AI for Physics

1. Auflage 2022
ISBN: 978-1-03-215169-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 147 Seiten, Format (B × H): 125 mm x 194 mm, Gewicht: 168 g

Reihe: AI for Everything

Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.

Zielgruppe

General, Postgraduate, Professional, and Undergraduate Advanced

Autoren/Hrsg.

Knecht, Volker

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Naturwissenschaften Physik Quantenphysik Atom- und Molekülphysik
• Naturwissenschaften Physik Physik Allgemein
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein EDV & Informatik: Geschichte
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Naturwissenschaften Biowissenschaften Angewandte Biologie Biophysik

Inhaltsverzeichnis

Part I: Opening 1. Gathering the Team 2. Teamplay 3. The Rules of the Game Part II: Machine-Learning the World from Subatomic to Cosmic Scales 4. AI for Particle Physics 5. AI for Molecular Physics 6. AI for Condensed Matter Physics 7. AI for Cosmology Part III: Showdown 8. AI for Theory of Everything 9. Conclusion and Outlook

Über Autor(innen)

Volker Knecht, Germany, Editor at International Journal of Molecular Sciences, Science Writer as Freelancer. Diploma in Physics at University of Kaiserslautern, PhD in Theoretical Physics at University of Göttingen, PhD project at MPI Göttingen, postdoc at University of Groningen, group leader and PI at MPI Potsdam and University of Freiburg. Research at the interface between physics, chemistry, biology, and computer science for 17 years.