TITLE:
Artificial Intelligence in Multi-Messenger Astronomy
AUTHORS:
Rashi Pandey, Sananjay Biswas
KEYWORDS:
Multi-Messenger Astronomy, Artificial Intelligence, Machine Learning, Gravitational Waves, Astrophysical Data Analysis
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.14 No.9,
September
15,
2026
ABSTRACT: The arrival of multi-messenger astronomy has marked a breakthrough in astronomy thanks to the ability to simultaneously observe astrophysical events using electromagnetic waves, gravitational waves, neutrinos, and cosmic rays. The increasing sensitivity of modern observatories has produced an explosion in the amount and diversity of astronomical data, requiring novel solutions to cope with data analysis challenges in real time. Artificial intelligence (AI), which encompasses machine and deep learning as well as physics-informed approaches, has been demonstrated to be an enabling technology to tackle these issues. Nowadays, AI methods have become a central piece within the whole process of multi-messenger astronomy, involving the use of such methods in the different phases: from detecting the presence of a signal, filtering out the noise, classifying the type of event, estimating its parameters, localizing the source, to carrying out follow-up observations. This review presents an introduction to the application of AI for multi-messenger astronomy, showcasing current advances, applications, and main problems that can be found when dealing with this technology for data analysis purposes in multi-messenger astronomy.