unified description of Lyman-$α$ forest clustering from linear to nonlinear scales. This framework enables us to determine the range of three-dimensional clustering models compatible with the DESI one-dimensional flux power spectrum ($P_{\rm 1D}$). The resulting predictions successfully reproduce the large-scale clustering measured by the DESI BAO analysis and provide physically motivated priors on nonlinear clustering that are used in a companion paper presenting the full-shape analysis of the DESI DR2 Lyman-$α$ forest. We validate our methodology using the large-volume, high-resolution hydrodynamical simulation ACCEL-2, demonstrating excellent agreement across the full range of scales considered. Finally, we combine constraints from the $P_{\rm 1D}$ and BAO analyses on the parameter combinations $b_δσ_8$ and $b_ηf σ_8$, finding that the two probes provide comparable constraining power while exhibiting complementary parameter degeneracies. Our results establish a direct connection between one- and three-dimensional Lyman-$α$ forest measurements through ForestFlow, an approach we term Lyman-$α$ holography by analogy with the reconstruction of higher-dimensional structure from lower-dimensional information.
