arXiv paper: Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery submitted

The arXiv paper titled Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery was submitted in the Computer Science Artificial Intelligence category. It describes a neuro-symbolic system that pairs the Gemini Deep Think large language model with a Tree Search framework and automated numerical feedback. The system autonomously solved an open problem To support claims of AI-accelerated discovery the paper details system prompts, search constraints and intermittent feedback loops. The agent identified six different analytical methods. The most elegant approach expands the kernel in Gegenbauer polynomials C sub l to the power 3/2 to absorb the integrand's singularities. The methods produce an asymptotic result for I(N, alpha) at large N. This result agrees with numerical findings and connects to the continuous Feynman parameterization of Quantum Field Theory. The paper outlines both the algorithmic methodology and the mathematical derivations.