SORA: Stellar Occultation Reduction and Analysis

TL;DR

SORA is an open-source Python library designed to efficiently process and analyze stellar occultation data, aiding in the precise determination of Solar System bodies' characteristics amidst increasing observational data.

Contribution

It introduces a comprehensive tool that covers event prediction, data reduction, and analysis, enhancing capabilities for occultation studies in the Big Data era.

Findings

Enables efficient reduction of occultation data

Improves accuracy in size and shape determination

Supports large-scale occultation data analysis

Abstract

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.