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对来自DESI的极贫金属候选星的GTC后续观测

GTC Follow-up Observations of Very Metal-Poor Star Candidates from DESI

Carlos Allende Prieto, David S. Aguado, Jonay I. González Hernández, Rafael Rebolo, Joan Najita, Christopher J. Manser, Constance Rockosi, Zachary Slepian, Mar … 展开作者

Carlos Allende Prieto, David S. Aguado, Jonay I. González Hernández, Rafael Rebolo, Joan Najita, Christopher J. Manser, Constance Rockosi, Zachary Slepian, Mar Mezcua, Monica Valluri, Rana Ezzeddine, Sergey E. Koposov, Andrew P. Cooper, Arjun Dey, Boris T. Gänsicke, Ting S. Li, Katia Cunha, Siwei Zou, Jessica Nicole Aguilar, Steven Ahlen, David Brooks, Todd Claybaugh, Shaun Cole, Sarah Eftekharzadeh, Kevin Fanning, Jaime Forero-Romero, Satya Gontcho A Gontcho, Klaus Honscheid, Pascale Jablonka, Robert Kehoe, Theodore Kisner, Martin Landriau, Axel de la Macorra, Aaron Meisner, Ramón Miquel, John Moustakas, Jundan Nie, Claire Poppett, Francisco Prada, Mehdi Rezaie, Graziano Rossi, Eusebio Sánchez, Michael Schubnell, Ray Sharples, Malgorzata Siudek, Verne V. Smith, Gregory Tarlé, Fiorenzo Vincenzo, Benjamin Alan Weaver, Zhimin Zhou, Hu Zou

AI总结:

本文利用GTC上的OSIRIS仪器对DESI调试期间发现的9颗贫金属星进行高信噪比后续观测,验证了DESI光谱质量和数据处理流程的可靠性。

摘要:

暗能量光谱仪(DESI)的观测将使已知的极贫金属星数量显著增加约10倍,从而改善样本统计,以研究银河系早期化学演化和第一代恒星的性质。本文报告了在DESI调试期间识别的9颗贫金属星的高信噪比后续观测,使用的是安装在10.4米加那利大型望远镜(GTC)上的成像与低中分辨率集成光谱光学系统(OSIRIS)仪器。采用经过充分验证的方法对数据进行分析,证实了DESI光谱的质量以及为DESI数据缩减和分析所开发流程的性能。

英文摘要:

The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of ~ 10, improving the sample statistics to study the early chemical evolution of the Milky Way and the nature of the first stars. In this paper we report high signal-to-noise follow-up observations of 9 metal-poor stars identified during the DESI commissioning with the Optical System for Imaging and low-Intermediate-Resolution Integrated Spectroscopy (OSIRIS) instrument on the 10.4m Gran Telescopio Canarias (GTC). The analysis of the data using a well-vetted methodology confirms the quality of the DESI spectra and the performance of the pipelines developed for the data reduction and analysis of DESI data.

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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