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Theoretical physics with generative AI
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AI
DOI：10.1142/S0217751X2650065X.png)
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Abstract
En 中文
Large Language Models (LLMs) can make nontrivial contributions to math and physics, if used properly. Separate model instances used to Generate and Verify research steps produce more reliable results than single-shot inference. As a specific example, I describe the use of AI in recent research in quantum field theory (Tomonaga-Schwinger integrability conditions applied to state-dependent modifications of quantum mechanics), work now accepted for publication in Physics Letters B after peer review. Remarkably, the main idea in the paper originated de novo from GPT-5. GPT-5, Gemini and Qwen-Max were used extensively to perform calculations, find errors and generate the finished paper.
Keywords:
Artificial intelligence
quantum mechanics
Quantum Field Theory
relativistic invariance
Tomonaga-Schwinger formulation of Quantum Field Theory
Journal
I
IF:
1.2
Papers:
176
Citations:
0