AI in Astronomy

Introduction

Generally AI is defined as the simulation of human resources processes by the machines especially the computer systems, and astronomy deals with celestial objects(an object which is located outside of the earth’s atmosphere. For example moon, sun, planets etc..), space and the physical universe. In this article ?we are going to learn how Artificial Intelligence is used in astronomy.

History of AI in Astronomy

Firstly in 1980’s, AI techniques are used in astronomy, especially in the field of artificial neural networks (ANN’s) . Then after in 1990’s & 2000’s ANN are used in galaxy morphology classification, star-galaxy separation, object -detection in astronomical surveys. From 2010 to the present we used Convolutional Neural Network (CNN’s) in order to identify distant galaxies, analyzing data from space telescopes, simulating complex astrophysical phenomena.

Role of AI in Astronomy

Astronomy generates huge amounts of data from telescopes, satellites and other instruments. AI algorithms, on the other hand, can quickly and efficiently process this data, identifying patterns. By identifying patterns and relationships in data that humans might not have noticed, AI can help to uncover new insights and theories about the way the Universe works.

AI algorithms can analyze large volumes of astronomical data more efficiently than humans. These algorithms can help us identify patterns, classify objects. Deep learning techniques can enhance the quality of astronomical images, and improving resolution. AI is used to develop predictive models of astronomical data. These are used in predicting future events, motion of asteroids, behavior of stars, evolution of galaxies.

At present, the space technology and the research work on astronomical data being gradually increased, including the infrared rays, X-rays, and gamma rays. Astronomy has reached a new stage, the astronomical big data period. In recent years, a large quantity of large scale equipment has been put into use, such as the Hubble Space Telescope, the X-ray Space Observatory, etc. Using the features of various knowledge methods in artificial intelligence (ANN’s ,deep learning algorithms etc..) these methods can solve the big data problem in astronomy perfectly.

While researches performing experiments on the data, there is a chance of equipment failures (i.e experiment’s data sometimes cannot detect where the problems are). Here comes the use of ANN(Artificial Neural Network), it establishes a mapping from inputs to outputs, and vice versa (outputs to inputs). By this mapping we can make the complete use of data.

Integrating Astronomy with Cyber Security:

1. Data Protection:Astronomical data means it includes observations, simulations, research findings that are valuable and needs protection from unauthorized access, tampering, or theft. Implementing encryption, access controls, and secure data storage mechanisms can safeguard the sensitive astronomical data.
2. Network Security:Research institutions, Observations, and collaborative projects often rely on the interconnected networks for data transmission and collaboration. Securing these networks with firewalls, intrusion detection systems, and virtual private networks (VPN’s) helps prevent unauthorized access and data breaches.
3. Threat Detection:Actively monitoring for cybersecurity threats and anomalies can help detect and reduce potential attacks before they cause significant damage. Employing threat intelligence feeds, anomaly detection algorithms, and Security Information and Even Management (SIEM) systems can enhance threat detection capabilities.

Applications

1. AI in Black hole Demystification:Dark zones in space known as black holes are so intensely gravitationally concentrated that not even light can escape from them. AI algorithms are trained to notice patterns in this data. By analyzing the data AI can help scientists make predictions about what we might find near the black holes or even we can discover new things.
2. Astronomy related chatbots:Chatbots/Virtual assistants use NLP(natural language processing) algorithms to understand the questions of the users, and these chatbots provide relevant data related to the query. These chatbots make astronomy more accessible to people of all ages and backgrounds. ?By analyzing user interactions and feedback, astronomy chatbots can continuously improve their performance and expand their knowledge base.
3. Astro-Photography Enhancement:Image processing tools can help the astronomers. These tools can automatically align, stack and enhance astronomical images captured by telescopes and camera, reducing noise, and revealing finer details in celestial objects, there by enabling users to produce stunning astro-photographs.
4. AI techniques used in astronomical data:Telescopes and satellites take pictures and gather information about stars, galaxies, and other things in the universe. These can be collected in huge amounts such that humans cannot even analyze it. Here comes the role of AI, The data which is collected from the satellites and telescopes are evaluated(analyzed) by using the ai techniques .

Conclusion

In conclusion, astronomy has greatly benefited from the incorporation of AI, especially through Convolutional Neural Network (CNN) algorithms. Its applications cut across many fields pertaining to astronomical objects, transforming our understanding, perception, and interaction with the cosmos. The future of astronomy will be greatly influenced by AI-driven tools and applications, which will also improve our capabilities and expand our knowledge of the universe.

Written by,

Monika Dandila

Kognitiv Club

Department of Computer Science & Engineering, K L University.