ID: 2012.04084

Machine-Learning Arithmetic Curves

December 7, 2020

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Yang-Hui He, Kyu-Hwan Lee, Thomas Oliver
Mathematics
High Energy Physics - Theory
Statistics
Number Theory
Machine Learning

We show that standard machine-learning algorithms may be trained to predict certain invariants of low genus arithmetic curves. Using datasets of size around one hundred thousand, we demonstrate the utility of machine-learning in classification problems pertaining to the BSD invariants of an elliptic curve (including its rank and torsion subgroup), and the analogous invariants of a genus 2 curve. Our results show that a trained machine can efficiently classify curves according to these invariants with high accuracies (>0.97). For problems such as distinguishing between torsion orders, and the recognition of integral points, the accuracies can reach 0.998.

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