From Euler to AI: Unifying Formulas for Mathematical Constants
Raz, Tomer, Shalyt, Michael, Leibtag, Elyasheev, Kalisch, Rotem, Hadad, Yaron, Kaminer, Ido
–arXiv.org Artificial Intelligence
The constant $\pi$ has fascinated scholars for centuries, inspiring the derivation of countless formulas rooted in profound mathematical insight. This abundance of formulas raises a question: Are they interconnected, and can a unifying structure explain their relationships? We propose a systematic methodology for discovering and proving formula equivalences, leveraging modern large language models, large-scale data processing, and novel mathematical algorithms. Analyzing 457,145 arXiv papers, over a third of the validated formulas for $\pi$ were proven to be derivable from a single mathematical object - including formulas by Euler, Gauss, Lord Brouncker, and newer ones from algorithmic discoveries by the Ramanujan Machine. Our approach extends to other constants, such as $e$, $\zeta(3)$, and Catalan's constant, proving its broad applicability. This work represents a step toward the automatic unification of mathematical knowledge, laying a foundation for AI-driven discoveries of connections across scientific domains.
arXiv.org Artificial Intelligence
Feb-24-2025
- Country:
- Africa > Mali (0.04)
- Asia > Middle East
- Israel > Haifa District > Haifa (0.04)
- Europe > Monaco (0.04)
- North America > United States
- California > San Diego County > San Diego (0.04)
- Genre:
- Research Report (0.67)
- Industry:
- Information Technology (0.34)
- Technology: