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CMB LENSING POWER SPECTRUM BIASES FROM GALAXIES AND CLUSTERS USING HIGH-ANGULAR RESOLUTION TEMPERATURE MAPS

机译:使用高角分辨率温度映射的CMB从星系和团簇获得的力谱偏差

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The lensing power spectrum from cosmic microwave background (CMB) temperature maps will be measured with unprecedented precision with upcoming experiments, including upgrades to the Atacama Cosmology Telescope and the South Pole Telescope. Achieving significant improvements in cosmological parameter constraints, such as percent level errors on σ8 and an uncertainty on the total neutrino mass of ~50 meV, requires percent level measurements of the CMB lensing power. This necessitates tight control of systematic biases. We study several types of biases to the temperature-based lensing reconstruction signal from foreground sources such as radio and infrared galaxies and the thermal Sunyaev-Zel'dovich effect from galaxy clusters. These foregrounds bias the CMB lensing signal due to their non-Gaussian nature. Using simulations as well as some analytical models we find that these sources can substantially impact the measured signal if left untreated. However, these biases can be brought to the percent level if one masks galaxies with fluxes at 150?GHz above 1 mJy and galaxy clusters with masses above M vir = 1014 M ☉. To achieve such percent level bias, we find that only modes up to a maximum multipole of l max ~ 2500 should be included in the lensing reconstruction. We also discuss ways to minimize additional bias induced by such aggressive foreground masking by, for example, exploring a two-step masking and in-painting algorithm.
机译:通过即将进行的实验,包括升级阿塔卡马宇宙望远镜和南极望远镜,将以前所未有的精度测量来自宇宙微波背景(CMB)温度图的透镜功率谱。要实现宇宙学参数约束的显着改善,例如σ8的水平误差百分比以及〜50 meV的总中微子质量的不确定性,就需要测量CMB透镜屈光力的水平。这需要严格控制系统偏差。我们研究了来自前景源(如无线电和红外星系)的基于温度的镜头重建信号的几种类型的偏差,以及来自星系团的热Sunyaev-Zel'dovich效应。这些前景由于其非高斯性质而使CMB透镜信号产生偏差。使用仿真以及一些分析模型,我们发现,如果不进行处理,这些源会严重影响测量信号。但是,如果一个人以高于1 mJy的150?GHz的通量掩盖星系和质量大于M vir = 1014 M above的星系团,可以将这些偏差带到百分数水平。为了达到这样的百分比水平偏差,我们发现在镜头重建中仅应包括最大多极l max〜2500的模。我们还讨论了一些方法,例如,通过探索两步掩膜和画中算法,来最大限度地减少由这种积极的前景掩膜引起的额外偏差。

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