ELEPHANT:寻找无主天体瞬态的乳酸外管线

IF 5.4 2区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
P.J. Pessi, R. Durgesh, L. Nakazono, E. Hayes, R.A.P. Oliveira, E.O. Ishida, A. Moitinho, A. Krone-Martins, B. Moews, R.S. de Souza, R. Beck, M.A. Kuhn, K. Nowak, S. Vaughan
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引用次数: 0

摘要

与宿主星系没有明显关联的瞬态天文现象通常被称为无宿主现象。这些罕见的现象可以为了解恒星和星系的特性和演化提供独特的见解。然而,由于当代高分辨率天文巡天所捕捉到的瞬态现象数量庞大,要对所有潜在的无主瞬态现象进行人工识别是不切实际的。因此,创建一个系统化的识别工具对于研究这些难以捉摸的事件至关重要。我们提出了 "无主天文瞬变的乳酸外管道"(ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients)(一个用于过滤天文数据流中无主瞬变的框架)。它的设计目的是处理来自 Fink 经纪商提供的 Zwicky 瞬变设施(ZTF)的警报;不过,其基本概念也可应用于其他数据源。我们使用 Fink 访问了 2022 年 1 月至 2023 年 12 月间产生的所有 ZTF 警报,选择了与 SIMBAD 或 TNS 报告的河外瞬变相关的警报,以及那些被经纪人内的机器学习(ML)分类器归类为超新星(SNe)或千新星(KNe)的警报。然后,我们使用一系列图像分析技术处理相关的邮票,以检索无主候选者。我们发现,在所有分析过的瞬变中,只有不到 2 个可能是无主的。其中,只有 10 个瞬变有 TNS 上报告的光谱类别,最常见的类别是 Ia 型自发彗星,其次是超光速自发彗星。特别是,在我们的管道检索到的无主候选者中,有被认为是一对不稳定SN候选者的SN 2018ibb,以及仅有的五个已知SNe Icn之一的SN 2022ann。当 TNS 上没有报告任何类别时,主要类别是准恒星天体(QSO)和 SN 候选天体,前者由 SIMBAD 获得,后者由 Fink ML 分类器推断。这一管道将在许多应用中发挥作用,从选择瞬变事件进行跟踪到研究瞬变环境,不一而足。本文介绍的结果表明,开发专门设计的管道是可行的,可以在大规模巡天的基础上进行各种科学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ELEPHANT: ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients
Transient astronomical events that exhibit no discernible association with a host galaxy are commonly referred to as hostless. These rare phenomena can offer unique insights into the properties and evolution of stars and galaxies. However, the sheer number of transients captured by contemporary high-cadence astronomical surveys renders the manual identification of all potential hostless transients impractical. Therefore, creating a systematic identification tool is crucial for studying these elusive events. We present the ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients ( a framework for filtering hostless transients in astronomical data streams. It was designed to process alerts from the Zwicky Transient Facility (ZTF) presented in the Fink broker; however, its underlying concept can be applied to other data sources. We used Fink to access all the ZTF alerts produced between January 2022 and December 2023, selecting alerts associated with extragalactic transients reported in SIMBAD or TNS, as well as those classified as supernovae (SNe) or kilonovae (KNe) by the machine learning (ML) classifiers within the broker. We then processed the associated stamps using a sequence of image analysis techniques to retrieve hostless candidates. We find that lesssim 2 of all analyzed transients are potentially hostless. Among them, only sim 10 have a spectroscopic class reported on TNS, with type Ia SNe being the most common class, followed by superluminous SNe. In particular, among the hostless candidates retrieved by our pipeline, there is SN 2018ibb, which has been proposed to be a pair instability SN candidate, and SN 2022ann, one of only five known SNe Icn. When no class is reported on TNS, the dominant classes are quasi-stellar object (QSO) and SN candidates, with the former obtained from SIMBAD and the latter inferred using the Fink ML classifier. represents an effective strategy to filter extragalactic events within large and complex astronomical alert streams. There are many applications for which this pipeline will be useful, ranging from transient selection for follow-up to studies of transient environments. The results presented here demonstrate the feasibility of developing specially crafted pipelines that enable a variety of scientific studies based on large-scale surveys.
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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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