An Optimization Framework for Wide-Field Small Aperture Telescope Arrays Used in Sky Surveys

TL;DR

This paper presents an automated optimization framework for configuring wide-field small aperture telescope arrays, balancing scientific observation needs and costs, demonstrated through a case study on the SiTian project.

Contribution

The paper introduces a novel integrated optimization framework combining optical design, neural networks, and algorithms for telescope array configuration.

Findings

Framework effectively balances observation capabilities and costs.

Neural networks accelerate configuration result retrieval.

Case study demonstrates practical utility for the SiTian project.

Abstract

For time-domain astronomy, it is crucial to frequently image celestial objects at specific depths within a predetermined cadence. To fulfill these scientific demands, scientists globally have started or planned the development of non-interferometric telescope arrays in recent years. Due to the numerous parameters involved in configuring these arrays, there is a need for an automated optimization framework that selects parameter sets to satisfy scientific needs while minimizing costs. In this paper, we introduce such a framework, which integrates optical design software, an exposure time calculator, and an optimization algorithm, to balance the observation capabilities and the cost of optical telescope arrays. Neural networks are utilized to speed up results retrieval of the system with different configurations. We use the SiTian project as a case study to demonstrate the framework's effectiveness, showing that this approach can aid scientists in selecting optimal parameter sets. The code for this framework is published in the China Virtual Observatory PaperData Repository, enabling users to optimize parameters for various non-interferometric telescope array projects.