AI and the Research-Education Environment of Physics

2026/05/04 by Savannah Thais, Koji Hashimoto, David S. Berman +6 · 1 voice
Physics and Astronomy · #physics.ed-ph #physics.comp-ph #physics.soc-ph

paper · pdf

Abstract

In the current era of AI transforming the research-education environment of physics, variety of issues and concerns arise. The KITP program "Generative AI for High and Low Energy Physics'' offered a discussion session on this, and here presented is a summary of the opinions provided in the discussion. The material is formulated such that it can serve as a starting point for further discussions in readers' research community/institution/group.

Citations

• GPQA: A Graduate-Level Google-Proof Q&A Benchmark
• Applications of Machine Learning to Lattice Quantum Field Theory
• Physics-informed machine learning
• A Living Review of Machine Learning for Particle Physics
• Attention Is All You Need
• Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
• Solving the Quantum Many-Body Problem with Artificial Neural Networks

Discussions

• Thais, Hashimoto, Berman, Inack, Howard, Kasieczka, Maiti, Merz, Toledo: AI and the Research-Education Environment of Physics https://arxiv.org/abs/2605.03185 https://arxiv.org/pdf/2605.03185 https:// [bsky, 0 points, 0 comments]

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