The Intelligent Universe

2Data Mining and Machine Learning in Astrophysics

Gissmol Saji¹* and Sanjay Singh Bisht²

¹Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany

²Department of Physics, Radhe Hari Govt. PG College, Kashipur (U S Nagar), Uttarakhand, India

Abstract

In recent years, data mining and machine learning (ML) have revolutionized numerous fields, including astrophysics, by efficiently analyzing the vast and complex datasets that are collected from telescopes, satellites, other observational devices, and simulations. These technologies have proven beneficial in automating and accelerating tasks that are traditionally labor-intensive and time-consuming for humans. Applications in astrophysics span a wide range of areas, including exoplanet detection, gravitational wave analysis, galaxy classification, and transient event identification. By employing advanced techniques such as deep learning, supervised learning, clustering, and anomaly detection, researchers can extract meaningful patterns from large and often noisy datasets, gaining critical insights into the dynamic and diverse nature of celestial phenomena. Machine learning techniques play a pivotal role in addressing challenges associated with the analysis of big data in astronomy, for instance, supervised learning aids in classifying stellar types while clustering algorithms group similar galaxies based on their properties. Additionally, anomaly detection algorithms help identify ...