Inferring astrophysics and dark matter properties from 21 cm tomography using deep learning

Author:

Neutsch Steffen1,Heneka Caroline1ORCID,Brüggen Marcus1ORCID

Affiliation:

1. Hamburger Sternwarte, University of Hamburg, Gojenbergsweg 112, D-21029 Hamburg, Germany

Abstract

ABSTRACT 21 cm tomography opens a window to directly study astrophysics and fundamental physics of early epochs in our Universe’s history, the Epoch of Reionization (EoR) and Cosmic Dawn (CD). Summary statistics such as the power spectrum omit information encoded in this signal due to its highly non-Gaussian nature. Here, we adopt a network-based approach for direct inference of CD and EoR astrophysics jointly with fundamental physics from 21 cm tomography. We showcase a warm dark matter (WDM) universe, where dark matter density parameter Ωm and WDM mass mWDM strongly influence both CD and EoR. Reflecting the three-dimensional nature of 21 cm light-cones, we present a new, albeit simple, 3D convolutional neural network (3D-21cmPIE-Net) for efficient parameter recovery at moderate training cost. On simulations we observe high-fidelity parameter recovery for CD and EoR astrophysics (R2 > 0.78–0.99), together with DM density Ωm (R2 > 0.97) and WDM mass (R2 > 0.61, significantly better for $m_\mathrm{WDM}\lt 3\!-\!4\,$ keV). For realistic mock observed light-cones that include noise and foreground levels expected for the Square Kilometre Array, we note that in an optimistic foreground scenario parameter recovery is unaffected, while for moderate, less optimistic foreground levels (occupying the so-called wedge) the recovery of the WDM mass deteriorates, while other parameters remain robust against increased foreground levels at R2 > 0.9. We further test the robustness of our network-based inference against modelling uncertainties and systematics by transfer learning between bare simulations and mock observations; we find robust recovery of specific X-ray luminosity and ionizing efficiency, while DM density and WDM mass come with increased bias and scatter.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 4 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