Automated scheduler for the SOXS instrument: design and performance

TL;DR

This paper describes the development and initial testing of an automated, scalable scheduler for the SOXS instrument at ESO-NTT, designed to optimize transient observations without on-site astronomer presence.

Contribution

The paper introduces a new fully automated, scalable scheduler architecture for the SOXS instrument, capable of rapid response and weather adaptation, tailored for remote operation at ESO-NTT.

Findings

Scheduler is ready for on-site testing during commissioning.

Web interface and preliminary performance tests are described.

Architecture uses Docker, API Gateway, and Flask for scalability.

Abstract

We present the advancements in the development of the scheduler for the Son Of X-shooter instrument at the ESO-NTT 3.58-m telescope in La Silla, Chile. SOXS is designed as a single-object spectroscopic facility and features a high-efficiency spectrograph with two arms covering the spectral range of 350-2000 nm and a mean resolving power of approximately R=4500. It will conduct UV-visible and near-infrared follow-up observations of astrophysical transients, drawing from a broad pool of targets accessible through the streaming services of wide-field telescopes, both current and future, as well as high-energy satellites. The instrument will cater to various scientific objectives within the astrophysical community, each entailing specific requirements for observation planning. SOXS will operate at the European Southern Observatory (ESO) in La Silla, without the presence of astronomers on the mountain. This poses a unique challenge for the scheduling process, demanding a fully automated algorithm that is autonomously interacting with the appropriate databases and the La Silla Weather API, and is capable of presenting the operator not only with an ordered list of optimal targets (in terms of observing constraints) but also with optimal backups in the event of changing weather conditions. This imposes the necessity for a scheduler with rapid-response capabilities without compromising the optimization process, ensuring the high quality of observations and best use of the time at the telescope. We thus developed a new highly available and scalable architecture, implementing API Restful applications like Docker Containers, API Gateway, and Python-based Flask frameworks. We provide an overview of the current state of the scheduler, which is now ready for the approaching on-site testing during Commissioning phase, along with insights into its web interface and preliminary performance tests.