The Intelligent Universe

AI's Role in Astronomy
1. Auflage 2025
ISBN: 978-1-394-35548-8
Verlag: John Wiley & Sons Inc

Buch, Englisch, 528 Seiten, Format (B × H): 239 mm x 158 mm, Gewicht: 868 g

Uncover the universe’s secrets with this essential guide that provides a comprehensive exploration of how artificial intelligence is revolutionizing modern astronomical research.

Artificial intelligence (AI) is revolutionizing astronomy, enabling researchers to process vast datasets, uncover hidden patterns, and enhance observational precision like never before. This book explores this transformative synergy, bringing together insights from experts across the globe. Covering a wide spectrum of topics, including AI-driven data mining, exoplanet discovery, gravitational wave detection, and autonomous observatories, this book highlights the impact of machine learning, computer vision, and big data analytics on modern astrophysical research.

From detecting transient celestial events to refining cosmic evolution models, this volume delves into the ways AI is reshaping our understanding of the cosmos. As we enter a new era of discovery, this guide serves as both a foundational reference and a forward-looking exploration of AI’s expanding role in space science. Whether you are a student, researcher in astronomy or space science, or an AI practitioner, this book offers an invaluable resource on the frontiers of AI-driven astronomical research.

Readers will find this volume: - Provides a balanced mix of fundamental concepts, practical applications, and future perspectives;
- Designed to be informative and approachable, combining scientific insights, high-quality images, and detailed analyses to enhance understanding;
- Explores how AI is transforming space exploration, telescope automation, and cosmic data processing, providing readers a future-focused perspective.

Audience

Academics, researchers, astronomers, astrophysicists, and industry professionals interested in the transformative power of AI for astrological applications.

Autoren/Hrsg.

Chandra, Yogesh

Panda, Manjuleshwar

Mathpal, Mahesh Chandra

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Naturwissenschaften Astronomie Astronomie: Allgemeines

Inhaltsverzeichnis

Foreword xxv
Preface xxvii
Acknowledgement xxxi

Part I: Foundations and Core Applications of AI in Astronomy 1

1 Introduction to AI in Astronomy 3
Rahul Barnwal, Aman Kumar, Kala S. and Sree Ranjani Rajendran

1.1 Introduction 4
1.2 Understanding AI: Key Concepts and Techniques 6
1.3 Fundamentals of Deep Learning 8
1.4 AI Algorithms Shaping Astronomical Research 14
1.5 Revolutionizing Data Analysis: AI in Astronomical Surveys 18
1.6 Machine Learning Models for Celestial Object Classification 21
1.7 AI in Observational Astronomy: Transforming Telescopic Data 24
1.8 Harnessing AI for Space Exploration and Planetary Science 26
1.9 AI-Driven Discoveries: Case Studies in Astronomy 29
1.10 Challenges and Limitations of AI in Astronomy 32
1.11 The Future of AI in Astronomy: Opportunities and Horizons 34
1.12 Conclusion 41

2 Data Mining and Machine Learning in Astrophysics 47
Gissmol Saji and Sanjay Singh Bisht

2.1 Introduction 48
2.2 Foundations of Data Mining and Machine Learning 50
2.3 Machine Learning Applications in Astrophysics 55
2.4 Role of Machine Learning in Key Astrophysical Research Areas 58
2.5 Challenges in the Era of Big Data 75
2.6 Bridging Observations and Theory 77
2.7 The Future: Autonomous Observatories and Predictive Models 79
2.8 Conclusion 81

3 The Role of Artificial Intelligence in the Discovery and Characterization of Exoplanets 87
Shraddha. Biswas, D. Bisht and Ing-Guey Jiang

3.1 Introduction 88
3.2 Exoplanet Discovery 89
3.3 Naming Rules/Nomenclature 92
3.4 Types of Exoplanets 92
3.5 Detection Methods 98
3.6 Missions Launched to Detect Exoplanets 112
3.7 Role of Artificial Intelligence in Exoplanetary Science 117
3.8 Conclusion 123

4 Cosmology and Dark Matter Research 129
Arun Kumar Rathore, B. C. Chanyal and Sirley Marques-Bonham

4.1 Introduction 130
4.2 Role of Dark Matter in the Cosmos 133
4.3 Future Cosmological Observations 133
4

Über Autor(innen)

Yogesh Chandra, PhD is an assistant professor of physics at the Government Post Graduate College, Bazpur, Kumaun University, India. He has published several journal articles, mentored many students, and attended a number of conferences and workshops. He specializes in astronomy, astrophysics, and atmospheric science, with a focus on AI applications in these fields.

Manjuleshwar Panda is an independent astronomy researcher in New Delhi, India, with an M.Sc. in Physics from Kumaun University, Nainital, India. He has contributed to national and international research programs and has completed two specialized courses with the Indian Space Research Organization. He has a keen interest in observational and extragalactic astronomy, high-energy astrophysics, and the role of AI in astronomy.

Mahesh Chandra Mathpal, PhD is a lecturer in physics at Govt. IC Lohali, Uttarakhand, India. He has published over ten research papers in international journals and is actively engaged in advancing AI-driven astrophysical studies. His research focuses on astrophysics and solar physics, with a specialization in applying artificial neural networks (ANN) to these fields.