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arXiv · 2012.04084

Machine-Learning Arithmetic Curves

Abstract

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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Yang-Hui He, Kyu-Hwan Lee, Thomas Oliver. 2020-12-07. Machine-Learning Arithmetic Curves. https://doi.org/10.1016/j.jsc.2022.08.017

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