The Automatic Observation Management System of the GWAC Network. I. System Architecture and Workflow
Résumé
The Ground Wide Angle Camera Network (GWAC-N) is a network of robotic multi-aperture, multiple field-of-view (FoV) optical telescopes. The main contingent of GWAC-N instruments are provided by the Ground Wide Angle Cameras Array (GWAC-A), and additional, narrower FoV telescopes are utilized to provide fast multi-band follow-up capabilities. The primary scientific goal of the GWAC-N is to search for optical counterparts of gamma-ray bursts that will be detected by the Space Variable Object Monitor (SVOM) satellite. The GWAC-N performs many additional observing tasks including follow-up of Target of Opportunities (ToO) targets and the detection (and monitoring) of variable objects and optical transients. To handle these use cases (and to allow for extensibility), we have designed ten observation modes and 175 observation strategies, including a joint strategy with multiple GWAC-N telescopes for the follow-up of gravitational wave (GW) events. To perform these observations, we develop an Automatic Observation Management (AOM) system capable of performing object management, dynamic scheduling, automatic broadcasting across the network, and image handling. The AOM system combines the individual telescopes which comprise the GWAC-N into a network and smoothly organizes all associated operations, completely meeting the requirements dictated by GWAC-N. With its modular design, the AOM is scientifically and technically viable for other general-purpose telescope networks. As the GWAC-N extends and evolves, the AOM will greatly enhance its discovery potential. In this first paper of a series, we present the scientific goals of the GWAC-N and detail the hardware, software, and workflow developed to achieve these goals. The structure, technical design, implementation, and performance of the AOM system are also described in detail. We conclude with a summary of the current status of the GWAC-N and our near-future development plan.