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An Application of the Global ILC Algorithm over Large Angular Scales to Estimate the CMB Posterior Using Gibbs Sampling
The Astrophysical Journal ( IF 4.9 ) Pub Date : 2020-06-30 , DOI: 10.3847/1538-4357/ab964e
Vipin Sudevan , Rajib Saha

In this work, we formalize a new technique to investigate joint posterior density of Cosmic Microwave Background (CMB) signal and its theoretical angular power spectrum given the observed data, using the global internal-linear-combination (ILC) method first proposed by Sudevan & Saha (2017). We implement the method on low resolution CMB maps observed by WMAP and Planck satellite missions, using Gibbs sampling, assuming that the detector noise is negligible on large angular scales of the sky. The main products of our analysis are best fit CMB cleaned map and its theoretical angular power spectrum along with their error estimates. We validate the methodology by performing Monte Carlo simulations that includes realistic foreground models and noise levels consistent with WMAP and Planck observations. Our method has an unique advantage that the posterior density is obtained without any need to explicitly model foreground components. Secondly, the power spectrum results with the error estimates can be directly used for cosmological parameter estimations.

中文翻译:

全局 ILC 算法在大角度尺度上使用 Gibbs 采样估计 CMB 后验的应用

在这项工作中,我们正式确定了一种新技术,用于研究宇宙微波背景 (CMB) 信号的联合后验密度及其给定观测数据的理论角功率谱,使用由 Sudevan & 首次提出的全局内部线性组合 (ILC) 方法。萨哈 (2017)。我们在 WMAP 和普朗克卫星任务观测到的低分辨率 CMB 地图上实施该方法,使用吉布斯采样,假设探测器噪声在天空的大角尺度上可以忽略不计。我们分析的主要产品是最佳拟合 CMB 清洁图及其理论角功率谱及其误差估计。我们通过执行蒙特卡罗模拟来验证该方法,其中包括与 WMAP 和普朗克观测一致的真实前景模型和噪声水平。我们的方法有一个独特的优势,即无需对前景成分进行显式建模即可获得后验密度。其次,带有误差估计的功率谱结果可以直接用于宇宙学参数估计。
更新日期:2020-06-30
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