用于未来光谱巡天的样本方差抵消方法
Sample Variance Cancellation for Future Spectroscopic Surveys
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中文总结 AI 辅助
该研究针对高红移LAE光谱巡天中辐射转移导致的角依赖偏差，提出样本方差抵消策略，利用同红移无修正角依赖的示踪剂，可识别并量化该效应的类型、形式及幅度。
中文摘要 AI 辅助
高红移光谱星系巡天将成为下一代大尺度结构宇宙学的科学核心。高红移恒星形成的莱曼α发射体（LAE）的成团信号，对获取高红移下结构增长和红移空间畸变的约束至关重要。莱曼α光子的复杂辐射转移（RT）会改变由这些星系构建的过密场所遵循的对称群，因此观测到的LAE大尺度成团可能具有与线性理论显著不同的角依赖，这可能会对宇宙学参数的推断产生偏差。虽然这种效应已在模拟中被观测到，但其在自然界中的幅度和具体形式仍不明确。在受限的线性高斯模型框架下，我们概述了一种程序，用于在假设观测者获得包含此类效应的LAE数据的场景中，确定因未知RT或更一般的未建模角效应导致的大尺度上角依赖变化的类型和幅度。我们表明，若存在另一种无修正角依赖的示踪剂可与同红移的LAE进行交叉相关（例如莱曼断裂星系），则对于规模适中的高红移巡天，可快速识别：1）辐射转移的非平凡角函数形式的存在（通过条件场级实现）；2）该函数形式（通过我们推导的最优滤波器）；3）其幅度的数值及不确定性（通过标准二次估计器的改进）。因此，此类样本方差抵消策略为解决未知天体物理或系统角成团依赖（包括RT带来的效应）提供了一种统计解决方案。
英文摘要
High-redshift spectroscopic galaxy surveys will be the scientific engines of the next generation of large-scale structure cosmology. The clustering signal of high redshift, star-forming Lyman-$α$ emitters (LAEs) will be of key importance for obtaining high-redshift constraints on the growth of structure and redshift-space distortions. The complex radiative transfer (RT) of Lyman-$α$ photons alters the symmetry group respected by the overdensity field constructed from these galaxies, and so the observed large-scale clustering of LAEs may have an angular dependence that differs significantly from that of linear theory, possibly biasing inference of cosmological parameters. While such an effect has been seen in simulations, its amplitude in nature and its detailed form remains unclear. In the restricted context of a linear, Gaussian model, we outline a procedure for pinning down the type and amplitude of such changes in angular dependence on large scales due to unknown RT or a more general unmodeled angular effect in the hypothetical scenario in which an observer is presented with LAE data containing such an effect. We show that if a second tracer without the modified angular dependence is available for cross correlation with the LAEs at the same redshifts (e.g., Lyman-break galaxies), then, with a high redshift survey of modest size, it is possible to rapidly identify: 1) the presence of a nontrivial angular functional form of radiative transfer (by a conditional field-level realization), 2) the functional form itself (with an optimal filter that we derive), and 3) the value of its amplitude with an uncertainty (via an adaptation of the standard quadratic estimator). Such sample-variance-cancellation strategies therefore provide a statistical solution to unknown astrophysical or systematic angular clustering dependence, including from RT.
