OH Megamasers in H i Surveys: Forecasts and a Machine-learning Approach to Separating Disks from Mergers
OH Megamasers in H i Surveys: Forecasts and a Machine-learning Approach to Separating Disks from Mergers
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DOI：
10.3847/1538-4357/abe944
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发表时间：
2021-02
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影响因子：
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通讯作者：
H. Roberts;J. Darling;A. Baker
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作者：
H. Roberts;J. Darling;A. Baker
哦，超大激光(欧姆)是在气体丰富的主要星系合并中发现的罕见的发光脉泽。在非定向中性氢(HI)发射线测量中，需要用光谱红移来区分由OHMS产生的λREST=18 cm谱线和HI 21 cm谱线。新一代的H I探测将探测到数量空前的星系，其中大部分将不会有光谱红移。我们提出了对将被检测到的欧姆的数量以及它们将对HI调查施加的潜在“污染”的预测。我们研究了用猫鼬阵列(Laduma)观测遥远的宇宙，一个达到红移z HI=1.45的单点深场观测，以及未来可能用平方公里阵列(SKA)观测到红移z HI=1.37的大部分天空。我们预测，拉杜马可能会使已知欧姆的数量翻一番，预计将造成调查中1.0%的HI样本的污染。未来的SKA H I调查预计将看到高达7.2%的OH污染。为了减轻这种污染，我们提出了使用近至中红外光度学和k最近邻算法在没有光谱红移的情况下区分HI和Ohm宿主种群的方法。使用我们的方法，几乎99%的出射到红移z OH∼1.0的欧姆都可以被正确识别。在红移到z OH∼2.0时，97%的欧姆可以被识别。这些高红移欧姆的发现对于理解极端恒星形成和星系演化之间的联系将是有价值的。
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.