ALeRCE光曲线分类器:潮汐破坏事件扩展包

IF 5.4 2区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
M. Pavez-Herrera, P. Sánchez-Sáez, L. Hernández-García, F. E. Bauer, F. Förster, M. Catelan, A. Muñoz Arancibia, C. Ricci, I. Reyes-Jainaga, A. Bayo, P. Huijse, G. Cabrera-Vives
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引用次数: 0

摘要

上下文。ALeRCE(事件快速分类自动学习)目前正在处理兹威基瞬变设施(ZTF)警报流,为Vera C. Rubin天文台做准备,并使用广泛的分类法对物体进行分类。ALeRCE光曲线分类器是一种平衡随机森林(BRF)算法,具有两级方案,该方案使用从ZTF警报流计算的可变性特征,以及从AllWISE和ZTF光度测量中获得的颜色。这项工作开发了一个更新版本的ALeRCE代理光曲线分类器,其中包括潮汐中断事件(TDEs)作为一个新的子类。为此,我们纳入了24个新特征,特别是包括ZTF科学图像中检测到的最近源的距离和瞬态幂律衰减的参数化模型。我们还扩展了标记集,包括219 792个光谱分类源,其中包括60个tde。为了有效地将tde整合到ALeRCE的分类中,我们确定了将它们与其他瞬态类型区分开的特定特征,例如它们在星系中的中心位置,完全破坏时显示的典型衰变模式,以及破坏后缺乏颜色可变性。基于这些属性,我们开发了将tde与其他瞬态事件区分开来的特征。与以前的版本相比,改进的分类器可以区分广泛的类,性能更好,并且可以集成TDE类,达到91%的召回率,还可以识别ZTF警报流中未标记数据中的大量潜在的TDE候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ALeRCE light curve classifier: Tidal disruption event expansion pack
Context. ALeRCE (Automatic Learning for the Rapid Classification of Events) is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory, and classifying objects using a broad taxonomy. The ALeRCE light curve classifier is a balanced random forest (BRF) algorithm with a two-level scheme that uses variability features computed from the ZTF alert stream, and colors obtained from AllWISE and ZTF photometry.Aims. This work develops an updated version of the ALeRCE broker light curve classifier that includes tidal disruption events (TDEs) as a new subclass. For this purpose we incorporated 24 new features, notably including the distance to the nearest source detected in ZTF science images and a parametric model of the power-law decay for transients. We also expanded the labeled set to include 219 792 spectroscopically classified sources, including 60 TDEs.Methods. To effectively integrate TDEs into the ALeRCE’s taxonomy, we identified specific characteristics that set them apart from other transient classes, such as their central position in a galaxy, the typical decay pattern displayed when fully disrupted, and the lack of color variability after disruption. Based on these attributes, we developed features to distinguish TDEs from other transient events.Results. The modified classifier can distinguish between a broad range of classes with a better performance compared to the previous version and it can integate the TDE class achieving 91% recall, also identifying a large number of potential TDE candidates in ZTF alert stream unlabeled data.
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来源期刊
Astronomy & Astrophysics
Astronomy & Astrophysics 地学天文-天文与天体物理
CiteScore
10.20
自引率
27.70%
发文量
2105
审稿时长
1-2 weeks
期刊介绍: Astronomy & Astrophysics is an international Journal that publishes papers on all aspects of astronomy and astrophysics (theoretical, observational, and instrumental) independently of the techniques used to obtain the results.
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