OH Megamasers in H i Surveys: Forecasts and a Machine-learning Approach to Separating Disks from Mergers

Author:

Roberts HayleyORCID,Darling JeremyORCID,Baker Andrew J.ORCID

Abstract

Abstract OH megamasers (OHMs) are rare, luminous masers found in gas-rich major galaxy mergers. In untargeted neutral hydrogen (H i) emission-line surveys, spectroscopic redshifts are necessary to differentiate the λ rest = 18 cm masing lines produced by OHMs from H i 21 cm lines. Next-generation H i surveys will detect an unprecedented number of galaxies, most of which will not have spectroscopic redshifts. We present predictions for the numbers of OHMs that will be detected and the potential “contamination” they will impose on H i surveys. We examine the Looking at the Distant Universe with the MeerKAT Array (LADUMA), a single-pointing deep-field survey reaching redshift z H I = 1.45, as well as potential future surveys with the Square Kilometre Array (SKA) that would observe large portions of the sky out to redshift z H I = 1.37. We predict that LADUMA will potentially double the number of known OHMs, creating an expected contamination of 1.0% of the survey’s H i sample. Future SKA H i surveys are expected to see up to 7.2% OH contamination. To mitigate this contamination, we present methods to distinguish H i and OHM host populations without spectroscopic redshifts using near- to mid-IR photometry and a k-Nearest Neighbors algorithm. Using our methods, nearly 99% of OHMs out to redshift z OH ∼ 1.0 can be correctly identified. At redshifts out to z OH ∼ 2.0, 97% of OHMs can be identified. The discovery of these high-redshift OHMs will be valuable for understanding the connection between extreme star formation and galaxy evolution.

Funder

NSF

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 15 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