AI Meets Theoretical Physics

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• Dr Sven-Ludwig Krippendorf (Physics/DAMTP)
• Thursday 21 November 2024, 14:00-15:00
• Maxwell Centre.

If you have a question about this talk, please contact Sri Aitken.

Maxwell Centre

In this talk I present an overview of our work at the intersection of theoretical physics and machine learning. This is to outline how we can use ML to automatize the pen and paper methods of theoretical physicists. I present some examples on this journey which include: 1) Utilizing the unreasonable effectiveness of mathematics we can identify analytical expressions for symmetries of a system. 2) Formulating the search for solutions to partial differential equations as an optimization problem, we get an unprecedented look into Calabi-Yau metrics. 3) Rendering efficient numerical tools to study the physics of string theory models using automatic differentiation, vectorization and just in time compilation. In the second part of the talk I give an overview on how we get insights into the dynamics of neural network using collective variables.

This talk is part of the Data Intensive Science Seminar Series series.

This talk is included in these lists:

• Cambridge Astronomy Talks
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge talks
• Chris Davis' list
• Combined External Astrophysics Talks DAMTP
• Cosmology, Astrophysics and General Relativity
• Institute of Astronomy Extra Talks
• Institute of Astronomy Talk Lists
• Interested Talks
• Maxwell Centre
• Titel: TBC
• Trust & Technology Initiative - interesting events
• bld31
• ndk22's list
• ob366-ai4er
• rp587

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