标题： 宽视场小孔径望远镜阵列用于巡天的优化框架 显示英文标题

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

摘要： 对于时域天文学，频繁地在预定周期内以特定深度对天体进行成像是至关重要的。为了满足这些科学需求，近年来全球的科学家们已经开始或计划开发非干涉式望远镜阵列。由于配置这些阵列涉及大量参数，因此需要一个自动化优化框架来选择参数集，以满足科学需求同时最小化成本。本文介绍了一个这样的框架，该框架整合了光学设计软件、曝光时间计算器和优化算法，以平衡光学望远镜阵列的观测能力和成本。使用神经网络加速不同配置下系统的计算结果检索。我们以SiTian项目作为案例研究，展示了该框架的有效性，表明这种方法可以帮助科学家选择最优参数集。该框架的代码已发布在中国虚拟天文台PaperData仓库中，使用户能够为各种非干涉式望远镜阵列项目优化参数。 显示英文摘要

摘要： 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.