arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0708.3786astro-ph
收藏

局部型原始非高斯性的温度和极化CMB映射

Temperature and Polarization CMB Maps from Primordial non-Gaussianities of the Local Type

Michele Liguori, Amit Yadav, Frode K. Hansen, Eiichiro Komatsu, Sabino Matarrese, Benjamin Wandelt

摘要:

即将到来的普朗克实验将提供高灵敏度的偏振测量,这将使我们能够进一步收紧f_NL边界的温度数据。非高斯CMB图的蒙特卡罗模拟已被用作表征数据中的非高斯特征的基本工具,因为它们使我们能够校准任何统计估计值并了解系统学、前景和其他污染物的影响。我们描述了一种算法,以产生高角分辨率模拟的非高斯CMB地图的温度和偏振。我们考虑局部型的非高斯性,其中非高斯性的水平由无量纲参数f_NL定义。然后,我们应用温度和偏振快速立方统计最近开发的Yadav等人。一组非高斯温度和偏振模拟。我们比较我们的结果与基于Fisher矩阵分析的理论预期,测试估计的无偏性,并研究误差线对f_NL的依赖性。我们的所有结果与理论预测非常吻合,从而证实了模拟算法和快速立方温度和偏振估计的可靠性。

英文摘要:

The forthcoming Planck experiment will provide high sensitivity polarization measurements that will allow us to further tighten the f_NL bounds from the temperature data. Monte Carlo simulations of non-Gaussian CMB maps have been used as a fundamental tool to characterize non-Gaussian signatures in the data, as they allow us to calibrate any statistical estimators and understand the effect of systematics, foregrounds and other contaminants. We describe an algorithm to generate high-angular resolution simulations of non-Gaussian CMB maps in temperature and polarization. We consider non-Gaussianities of the local type, for which the level of non-Gaussianity is defined by the dimensionless parameter, f_NL. We then apply the temperature and polarization fast cubic statistics recently developed by Yadav et al. to a set of non-Gaussian temperature and polarization simulations. We compare our results to theoretical expectations based on a Fisher matrix analysis, test the unbiasedness of the estimator, and study the dependence of the error bars on f_NL. All our results are in very good agreement with theoretical predictions, thus confirming the reliability of both the simulation algorithm and the fast cubic temperature and polarization estimator.

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。

↑