arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 0912.2728astro-ph.CO
收藏

原始能量谱的特征?频率论分析

Features in the primordial power spectrum? A frequentist analysis

Jan Hamann, Arman Shafieloo, Tarun Souradeep

摘要:

原始功率谱中的特征被认为是WMAP卫星测量的温度各向异性角功率谱中毛刺的解释。然而,这些小故障也可能是噪声或宇宙方差的伪影。我们使用最佳拟合幂律谱和去卷积原始谱之间的有效Δ卡方面积作为数据“特征性”的度量,进行了完整的蒙特卡罗分析,以解决恢复的特征有多重要的问题。我们发现,在26%的模拟数据集的重建频谱产生更大的改善的可能性比实际观察到的数据。虽然不能明确排除这种分析的功能,和可能性仍然是简单的理论模型,预测一些观察到的功能可能经得起严格的统计测试,我们的研究结果表明,WMAP数据与无特征的幂律原始光谱的假设是一致的。

英文摘要:

Features in the primordial power spectrum have been suggested as an explanation for glitches in the angular power spectrum of temperature anisotropies measured by the WMAP satellite. However, these glitches might just as well be artifacts of noise or cosmic variance. Using the effective Delta chi^2 between the best-fit power-law spectrum and a deconvolved primordial spectrum as a measure of "featureness" of the data, we perform a full Monte-Carlo analysis to address the question of how significant the recovered features are. We find that in 26% of the simulated data sets the reconstructed spectrum yields a greater improvement in the likelihood than for the actually observed data. While features cannot be categorically ruled out by this analysis, and the possibility remains that simple theoretical models which predict some of the observed features might stand up to rigorous statistical testing, our results suggest that WMAP data are consistent with the assumption of a featureless power-law primordial spectrum.

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。

↑