Production of Alternate Realizations of DESI Fiber Assignment for Unbiased Clustering Measurement in Data and Simulations

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.光谱大尺度结构分析的一项关键要求是，从各向同性靶星列表中遴选待观测星系时需完成校正。这类遴选通常受巡天所用硬件限制：硬件会对同时可观测的靶标施加角向约束，因此需开展多轮观测才能覆盖全部靶星。在斯隆数字巡天（Sloan Digital Sky Survey, SDSS）中，该问题仅表现为安装在光纤板上的物理光纤与定位塞之间的碰撞；而在暗能量光谱仪（Dark Energy Spectroscopic Instrument, DESI）中，还存在额外约束：控制单根光纤的机械定位装置存在有限巡天半径。此前已有多种近似方法被提出，用于校正这些效应导致的星系成团统计偏差，但这类方法在小尺度下通常失效。若要精准校正成团信号，需基于星系对被观测到的逆概率，对该类星系对赋予更高权重（Bianchi & Percival 2017）。本文详细阐述了该方法的实现流程，用于校正DESI巡天的观测不完备性。为计算所需的概率权重，我们需要生成多套DESI替代实现方案：在这些方案中，我们调整原本完全相同的靶星的相对优先级。这类方案以替代合并靶标账本（Alternate Merged Target Ledgers, AMTL）的形式存在——此类文件用于关联DESI的观测数据与靶星信息。本文还介绍了生成这些替代实现方案的方法，以及如何结合真实观测记录与硬件状态进行时间溯源，模拟在采用替代排序方式的情况下的巡天推进过程。此外，本文详述了该方法在DESI百分之一巡天（SV3）与DESI第一年观测数据中的首批应用，包含对数据流水线输出结果的评估、基于该方法与其他方法的巡天完备性估计，以及利用模拟星系星表对该方法开展的验证。