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arXiv 0904.0789astro-ph.CO
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根据WMAP 5年低分辨率资料对CMB角功率谱的新估计

New estimates of the CMB angular power spectra from the WMAP 5 yrs low resolution data

A. Gruppuso, A. De Rosa, P. Cabella, F. Paci, F. Finelli, P. Natoli, G. de Gasperis, N. Mandolesi

摘要:

一个二次最大似然(QML)估计应用于WMAP 5年低分辨率地图计算CMB角功率谱在大尺度的温度和偏振。提供了六个角功率谱的估计值和误差条,并在可能的情况下与WMAP团队获得的结果进行了比较,没有发现任何不一致之处。还通过基于像素的似然码针对从$\ell =2$到10的所有六个功率谱的$C_{\ell}$计算条件似然切片。这两种代码都在单个矩阵中处理$(T,Q,U)$的协方差,而不采用任何近似。这两个代码的输入(前景简化图和相关协方差)由WMAP团队提供。似然切片的峰值总是与误差条内的QML估计一致,然而,当QML估计用作基准功率谱而不是最佳拟合理论功率谱时,会出现极好的一致性。通过对估计谱的条件似然的充分计算,发现温度四极杆$C_{\ell=2}^{TT}$值与WMAP 5年$Λ$ CDM最佳拟合值的距离小于$2 σ$。发现$BB$光谱与零一致,并提供了B模式的上限。发现奇偶校验奇信号$TB$和$EB$与零一致。

英文摘要:

A Quadratic Maximum Likelihood (QML) estimator is applied to the WMAP 5 year low resolution maps to compute the CMB angular power spectra at large scales for both temperature and polarization. Estimates and error bars for the six angular power spectra are provided and compared, when possible, to those obtained by the WMAP team, without finding any inconsistency. The conditional likelihood slices are also computed for the $C_{\ell}$ of all the six power spectra from $\ell =2$ to 10 through a pixel based likelihood code. Both the codes treat the covariance for $(T,Q,U)$ in a single matrix without employing any approximation. The inputs of both the codes (foreground reduced maps and related covariances) are provided by the WMAP team. The peaks of the likelihood slices are always consistent with the QML estimates within the error bars, however an excellent agreement occurs when the QML estimates are used as fiducial power spectrum instead of the best-fit theoretical power spectrum. By the full computation of the conditional likelihood on the estimated spectra, the value of the temperature quadrupole $C_{\ell=2}^{TT}$ is found to be less than $2 σ$ away from the WMAP 5 yrs $Λ$CDM best-fit value. The $BB$ spectrum is found well consistent with zero and upper limits on the B-modes are provided. The parity odd signals $TB$ and $EB$ are found consistent with zero.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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