Baryon Acoustic Oscillations (BAO) are considered to be a very robust standard ruler against various systematics. This premise has been tested against observational systematics, but not to the level required for the next generation of galaxy surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid. In this paper, we investigate the effect of observational systematics on the BAO measurement of the final sample of quasars from the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in order to prepare and hone a similar analysis for upcoming surveys. We employ catalogues with various treatments of imaging systematic effects using linear and neural network-based non-linear approaches and consider how the BAO measurement changes. We also test how the variations to the BAO fitting model respond to the observational systematics. As expected, we confirm that the BAO measurements obtained from the DR16 quasar sample are robust against imaging systematics well within the statistical error, while reporting slightly modified constraints that shift the line-of-sight BAO signal by less than 1.1 per cent. We use realistic simulations with similar redshift and angular distributions as the DR16 sample to conduct statistical tests for validating the pipeline, quantifying the significance of differences, and estimating the expected bias on the BAO scale in future high-precision data sets. Although we find a marginal impact for the eBOSS QSO data, the work presented here is of vital importance for constraining the nature of dark energy with the BAO feature in the new era of big data cosmology.

中文翻译：

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SDSS-IV 扩展重子振荡光谱调查类星体样本的聚类：测试重子声振荡测量的观测系统学

重子声学振荡 (BAO) 被认为是针对各种系统学的非常强大的标准标尺。这个前提已经针对观测系统学进行了测试，但还没有达到下一代星系调查所需的水平，例如暗能量光谱仪 (DESI) 和欧几里得。在本文中，我们研究了观测系统学对来自扩展的重子振荡光谱调查数据第 16 版的类星体最终样本的 BAO 测量的影响，以便为即将进行的调查准备和完善类似的分析。我们使用基于线性和神经网络的非线性方法对成像系统效应进行各种处理的目录，并考虑 BAO 测量如何变化。我们还测试了 BAO 拟合模型的变化如何响应观察系统学。正如预期的那样，我们确认从 DR16 类星体样本中获得的 BAO 测量结果在统计误差范围内对成像系统具有鲁棒性，同时报告了稍微修改的约束，使视线 BAO 信号偏移不到 1.1%。我们使用具有与 DR16 样本相似的红移和角度分布的真实模拟来进行统计测试，以验证管道、量化差异的显着性以及估计未来高精度数据集中 BAO 尺度的预期偏差。虽然我们发现对 eBOSS QSO 数据的影响很小，