AstroSA: An astronomical observation scheduler assessment framework in python

Abstract

Time-domain astronomy, as a leading aspect of astronomical research, demands a significant increase in telescope hours. An efficient scheduler is crucial to handle the large number of observational requests effectively. However, the commonly used schedulers in observatories have not yet fully utilized the advancements in mathematics and computer science. In order to establish a connection between astronomy and the latest achievements in these fields, we propose the Astronomical Observing Scheduler Assessment Framework (AstroSA), implemented as a Python package. The AstroSA offers a rapid and user-friendly quantitative evaluator of the scheduler with five built-in metrics: expected quality of observed data, overhead ratio, scientific value, schedule rate, and ratio to the best airmass. Additionally, AstroSA includes a default virtual telescope and a night of cloud coverage, so that users can start to use it with minimal settings.