arXiv paper explores ML for classifying rational maps

A new paper on arXiv explores surjective rational endomorphisms of the projective plane, specifically focusing on those with cubic terms and a non-empty indeterminacy locus. The research utilizes an experimental approach, incorporating Python programming and machine learning techniques to aid in the classification of these maps. The study also includes a proof demonstrating that a general non-regular cubic endomorphism is surjective if and only if its indeterminacy locus contains at least three points. AI

IMPACT This research applies machine learning to a specific area of algebraic geometry, potentially opening new avenues for computational mathematics.

RANK_REASON The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]

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• arXiv
• Hugging Face
• Ilya Karzhemanov
• Python

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