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AI in Astronomy | Artificial Intelligence and Astronomy

AI in Astronomy
AI in Astronomy

AI in Astronomy

Concept of AI in Astronomy: Many peoples are as fascinated by Artificial intelligence as astronomers are, some find it a mystery and some an annoyance. With the creation of appropriate computer software, researchers in artificial intelligence laboratories around the world try to solve various forms and degrees of intelligence. However, In these works, we need natural language processing, speech processing, vision, symbolic computation, as well as various types of formal reasoning such as theorems. The results of numerous intervening innings have been achieved in the past, but progress has generally been slower than expected by the initial enthusiasts. And, This phenomenon is not unknown in other scientific fields.

Application of AI in Astronomy:

A few years ago, artificial intelligence entered astronomy. The original calculation of recent ideas and applications by astronomers is a knowledge-based astronomical system. And started and edited by Andre Heck and Fionn Murtagh. For which we should all be very grateful. As can be seen from the collaboration in this book, A1 has reached the limits of astronomy, but it does not have a basic existence. Proposal processing and scheduling. The Hubble Space Telescope has emerged as the hub of purpose applications in the United States and Europe. A few years ago, the Space Telescope European Coordinating Facility launched its “Artificial Intelligence Pilot Project”. Aimed at finding opportunities and applying these new software techniques to a select few areas of interest.

Full-Text Retrieval

Retrieving full-text information on astronomy is another area for which technology has originally been proposed for the machine-readable version of astronomy and astrophysics and is now realized in US astrophysics data. Happened inside the system (ADS). A distributed database system that includes all large space-related databases.

Symbolic computation:

Symbolic computation is required, for example, in the process of solving integrals or differential equations. So, For some time now, there have been computer programs that can help you do just that. In physics, these programs are primarily used to count elementary particles or general relationships. However, One of these programs available at ESO is a comprehensive mathematics system for doing math. This allows one to easily solve algebraic equations, multiplication matrices, complex formulas, etc. on a symbolic level.


It seems like a natural area for the use of artificial techniques in astronomy. Already in 1986, a theoretical classification for the morphological classification of galaxies was developed by the French computer scientist Monique Thonnat. However, Other classifiers are designed to classified as IUE low Spread Spectra and Low-Resolution Spectra by Infrared Astronomical Satellite (IRAS). Trainable neural networks offer some possibilities for difficult classified tasks, such as cosmic ray detection and discrimination on images of solid-state detectors in space.

Future of AI in Astronomy

The future of AI in astronomy is not as bright as some see it, nor is it as dark a future as some do. It is still easy to imagine many fields. They are still outside the core of astronomy, where technology can play a role in the future. The increasing complexity of computer systems will require better human-computer interfaces. However, Ground-based observation operations also appear to be increasingly complex and can also reach far beyond the level at which humans can handle them quickly and reliably.

Absence and split schedule observation procedures will become more common. Combining multiple frequency observations, which require the coordination of multiple ground bases and satellite observations, can be facilitated with the help of state-of-the-art scheduling. Planned planetary missions, if ever funded, will require independent observation capabilities. Adaptive control of “flexible” telescopic optics or optimization of telescopic rows can be made possible by using neural networks. And is associated with data content from large image databases.


Considering some examples, we have seen that artificial intelligence techniques have already entered astronomy. These deeds have been set up by a few dedicated people through the driving force without monetary reasons. With the astronomical community and the number of resources associated with the development of research and astronomical experience. However, It is fairly safe to anticipate their purpose in the future.

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