广义可见度ILC：低红移宇宙中干涉式HI强度映射的新前景缓解策略
Generalised Visibility ILC: a new foreground mitigation strategy for interferometric HI intensity mapping in the low-redshift Universe
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- Instituto de Física de Cantabria (CSIC-Universidad de Cantabria)（坎塔布里亚物理研究所）
- Dpto. de Física Moderna, Universidad de Cantabria（坎塔布里亚大学现代物理系）
- Jodrell Bank Centre for Astrophysics, Department of Physics and Astronomy, The University of Manchester（曼彻斯特大学天体物理学乔德雷尔银行中心）
- State Key Laboratory of Radio Astronomy and Technology, Shanghai Astronomical Observatory, CAS（中国科学院上海天文台射电天文与技术国家重点实验室）
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中文总结 AI 辅助
针对低红移HI强度映射，提出广义可见度内部线性组合（GVILC）方法，结合PCA与多维ILC在可见度空间抑制前景，优于仅前景规避，可恢复傅里叶空间信息。
中文摘要 AI 辅助
HI强度映射是大尺度物质分布以及基础天体物理和宇宙学的强大探针。然而，其应用受到将微弱的中性氢（HI）信号与更明亮的前景发射分离这一挑战的限制。我们提出了一种在可见度空间中用于低红移HI强度映射的新非参数前景清洁方法，并将其应用于干涉式MeerKAT和SKA-Mid类模拟。我们新开发的广义可见度内部线性组合（GVILC）方法结合了主成分分析（PCA）用于前景子空间识别，该分析由先验的HI信号加噪声协方差矩阵提供信息，并在可见度空间中使用多维ILC来抑制前景并以减少污染的方式恢复HI信号。PCA中要移除的模态数量通过数据驱动的统计方法计算，从而在有限的HI信号损失下实现显著的前景残差抑制。此外，GVILC与前景规避相结合可以防止大部分信号损失，同时恢复最初被前景污染的模态。均方误差统计表明，对于MeerKAT和SKA-Mid类模拟，GVILC均优于仅前景规避策略。我们发现，包含具有线展宽以及HI与连续谱源之间空间相关性的更现实HI模型会导致前景移除后信号损失增加，而不影响GVILC移除的模态数量。本文证明GVILC是使用射电干涉数据在HI强度映射中清洁前景污染的有效方法，使得能够从傅里叶空间中先前无法进入的区域恢复宇宙学信息。
英文摘要
HI intensity mapping is a powerful probe of the large-scale matter distribution and of the underlying astrophysics and cosmology. However, its application is limited by the challenge of separating the faint neutral hydrogen (HI) signal from much brighter foreground emission. We present a new non-parametric foreground-cleaning method in visibility space for low-redshift HI intensity mapping and apply it to interferometric MeerKAT and SKA-Mid-like simulations. Our newly-developed Generalised Visibility Internal Linear Combination (GVILC) method combines Principal Component Analysis (PCA) for foreground subspace identification, informed by a prior HI signal-plus-noise covariance matrix, with a multi-dimensional ILC in visibility space to suppress foregrounds and recover the HI signal with reduced contamination. The number of modes to remove in the PCA is calculated using a data-driven statistical approach, leading to significant foreground residual suppression with limited HI signal loss. Moreover, GVILC in combination with foreground avoidance can prevent most of the signal loss, while simultaneously recovering modes that were initially contaminated by foregrounds. The mean squared error statistic shows that for both MeerKAT and SKA-Mid-like simulations, GVILC outperforms the foreground avoidance only strategy. We find that including a more realistic HI model with line broadening and spatial correlations between HI and continuum sources leads to increased signal loss after foreground removal, without affecting the number of modes removed by GVILC. This paper demonstrates that GVILC is an effective method to clean foreground contamination in HI intensity mapping with radio interferometric data, enabling the recovery of cosmological information from previously inaccessible regions of Fourier space.
