arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2503.08041astro-ph.GA
收藏

AGEL巡天数据发布2:用于星系演化与宇宙学的引力透镜样本

The AGEL Survey Data Release 2: A Gravitational Lens Sample for Galaxy Evolution and Cosmology

Tania M. Barone, Keerthi Vasan G. C., Kim-Vy Tran, Glenn G. Kacprzak, Karl Glazebrook, Tucker Jones, Duncan J. Bowden, Faith Dalessandro, Nandini Sahu, Hannah S… 展开作者

Tania M. Barone, Keerthi Vasan G. C., Kim-Vy Tran, Glenn G. Kacprzak, Karl Glazebrook, Tucker Jones, Duncan J. Bowden, Faith Dalessandro, Nandini Sahu, Hannah Skobe, Rebecca J. Allen, A. Makai Baker, Daniel J. Ballard, Yuguang Chen, Thomas E. Collett, Giovanni Ferrami, Jimena Gonzalez, William Gottemoller, Anishya Harshan, Xiaosheng Huang, Leena Iwamoto, Colin Jacobs, Tesla E. Jeltema, Kaustubh Rajesh Gupta, Geraint F. Lewis, Sebastian Lopez, Themiya Nanayakkara, Nikole M. Nielsen, Jackson O'Donnell, Huimin Qu, Sunny Rhoades, Anowar Shajib, Sarah M. Sweet, Nicolas Tejos

AI总结:

AGEL巡天数据发布2将光谱证认的引力透镜样本扩展至138个,并利用HST高分辨率成像和卷积神经网络候选识别,为星系演化与宇宙学研究及下一代巡天提供探路者样本。

摘要:

ASTRO 3D星系演化透镜巡天(AGEL)是一项持续开展的工作,旨在通过高空间分辨率成像对多样化的引力透镜样本进行光谱证认,以促进广泛的科学产出。AGEL系统涵盖从单个星系尺度偏转体到星系群和星系团,并包括稀有目标,如具有多重源、透镜化宁静星系和爱因斯坦环的星系尺度透镜。我们在Tran等人2022年(AGEL数据发布1)提出的77个系统基础上,共呈现138个透镜,以及来自已完成的HST SNAP项目对71个透镜的高分辨率F140W和F200LP哈勃空间望远镜图像。透镜候选体最初由卷积神经网络在DES和DECaLS成像场中识别,在具有后续光谱观测的目标中,我们发现成功率很高(96%)。与其他光谱透镜样本相比,AGEL透镜往往具有更高红移的偏转体和源。我们简要讨论了假阳性候选体的常见原因,以及下一代透镜搜寻中减少假阳性的策略。最后,我们呈现了6个可用于宇宙学分析的星系尺度双源平面透镜。随着下一代望远镜和巡天项目如Euclid、Vera Rubin的时空遗产巡天、Keck天文台的KAPA项目以及4MOST的4SLSLS巡天即将到来,AGEL巡天代表了改进自动化候选体搜索方法以及根据科学潜力识别和分诊后续观测候选体的探路者。

英文摘要:

The ASTRO 3D Galaxy Evolution with Lenses (AGEL) Survey is an ongoing effort to spectroscopically confirm a diverse sample of gravitational lenses with high spatial resolution imaging, to facilitate a broad range of science outcomes. The AGEL systems span single galaxy-scale deflectors to groups and clusters, and include rare targets such as galaxy-scale lenses with multiple sources, lensed quiescent galaxies, and Einstein rings. We build on the 77 systems presented in Tran et al. 2022 (AGEL data release 1) to present a total 138 lenses, and high resolution F140W and F200LP Hubble Space Telescope images for 71 lenses from a completed HST SNAP program. Lens candidates were originally identified by convolutional neural networks in the DES and DECaLS imaging fields, and of the targets with follow-up spectroscopy we find a high (96%) success rate. Compared with other spectroscopic lens samples, AGEL lenses tend to have both higher redshift deflectors and sources. We briefly discuss the common causes of false-positive candidates, and strategies for mitigating false-positives in next generation lens searches. Lastly, we present 6 galaxy-scale double-source plane lenses useful for cosmological analyses. With next-generation telescopes and surveys such as Euclid, Vera Rubin's Legacy Survey of Space and Time, Keck Observatory's KAPA program, and 4MOST's 4SLSLS surveys on the horizon, the AGEL survey represents a pathfinder for refining automated candidate search methods and identifying and triaging candidates for followup based on scientific potential.

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。

↑