泊松数据空间畸变宇宙信号的贝叶斯分析
Bayesian analysis of spatially distorted cosmic signals from Poissonian data
摘要：
从星系计数重建物质密度场是当前文献中经常讨论的问题。两个主要的误差来源是星系计数产生的散粒噪声和对星系正确位置的不充分认识，这是由特殊的速度和红移测量的不确定性造成的。在这里，我们解决重建问题的泊松采样对数正态密度场的速度失真的贝叶斯方式通过最大后验方法。我们测试我们的算法在一个1D玩具的情况下，发现显着的改善相比，简单的数据反演。特别是，我们解决了以下问题：光度红移，编码掩模系统中的扩展源的映射，从红移空间星系分布的实空间重建和不同点扩散函数的数据的组合分析。
英文摘要：
Reconstructing the matter density field from galaxy counts is a problem frequently addressed in current literature. Two main sources of error are shot noise from galaxy counts and insufficient knowledge of the correct galaxy position caused by peculiar velocities and redshift measurement uncertainty. Here we address the reconstruction problem of a Poissonian sampled log-normal density field with velocity distortions in a Bayesian way via a maximum a posteriory method. We test our algorithm on a 1D toy case and find significant improvement compared to simple data inversion. In particular, we address the following problems: photometric redshifts, mapping of extended sources in coded mask systems, real space reconstruction from redshift space galaxy distribution and combined analysis of data with different point spread functions.
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。
