Autonomous Algorithm Discovery for Ptychography via Evolutionary LLM Reasoning

• URL: http://arxiv.org/abs/2603.05696v1
• Date: Thu, 05 Mar 2026 21:39:57 GMT
• Title: Autonomous Algorithm Discovery for Ptychography via Evolutionary LLM Reasoning
• Abstract summary: Ptychi-Evolve is an autonomous framework that uses large language models to discover and evolve novel regularization algorithms.<n>We show that discovered regularizers outperform conventional reconstructions, achieving up to +0.26 SSIM and +8.3dB PSNR improvements.
• Score: 13.312986731075753
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Ptychography is a computational imaging technique widely used for high-resolution materials characterization, but high-quality reconstructions often require the use of regularization functions that largely remain manually designed. We introduce Ptychi-Evolve, an autonomous framework that uses large language models (LLMs) to discover and evolve novel regularization algorithms. The framework combines LLM-driven code generation with evolutionary mechanisms, including semantically-guided crossover and mutation. Experiments on three challenging datasets (X-ray integrated circuits, low-dose electron microscopy of apoferritin, and multislice imaging with crosstalk artifacts) demonstrate that discovered regularizers outperform conventional reconstructions, achieving up to +0.26 SSIM and +8.3~dB PSNR improvements. Besides, Ptychi-Evolve records algorithm lineage and evolution metadata, enabling interpretable and reproducible analysis of discovered regularizers.

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