论文标题

能够发现重力镜头爆炸性瞬变:一种新的方法,用于构建全天空观察列表和星系簇

Enabling discovery of gravitationally lensed explosive transients: a new method to build an all-sky watch-list of groups and clusters of galaxies

论文作者

Ryczanowski, Dan, Smith, Graham P., Bianconi, Matteo, McGee, Sean, Robertson, Andrew, Massey, Richard, Jauzac, Mathilde

论文摘要

通过从实时范围调查数据的实时探测到瞬时检测的星系组和群集的跨引用是一种有前途的方法,可在接下来的十年中发现重力透镜爆炸性瞬态,包括超新星,Kilonovae,Kilonovae,Grvertication Wave和Gamma-ray爆发。但是,目前没有足够的角度和深度的对象目录可以充分执行此类搜索。在这项研究中,我们开发了一种能够根据其镜头平面属性创建到$ z \ simeq1 $的星系组和集群尺度对象的群集找到方法,并且仅使用来自VHS和UHS和UHS和ALL-SKY \ TEXTIT的宽大红外调查的现有数据。在测试此方法时,我们回收了包含$θ_e\ geq 5 \ arcsec $的Einstein Radii的样本中的91%。我们还使用我们的方法搜索了该测试样本的周围区域和簇,并通过视觉检查验证了任何重要发现的存在,从而得出了估计假阳性率低至6%的估计。该方法还对来自其DP0程序的模拟鲁宾数据进行了测试,该方法得出了$ \ gtrsim良好恢复率的互补结果80 $ 80 $ 80 $,对于$ M_ {200} \ geq7 \ geq7 \ times10^{13} $ _ $ _ $ _ \ odot $ clusters,并且在我们的测试区域中没有误差。重要的是,我们的方法定位在鲁宾的LSST之前创建一个监视列表,因为它仅利用现有数据,因此可以在调查寿命的早期发现镜头瞬变。

Cross-referencing a watchlist of galaxy groups and clusters with transient detections from real-time streams of wide-field survey data is a promising method for discovering gravitationally lensed explosive transients including supernovae, kilonovae, gravitational waves and gamma-ray bursts in the next ten years. However, currently there exists no catalogue of objects with both sufficient angular extent and depth to adequately perform such a search. In this study, we develop a cluster-finding method capable of creating an all-sky list of galaxy group- and cluster-scale objects out to $z\simeq1$ based on their lens-plane properties and using only existing data from wide-field infrared surveys such as VHS and UHS, and all-sky \textit{WISE} data. In testing this method, we recover 91 per cent of a sample containing known and candidate lensing objects with Einstein radii of $θ_E \geq 5\arcsec$. We also search the surrounding regions of this test sample for other groups and clusters using our method and verify the existence of any significant findings by visual inspection, deriving estimates of the false positive rate that are as low as 6 per cent. The method is also tested on simulated Rubin data from their DP0 programme, which yields complementary results of a good recovery rate of $\gtrsim 80$ per cent for $M_{200}\geq7\times10^{13}$M$_\odot$ clusters and with no false positives produced in our test region. Importantly, our method is positioned to create a watchlist in advance of Rubin's LSST, as it utilises only existing data, therefore enabling the discovery of lensed transients early within the survey's lifetime.

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