论文标题
利用互相关和基于线性协方差的过滤，以在线性尺度上进行线性地图重建
Leveraging cross-correlations and linear covariance-based filtering for line-intensity map reconstructions at linear scales
论文作者
论文摘要
我们探讨了基于线性协方差（LCB）过滤到线强度映射（LIM）信号重建的可能应用。 LCB过滤器最初是为重建集成的Sachs-Wolfe效应的重建，是一个最佳的地图估计器，它通过利用外部相关数据来扩展简单的Wiener滤波器。鉴于可检测到的强烈lim-galaxy或lim-lim交叉功率谱，我们显示了在仿真[c ii] lim调查的模拟中恢复高红移，大规模的线强度波动 - 即使在存在明亮的闯入者发射的情况下，也可以恢复。具有足够的星系丰度或低LIM调查噪声，LCB重建和真实信号之间的归一化互相关在大的，线性的共同量表上达到70-90％，对应于$ k \ sim0.1 $ MPC $^{ - 1} $。这表明可能在天体物理或宇宙学环境中使用此类信号重建，这些背景需要识别线发射峰和空隙的位置，尽管在较小的尺度上存在明显的缺点。 LCB过滤器在模拟的LIM环境中的成功应用突显了互相关对与LIM和其他大规模结构调查的恢复原始和电离的高红移宇宙的重要性的重要性。
We explore the possible application of linear covariance-based (LCB) filtering to line-intensity mapping (LIM) signal reconstructions. Originally introduced for reconstruction of the integrated Sachs-Wolfe effect in the cosmic microwave background, the LCB filter is an optimal map estimator that extends the simple Wiener filter by leveraging external correlated data. Given a detectable strong LIM-galaxy or LIM-LIM cross power spectrum, we show recovery of high-redshift, large-scale line-intensity fluctuations -- even in the presence of bright interloper emission -- in simulations of a futuristic [C II] LIM survey as well as simulated future iterations of the CO Mapping Array Project (COMAP). With sufficient galaxy abundances or low LIM survey noise, normalised cross-correlation between the LCB reconstruction and the true signal reaches 70-90% on large, linear comoving scales corresponding to $k\sim0.1$ Mpc$^{-1}$. This suggests the possible use of such signal reconstructions in astrophysical or cosmological contexts that require identifying the locations of line emissivity peaks and voids, although clear shortcomings exist on smaller scales. The successful application of the LCB filter in simulated LIM contexts highlights the importance of cross-correlations to studies of the reionising and reionised high-redshift universe with LIM and other large-scale structure surveys.
