基于COMAP的CO光度函数的联合功率谱和体素强度分布预测
Joint power spectrum and voxel intensity distribution forecast on the CO luminosity function with COMAP
摘要：
我们开发了一个框架，联合约束的CO光度函数的基础上的功率谱（PS）和体素强度分布（VID），并将其应用到COMAP，CO强度映射实验的模拟。该贝叶斯框架是基于马尔可夫链蒙特卡罗（MCMC）采样器耦合到高斯似然与联合PS + VID协方差矩阵计算从大量的基准模拟，并重新校准与少量的模拟每个MCMC步骤。这些模拟基于来自快速峰值补丁模拟的暗物质晕，结合Li等人的$L_\text{CO}(M_\text{halo})$模型。我们发现，约束CO光度函数的相对功率取决于感兴趣的光度范围。特别地，VID在小和大光度下都更敏感，而PS在中间光度下更敏感。联合分析优于单独使用任何一个可观察数据。当对范围在$L_\text{CO} = 10^4-10^7L_\odot$和COMAP第2阶段的10个以上宇宙学实现之间的CO光度进行平均时，与联合分析（PS + VID）相比，PS和VID的不确定性（以dex计）分别大58%和30%。这种方法一般适用于任何其他随机场，具有复杂的可能性，只要一个快速的模拟过程是可用的。
英文摘要：
We develop a framework for joint constraints on the CO luminosity function based on power spectra (PS) and voxel intensity distributions (VID), and apply this to simulations of COMAP, a CO intensity mapping experiment. This Bayesian framework is based on a Markov chain Monte Carlo (MCMC) sampler coupled to a Gaussian likelihood with a joint PS + VID covariance matrix computed from a large number of fiducial simulations, and re-calibrated with a small number of simulations per MCMC step. The simulations are based on dark matter halos from fast peak patch simulations combined with the $L_\text{CO}(M_\text{halo})$ model of Li et al. (2016). We find that the relative power to constrain the CO luminosity function depends on the luminosity range of interest. In particular, the VID is more sensitive at both small and large luminosities, while the PS is more sensitive at intermediate luminosities. The joint analysis is superior to using either observable separately. When averaging over CO luminosities ranging between $L_\text{CO} = 10^4-10^7L_\odot$, and over 10 cosmological realizations of COMAP Phase 2, the uncertainties (in dex) are larger by 58 % and 30 % for the PS and VID, respectively, when compared to the joint analysis (PS + VID). This method is generally applicable to any other random field, with a complicated likelihood, as long a fast simulation procedure is available.
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