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arXiv 2201.01799astro-ph.IM
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SORA:恒星掩星还原和分析

SORA: Stellar Occultation Reduction and Analysis

A. R. Gomes-Júnior, B. E. Morgado, G. Benedetti-Rossi, R. C. Boufleur, F. L. Rommel, M. V. Banda-Huarca, Y. Kilic, F. Braga-Ribas, B. Sicardy

摘要:

恒星掩星技术在确定恒星的大小、形状、天体测量等方面提供了有竞争力的准确性,的掩星体,相当于在现场观测航天器。随着LSST预计的已知太阳系天体数量的增加,高度精确的天体测量目录,如盖亚,以及星历表的改进,掩星观测将变得更加普遍,每次观测的弦数也会增加。在大数据时代的背景下,我们开发了Sora,这是一个开源的Python库,可以有效地减少和分析恒星掩星数据。它包括从预测这些事件到确定太阳系天体的大小,形状和位置的例程。

英文摘要:

The stellar occultation technique provides competitive accuracy in determining the sizes, shapes, astrometry, etc., of the occulting body, comparable to in-situ observations by spacecraft. With the increase in the number of known Solar System objects expected from the LSST, the highly precise astrometric catalogues, such as Gaia, and the improvement of ephemerides, occultations observations will become more common with a higher number of chords in each observation. In the context of the Big Data era, we developed SORA, an open-source python library to reduce and analyse stellar occultation data efficiently. It includes routines from predicting such events up to the determination of Solar System bodies' sizes, shapes, and positions.

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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