论文标题

分子气体丰度测量的偏见和宇宙差异

Biases and Cosmic Variance in Molecular Gas Abundance Measurements

论文作者

Keenan, Ryan P., Marrone, Daniel P., Keating, Garrett K.

论文摘要

最近的深毫米波调查试图通过CO发射线的盲检测来测量一氧化碳(CO)光度函数和平均分子气体密度。虽然宇宙恒星的形成率密度现在在数百个Arcmin $^2 $或更多的场中受到限制,但分子天然气研究仅限于$ \ le50 $ arcmin $^2 $。这些小领域会导致重大偏见,这些偏见尚未在发布的结果中考虑到。为了量化这些偏见,我们将CO亮度分配给宇宙学模拟中的光晕,以对一系列田间大小进行模拟观察。我们发现字段$ \ Lessim 10 $ arcmin $^2 $更改光度函数的恢复形状,从而导致明亮对象数量的低估。我们的模型表明,当前的调查足够敏感,可以检测到高红移时大约一半宇宙分子气体密度的来源。但是,气体密度测量中的不确定性很大,宇宙方差可能会使这些调查中声称的不确定性增加一倍。结果,以高置信度检测分子气体中的红移进化所需的场大小可能大于比当前调查所实现的数量级。射击功率强度映射测量值对泊松方差特别敏感,需要更大的区域来限制气体密度或其演变。我们为直接检测和强度映射调查均提供了简单的处方,以使总CO发射与调查区域和红移的函数近似不确定性。

Recent deep millimeter-wave surveys attempt to measure the carbon monoxide (CO) luminosity function and mean molecular gas density through blind detections of CO emission lines. While the cosmic star formation rate density is now constrained in fields hundreds of arcmin$^2$ or more, molecular gas studies have been limited to $\le50$ arcmin$^2$. These small fields result in significant biases that have not been accounted for in published results. To quantify these biases, we assign CO luminosities to halos in cosmological simulations to produce mock observations for a range of field sizes. We find that fields $\lesssim 10$ arcmin$^2$ alter the recovered shape of the luminosity function, causing underestimates of the number of bright objects. Our models suggest that current surveys are sensitive enough to detect sources responsible for approximately half of the cosmic molecular gas density at high redshift. However, uncertainties in the gas density measurement are large, and cosmic variance may double the uncertainty claimed in these surveys. As a result, the field size needed to detect redshift evolution in the molecular gas at high confidence may be more than an order of magnitude larger than what current surveys have achieved. Shot power intensity mapping measurements are particularly sensitive to Poisson variance and require yet larger areas to constrain the gas density or its evolution. We provide a simple prescription for approximating uncertainty in total CO emission as a function of survey area and redshift, for both direct detection and intensity mapping surveys.

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