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arXiv 2004.13125astro-ph.GA
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GLEAM 4-Jy(G4Jy)样品:定义和目录

The GLEAM 4-Jy (G4Jy) Sample: I. Definition and the catalogue

Sarah V. White, Thomas M. O. Franzen, Chris J. Riseley, O. Ivy Wong, Anna D. Kapińska, Natasha Hurley-Walker, Joseph R. Callingham, Kshitij Thorat, Chen Wu, Pau… 展开作者

Sarah V. White, Thomas M. O. Franzen, Chris J. Riseley, O. Ivy Wong, Anna D. Kapińska, Natasha Hurley-Walker, Joseph R. Callingham, Kshitij Thorat, Chen Wu, Paul Hancock, Richard W. Hunstead, Nick Seymour, Jesse Swan, Randall Wayth, John Morgan, Rajan Chhetri, Carole Jackson, Stuart Weston, Martin Bell, Bi-Qing For, B. M. Gaensler, Melanie Johnston-Hollitt, André Offringa, Lister Staveley-Smith

摘要:

默奇森宽场天线阵(MWA)在72-231 MHz的低无线电频率范围内观测了整个南部天空(December,$δ<$ 30 deg)。这些观测构成了银河系和河外全天空MWA(GLEAM)巡天,我们使用河外星表(银河纬度,$|b| >$ 10度)来定义GLEAM 4-Jy(G4 Jy)样本。这是一个完整的“最亮”射电源样本($S_{\mathrm{151MHz}} >$ 4 Jy),其中大部分是具有强大射电源喷流的活动星系核。至关重要的是,低频观测允许以与方向无关的方式选择这些源(即最大限度地减少高频调查中固有的多普勒增强造成的偏差)。然后,我们使用更高分辨率的无线电图像和其他波长的信息,对GLEAM中最亮的成分进行形态学分类。我们还对文献进行交叉检查,并进行内部匹配,以提高样本完整性(估计为$>$ 95.5%)。这导致了1,863个源的目录,使G4 Jy样本比修订后的第三剑桥射电源目录(3CRR; $S_{\mathrm{178MHz}} >$ 10.9 Jy)大10倍以上。在这些G4 Jy源中,78个通过MWA(第一阶段)合成束($\sim$在200 MHz下2弧分)分辨,并且我们将67%的样品标记为“单”,26%标记为“双”,4%标记为“三”,并且3%标记为在$\sim$ 1 GHz下具有“复杂”形态(45弧秒分辨率)。除此之外,我们的增值目录还提供了无线电发射的中红外源关联(3.4微米时的分辨率为6角秒),通过目视检查和对文献的彻底检查来识别。因此,G4 Jy样本可以用作通过机器学习算法进行交叉识别的可靠训练集。[摘要删节为arXiv提交。]

英文摘要:

The Murchison Widefield Array (MWA) has observed the entire southern sky (Declination, $δ<$ 30 deg) at low radio-frequencies, over the range 72-231 MHz. These observations constitute the GaLactic and Extragalactic All-sky MWA (GLEAM) Survey, and we use the extragalactic catalogue (Galactic latitude, $|b| >$ 10 deg) to define the GLEAM 4-Jy (G4Jy) Sample. This is a complete sample of the 'brightest' radio-sources ($S_{\mathrm{151MHz}} >$ 4 Jy), the majority of which are active galactic nuclei with powerful radio-jets. Crucially, low-frequency observations allow the selection of such sources in an orientation-independent way (i.e. minimising the bias caused by Doppler boosting, inherent in high-frequency surveys). We then use higher-resolution radio images, and information at other wavelengths, to morphologically classify the brightest components in GLEAM. We also conduct cross-checks against the literature, and perform internal matching, in order to improve sample completeness (which is estimated to be $>$ 95.5%). This results in a catalogue of 1,863 sources, making the G4Jy Sample over 10 times larger than that of the revised Third Cambridge Catalogue of Radio Sources (3CRR; $S_{\mathrm{178MHz}} >$ 10.9 Jy). Of these G4Jy sources, 78 are resolved by the MWA (Phase-I) synthesised beam ($\sim$2 arcmin at 200 MHz), and we label 67% of the sample as 'single', 26% as 'double', 4% as 'triple', and 3% as having 'complex' morphology at $\sim$1 GHz (45-arcsec resolution). Alongside this, our value-added catalogue provides mid-infrared source associations (subject to 6-arcsec resolution at 3.4 micron) for the radio emission, as identified through visual inspection and thorough checks against the literature. As such, the G4Jy Sample can be used as a reliable training set for cross-identification via machine-learning algorithms. [Abstract abridged for arXiv submission.]

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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