five

The Near-Earth Didymos-Dimorphos binary system after the NASA/DART impact: rotationally resolved spectral characterization.

收藏
DataCite Commons2024-11-27 更新2025-02-15 收录
下载链接:
https://researchdata.cab.unipd.it/id/eprint/1440
下载链接
链接失效反馈
官方服务:
资源简介:
In this data collection, we present new spectra of the binary asteroid Didymos obtained 25 days after DART's impact and two months later. These observations allowed us to investigate the spectroscopic rotation of Didymos, and geometric analyses were performed to identify the source regions corresponding to each spectrum. Although the spectra are consistent with the pre-impact behavior of the system and confirm its S-type taxonomic classification, the spectral slopes exhibit a slight increasing trend from October to December. Additionally, subtle variations were tentatively identified in correspondence with secondary eclipse/occultation events observed in both October and December. The spectroscopic data were acquired using the Copernico Telescope (INAF-OAPD) in Asiago, Italy; the Large Binocular Telescope (INAF) on Mount Graham, Arizona; and the Gran Telescopio Canarias (GTC) in La Palma, Spain. Observations were conducted using the AFOSC instrument on the Copernico Telescope and the MODS instrument on the Large Binocular Telescope, covering the spectral range of 0.5–0.9 µm. This dataset includes: • Raw calibration files: Bias, flat-field, and lamp data. • Spectra of the solar analog Landolt SA 98-978 and Didymos, obtained on different dates: o Copernico Telescope: October 18, 2022; December 26, 2022; and December 27, 2022. o Large Binocular Telescope: October 18, 2022. • Reduced spectra of Didymos from October 19, 2022, acquired using the GTC. These are provided as three text files. Additionally, a log file named Log.txt is included. This file summarizes key metadata for each dataset, such as file name, object, and observation date (FILENAME, OBJECT, DATE-OBS).
提供机构:
Centro di Ateneo per le Biblioteche dell'Università degli Studi di Padova
创建时间:
2024-11-27
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作