发表机构
University of California, Berkeley; Lawrence Berkeley National Laboratory; Massachusetts Institute of Technology; Perimeter Institute for Theoretical Physics（加州大学伯克利分校; 劳伦斯伯克利国家实验室; 麻省理工学院; 理论物理前沿研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
我们首次将神经场级BAO重建（LiFT）应用于真实巡天数据，在DESI DR1亮红星系上相比标准重建将α_iso和α_AP误差改善5%-30%，等效品质因数提升1.2-2.0倍，验证了其作为巡天工具的可靠性。
AI 中文摘要
我们首次将神经场级重子声学振荡（BAO）重建方法应用于真实光谱巡天数据。我们开发了线性场Transformer（LiFT），这是一个三维视觉Transformer，其输入为观测到的星系场、标准重建结果以及一组编码局部视线方向、巡天覆盖范围和红移的上下文通道，并学习将标准重建结果校正至线性密度场。我们构建了一个前向建模流程，以生成与暗能量光谱仪器数据发布1（DESI DR1）亮红星系（LRG）样本相似的模拟光锥，并在此类模拟上训练LiFT。我们在保留的模拟数据上验证LiFT，并在采用不同引力求解器、暗物质晕查找器、晕占据分布（HOD）、宇宙学参数及光纤分配历史的额外模拟上，以及在使用畸变的距离-红移关系分析的模拟上进行了验证；最终，我们发现LiFT给出的无偏膨胀参数，其约束始终比标准重建更紧。将LiFT应用于DESI DR1亮红星系后，在LRG1、LRG2和LRG3分箱中，相对于DESI DR1标准重建分析，α_iso的误差分别改善了13%、24%和30%，α_AP的误差分别改善了5%、22%和30%；同时，我们基于DR1的中心值与DR1和DR2的结果保持一致。这相当于，若仅使用标准重建，品质因数（或有效巡天体积）分别提高了1.2倍、1.7倍和2.0倍。最终，这些结果确立了LiFT作为经过验证、可用于当前及未来星系巡天的现成工具。
英文摘要
We present the first application of neural field-level baryon-acoustic oscillation (BAO) reconstruction to real spectroscopic survey data. We develop Linear Field Transformer (LiFT), a 3D vision transformer that takes as input the observed galaxy field, its standard reconstruction, and a set of context channels encoding local line of sight, survey coverage, and redshift, and learns to correct standard reconstruction toward the linear density field. We construct a forward-modeling pipeline to produce mock lightcones similar to the DESI Data Release 1 (DR1) luminous red galaxy (LRG) sample, and train LiFT on these. We validate LiFT on held-out simulations, as well as on additional mocks which differ in gravity solver, halo finder, HOD, cosmology, and fiber-assignment history, as well as on mocks analyzed with a distorted distance-redshift relation; ultimately, we find unbiased dilation parameters with consistently tighter constraints than standard reconstruction. Applied to the DESI DR1 LRGs, LiFT improves errors on $α_{\rm iso}$ by 13%, 24%, and 30% and on $α_{\rm AP}$ by 5%, 22%, and 30% relative to the DESI DR1 standard reconstruction analysis in the LRG1, LRG2, and LRG3 bins respectively; meanwhile, our DR1 central values remain consistent with DR1 and DR2. This equates to a factor of 1.2, 1.7 and 2.0 increase in Figure of Merit (or effective survey volume) if one were to only use standard reconstruction. Ultimately, these results establish LiFT as a validated, survey-ready tool for current and upcoming galaxy surveys.
