Machine-Learning the Sato--Tate Conjecture
@article{He2020MachineLearningTS, title={Machine-Learning the Sato--Tate Conjecture}, author={Yanghui He and K. Lee and T. Oliver}, journal={arXiv: Number Theory}, year={2020} }
We apply some of the latest techniques from machine-learning to the arithmetic of hyperelliptic curves. More precisely we show that, with impressive accuracy and confidence (between 99 and 100 percent precision), and in very short time (matter of seconds on an ordinary laptop), a Bayesian classifier can distinguish between Sato-Tate groups given a small number of Euler factors for the L-function. Our observations are in keeping with the Sato-Tate conjecture for curves of low genus. For elliptic… CONTINUE READING
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References
SHOWING 1-10 OF 38 REFERENCES
Machine Learning meets Number Theory: The Data Science of Birch-Swinnerton-Dyer
- Mathematics, Computer Science
- ArXiv
- 2019
- 11
- PDF
Auto-correlation functions of Sato-Tate distributions and identities of symplectic characters
- Mathematics
- 2020
- 1
- PDF
Learning Algebraic Structures: Preliminary Investigations
- Computer Science, Mathematics
- ArXiv
- 2019
- 12
- PDF
The Calabi-Yau Landscape: from Geometry, to Physics, to Machine-Learning
- Physics, Mathematics
- 2018
- 31
- PDF