Digital twin of optical telescopes could provide high reliable models to predict the performance of the overall system during the design or the manufacture stage and could further be used to analyse faults after we build these telescopes. Comparing with conventional simulation methods, the digital twin of optical telescopes would import real test or telemetry data with machine learning algorithms and integrate numerical models with these data. As there are a lot of data to be collected, such as test data for optical elements, telemetry data from the telescope and the outer environment, it would be necessary to develop an appropriate database for digital twin of the optical telescope. In this paper, we would discuss our design of the database and use a simple example to show applications of the database.
KEYWORDS: Telescopes, Optical instrument design, Point spread functions, Cameras, Signal to noise ratio, Prototyping, Genetic algorithms, Optimization (mathematics), Monte Carlo methods, CCD cameras
Time domain astronomy requires continuous observations to capture series of images of celestial object. To satisfy observation requirements, scientists need to place several telescopes in different sites or in the same site to form a telescope array. In recent years, several telescope array projects have been proposed. Design of telescope arrays is quite different from that of a single telescope. We need to make trade off between the image quality, the aperture size, the field of view and the number of telescopes to satisfy the scientific requirement with minimal overall cost. In this paper, we will introduce our method to optimize the design of a telescope array which would consider detail design of telescopes as well as the overall cost for building and maintaining of these telescopes. This paper provides a useful tool for future telescope array projects.
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