AI for Physics

Written in accessible language without mathematical formulas, the book covers important machine learning algorithms and their respective applications in physics and 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.

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.

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