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[论文解读] Validating the Galaxy and Quasar Catalog-Level Blinding Scheme for the DESI 2024 analysis

U. Andrade, J. Mena-Fernández|arXiv (Cornell University)|Apr 10, 2024
Astronomy and Astrophysical Research被引用 9
一句话总结

本文验证了面向 DESI DR1 的目录级盲化方案，聚焦于 BAO、RSD 和 PNG，结果表明盲化数据在分析时可保持不变的 BAO/RSD 选择，并且仍能鲁棒地解盲。

ABSTRACT

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks, as well as on data by applying a second blinding layer to perform a battery of sanity checks. We find that the blinding strategy alters the data vector in a controlled way such that the BAO and RSD analysis choices do not need any modification before and after unblinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.

研究动机与目标

  • 解决在使用 DESI DR1 进行精密宇宙学分析时的确认偏差风险。
  • 开发一种目录级盲化方案，在不改变角度位置的情况下扭曲 BAO、RSD 和 PNG 的观测量。
  • 在模拟数据和盲化数据上验证盲化方法，以确保数据处理流程的完整性。
  • 证明解盲不需要对 BAO 和 RSD 的分析选择进行修改。

提出的方法

  • 盲化在目录层面进行，通过平移红移以模拟 BAO 的 AP 样式效应，并通过扰动视线方向位置以模拟 RSD，同时使用一个移位的宇宙学模型与一个标准参考模型并存。
  • 通过对大尺度应用尺度相关的偏置权重来模仿 f_NL 效应，实现 PNG 盲化。
  • 使用两种宇宙学模型：一个 fiducial 参考和一个盲化移位，将观测到的红移转换为盲化距离。
  • 盲化参数被约束，使 alpha_perp、alpha_parallel 和 f 的平移在相关红shift 范围内保持在指定极限内（BAO 膨胀为 3%，生长率为 10%）。
  • 使用 Landy-Szalay 和 FKP 估计量分别计算二维点统计量（相关函数和功率谱），并通过标准的 BAO 与 ShapeFit 压缩方法进行分析。
  • 推断将 BAO 与 ShapeFit 方法结合起来，以提取如距离尺度、增长率和带通形状等宇宙学信息。
Figure 1 : Parameter space of interest for $(w_{0},w_{a})$ under the DESI DR1 blinding scheme. The white region represents the parameter region that allows for changes in $\alpha_{\parallel}$ and $\alpha_{\perp}$ of less than 3% with respect to a fiducial chosen value of 1 in the redshift range $0.4
Figure 1 : Parameter space of interest for $(w_{0},w_{a})$ under the DESI DR1 blinding scheme. The white region represents the parameter region that allows for changes in $\alpha_{\parallel}$ and $\alpha_{\perp}$ of less than 3% with respect to a fiducial chosen value of 1 in the redshift range $0.4

实验结果

研究问题

  • RQ1目录级盲化在解盲后不需要变更分析选择的前提下，能否保持对 BAO、RSD 和 PNG 分析的完整性？
  • RQ2将 DESI DR1 盲化方案应用于模拟数据和盲化数据时是否稳健？
  • RQ3观测量中盲化引入的平移是否保持在受控且物理可解释的参数空间区域内？
  • RQ4该盲化策略是否为最终的 DESI DR1 分析提供可靠的解盲条件？

主要发现

  • 盲化策略以与基础宇宙学相容的受控方式改变数据向量。
  • BAO 和 RSD 的分析选择在解盲前后无需修改。
  • 在模拟数据和盲化数据上的验证表明盲化程序具有鲁棒性。
  • 该方法为 DESI DR1 的解盲分析以及未来对 DESI 及其他调查的盲分析奠定了基础。
Figure 2 : Comparison of blinded and unblinded mocks for multipoles $\ell=0$ , $\ell=2$ , and $\ell=4$ , for the correlation function (left column) and power spectrum (right column). The curves show the mean is across 25 AbacusSummit catalogs which are blinded with the same blinding parameters.
Figure 2 : Comparison of blinded and unblinded mocks for multipoles $\ell=0$ , $\ell=2$ , and $\ell=4$ , for the correlation function (left column) and power spectrum (right column). The curves show the mean is across 25 AbacusSummit catalogs which are blinded with the same blinding parameters.

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