Telescope arrays are increasingly valued for their higher resource utilization, broader survey areas, and more frequent space-time monitoring compared to single telescopes. This new observation mode poses a challenging demand for efficient coordination of distributed telescopes while coherently modeling abstract environmental constraints to achieve scientific goals.
We propose a multilevel scheduling model and a flexible software framework for distributed time-domain survey telescope array. This framework is constructed from both global and site levels, successfully solves the telescope array scheduling problem considering the projected volumes of constraints and objectives. A remarkable feature of the framework is its ability to achieve global control of generic large-scale surveys through multi-level scheduling, dynamically responding to unexpected interruptions with robustness and scalability. Also, a Python simulator is built to model telescope array observations, including the creation of scheduling blocks obtained from global scheduler, observation conditions, telescope equipment status, and observation fields, enabling the evaluation of scheduling algorithms under various settings.
Using China's Sitian project as an example, telescope array scheduling algorithms and time-domain survey evaluation metrics are designed and implemented within the proposed framework. We envision this prototype framework being used to develop automated scheduling schema that support multi-telescope, multi-site coordinated observations. By integrating novel artificial intelligence techniques and solvers, further performance optimizations can be easily supported.