发表机构
Foundation for Research and Technology Hellas (FORTH); Université Paris-Saclay; Université Paris Cité; CEA; CNRS; University of Crete; Observatoire de la Côte d’Azur; Laboratoire Lagrange; University of the Western Cape; Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH)（希腊基金会; 巴黎萨克雷大学; 巴黎西岱大学; 法国原子能和替代能源委员会; 法国国家科学研究中心; 克里特大学; 蔚蓝海岸天文台; 拉格朗日实验室; 西开普大学; 希腊基金会计算机科学研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
JESSNet是一种波束感知、掩模兼容的前景去除框架，通过多尺度分解、学习型稀疏正则化和掩模约束重建，在模拟SKA-MID观测中准确恢复H I信号功率谱，改善角尺度恢复并减少波束效应。
AI 中文摘要
前景去除是H I 21厘米强度映射的主要挑战，特别是在存在色散仪器波束（将角向前景结构耦合到频率方向）以及天空覆盖不完整的情况下。我们引入了JESSNet，一种针对单天线强度映射的波束感知、掩模兼容的前景去除框架。基于SDecGMCA，JESSNet引入了三个主要扩展：具有尺度相关混合矩阵和通道选择的多尺度角向分解，学习型球面小波“learnlet”稀疏正则化算子，以及适用于银河系掩模和巡天足迹的掩模约束重建。我们在模拟的SKA-MID类观测上测试了JESSNet，频率范围为900-1300 MHz（红移z≈0.09-0.58），包括H I发射、银河系和河外前景、热噪声以及受MeerKAT启发的振荡色散波束。多尺度重建准确恢复了输入H I信号的角向和频率功率谱，相对于单尺度实现，改善了低和中间角尺度的恢复，并减少了残余的波束诱导光谱特征。JESSNet在合成巡天足迹下也保持有效，在不完整天空覆盖下保留了H I功率谱。代码和分析流程已公开，以促进可复现性以及未来对模拟和观测数据的应用。
英文摘要
Foreground cleaning is a major challenge for H\,{\sc i} 21 cm intensity mapping, particularly in the presence of a chromatic instrumental beam that couples angular foreground structure into the frequency direction and under incomplete sky coverage. We introduce JESSNet, a beam-aware, mask-compatible foreground-cleaning framework for single-dish intensity mapping. Building on SDecGMCA, JESSNet introduces three main extensions: a multiscale angular decomposition with scale-dependent mixing matrices and channel selection, a learned spherical-wavelet ''learnlet'' sparse regularization operator, and a mask-constrained reconstruction applicable to Galactic masks and survey footprints. We test JESSNet on simulated SKA-MID-like observations over $900\text{-}1300\,{\rm MHz}$ ($z\simeq0.09\text{-}0.58$), including H\,{\sc i} emission, Galactic and extragalactic foregrounds, thermal noise, and an oscillating MeerKAT-inspired chromatic beam. The multiscale reconstruction accurately recovers the angular and frequency power spectra of the input H\,{\sc i} signal, improves the recovery at low and intermediate angular scales relative to a single-scale implementation, and reduces residual beam-induced spectral features. JESSNet also remains effective for a synthetic survey footprint, preserving the H\,{\sc i} power spectra under incomplete sky coverage. The code and analysis pipeline are publicly released to facilitate reproducibility and future applications to simulated and observational data.
