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This paper introduces GRAFT-ATHENA, a self-improving agentic framework that autonomously discovers and evolves numerical algorithms for scientific problems. It demonstrates near-machine-precision accuracy on physics-informed machine learning benchmarks and successfully tackles complex engineering challenges.