论文标题

用当前和将来的数据测试电子模式极化中的CMB异常

Testing CMB Anomalies in E-mode Polarization with Current and Future Data

论文作者

Shi, Rui, Marriage, Tobias A., Appel, John W., Bennett, Charles L., Chuss, David T., Cleary, Joseph, Eimer, Joseph, Dahal, Sumit, Datta, Rahul, Espinoza, Francisco, Li, Yunyang, Miller, Nathan J., Núñez, Carolina, Padilla, Ivan L., Petroff, Matthew A., Valle, Deniz A. N., Wollack, Edward J., Xu, Zhilei

论文摘要

在本文中,我们探讨了宇宙微波背景(CMB)极化(E模式)数据的功能,以证实CMB温度数据中的四个潜在异常:缺乏较大的角度相关性,四极杆和八倍元(Q-O)的比对,并占用点对率高,并且是半明确的,并且是半明确的。我们使用具有三个实验的噪声代表的CMB模拟:Planck卫星,宇宙学大尺度测量师(类)和Litebird卫星 - 测试当前和将来的数据如何限制异常。我们发现温度和电子模式估计器之间的相关系数$ρ$小于$ 0.1 $,除了点 - 准则不对称($ρ= 0.17 $ for COSMIC-VARIANCE限制模拟),确认E-MODES对与温度数据的疾病有很大程度上独立于温度数据。与Planck组件分离的CMB数据(SMICA)相比,假定的LiteBird调查将通过$ \ sim 3 $的因素来减少电子模式异常估计量的错误,而半球性功率不对称和点 - 范式不对称,而$ \ sim 26 $对于缺乏大型相关性。由于巨大的宇宙差异,Q-O对齐的改进并不明显,但是我们发现固定估计值值的能力将通过因子$ \ gtrsim100 $提高。班级的改进与这些有关。

In this paper, we explore the power of the cosmic microwave background (CMB) polarization (E-mode) data to corroborate four potential anomalies in CMB temperature data: the lack of large angular-scale correlations, the alignment of the quadrupole and octupole (Q-O), the point-parity asymmetry, and the hemispherical power asymmetry. We use CMB simulations with noise representative of three experiments -- the Planck satellite, the Cosmology Large Angular Scale Surveyor (CLASS), and the LiteBIRD satellite -- to test how current and future data constrain the anomalies. We find the correlation coefficients $ρ$ between temperature and E-mode estimators to be less than $0.1$, except for the point-parity asymmetry ($ρ=0.17$ for cosmic-variance-limited simulations), confirming that E-modes provide a check on the anomalies that is largely independent of temperature data. Compared to Planck component-separated CMB data (SMICA), the putative LiteBIRD survey would reduce errors on E-mode anomaly estimators by factors of $\sim 3$ for hemispherical power asymmetry and point-parity asymmetry, and by $\sim 26$ for lack of large-scale correlation. The improvement in Q-O alignment is not obvious due to large cosmic variance, but we found the ability to pin down the estimator value will be improved by a factor $\gtrsim100$. Improvements with CLASS are intermediate to these.

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