Eliminating Primary Beam Effect in Foreground Subtraction of Neutral Hydrogen Intensity Mapping Survey with Deep Learning

Author:

Ni ShuleiORCID,Li YichaoORCID,Gao Li-YangORCID,Zhang XinORCID

Abstract

Abstract In neutral hydrogen (H i) intensity mapping (IM) survey, foreground contamination on cosmological signal is extremely severe, and systematic effects caused by radio telescopes further aggravate the difficulties in subtracting foreground. We investigate whether the deep-learning method, the 3D U-Net algorithm, can play a crucial role in foreground subtraction when considering the systematic effect caused by the telescope’s primary beam. We consider two beam models, i.e., the Gaussian beam and Cosine beam models. The traditional principal component analysis (PCA) method is employed as a preprocessing step for the U-Net method to reduce the map dynamic range. We find that in the case of the Gaussian beam, the PCA method can effectively clean the foreground. However, the PCA method cannot handle the systematic effect induced by the Cosine beam, and the additional U-Net method can improve the result significantly. To show how well the PCA and U-Net methods can recover the H i signal, we also derive the H i angular power spectrum and H i 2D power spectrum after performing foreground subtraction. It is found that in the case of Gaussian beam, the concordance with the original H i map using U-Net is better than that using PCA by 27.4%, and in the case of Cosine beam, the concordance using U-Net is better than that using PCA by 144.8%. Therefore, the U-Net–based foreground subtraction can efficiently eliminate the telescope primary beam effect and shed new light on recovering H i power spectrum for future H i IM experiments.

Funder

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Fundamental Research Funds for Central Universities

111 Project of China

China Manned Space Project

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3