从宇宙旋转功率重建检验宇称违反物理
Testing parity-violating physics from cosmic rotation power reconstruction
摘要：
我们研究宇称违反物理产生的宇宙旋转功率谱的重建，着眼于正在进行的和不久的将来的宇宙微波背景（CMB）实验，如BICEP阵列，CMBS 4，LiteBIRD和西蒙斯天文台。除了暴胀引力波和引力透镜之外，对CMB偏振的其他各种影响的测量为早期宇宙打开了新的窗口。其中之一是宇宙极化旋转的各向异性，它探测了弦论通常预测的陈-西蒙斯项。宇宙旋转的各向异性也是由原初磁性和标准模型外延框架产生的。宇宙旋转各向异性可以在CMB各向异性中重建为二次。然而，重建的宇宙旋转的功率是宇宙微波背景辐射四点相关，与宇宙旋转功率谱没有直接关系。理解四点相关中的所有贡献是提取宇宙旋转信号所必需的。假设由暴胀宇宙旋转模型激发的尺度不变旋转谱，我们采用模拟来量化对四点相关的每一个贡献，并发现（1）三谱的二次收缩增加了总信噪比，（2）与统计误差相比，来自透镜诱导的三谱的偏差是显著的，例如，LiteBIRD和CMBS 4类实验，（3）使用实现依赖估计量将统计误差降低了10%-20%，这取决于实验规范，（4）其他高阶贡献至少在不久的将来的实验中可以忽略不计。
英文摘要：
We study the reconstruction of the cosmic rotation power spectrum produced by parity-violating physics, with an eye to ongoing and near future cosmic microwave background (CMB) experiments such as BICEP Array, CMBS4, LiteBIRD and Simons Observatory. In addition to the inflationary gravitational waves and gravitational lensing, measurements of other various effects on CMB polarization open new window into the early Universe. One of these is anisotropies of the cosmic polarization rotation which probes the Chern-Simons term generally predicted by string theory. The anisotropies of the cosmic rotation are also generated by the primordial magnetism and in the Standard Model extention framework. The cosmic rotation anisotropies can be reconstructed as quadratic in CMB anisotropies. However, the power of the reconstructed cosmic rotation is a CMB four-point correlation and is not directly related to the cosmic-rotation power spectrum. Understanding all contributions in the four-point correlation is required to extract the cosmic rotation signal. Assuming a scale-invariant rotation spectrum motivated by the inflationary cosmic-rotation models, we employ simulation to quantify each contribution to the four-point correlation and find that (1) a secondary contraction of the trispectrum increases the total signal-to-noise, (2) a bias from the lensing-induced trispectrum is significant compared to the statistical errors in, e.g., LiteBIRD and CMBS4-like experiments, (3) the use of a realization-dependent estimator decreases the statistical errors by 10%-20%, depending on experimental specifications, and (4) other higher-order contributions are negligible at least for near future experiments.
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