This research combines Large Language Models with genetic algorithms to dramatically improve computational physics calculations.

• Developed a novel priority function using the FunSearch algorithm
• Achieved significant reductions in memory usage and computational requirements
• Made previously intractable physics problems more manageable
• Demonstrated practical integration of AI with theoretical physics

For engineering teams, this approach showcases how AI can optimize complex computational workflows beyond traditional methods, potentially enabling breakthroughs in fields requiring intensive calculations.

Explainable AI-assisted Optimization for Feynman Integral Reduction