Automated Search for Conjectures on Mathematical Constants using Analysis of Integer Sequences
Ofir Razon, Yoav Harris, Shahar Gottlieb, Dan Carmon, Ofir David, Ido Kaminer
Abstract
Formulas involving fundamental mathematical constants had a great impact on various fields of science and mathematics, for example aiding in proofs of irrationality of constants. However, the discovery of such formulas has historically remained scarce, often perceived as an act of mathematical genius by great mathematicians such as Ramanujan, Euler, and Gauss. Recent efforts to automate the discovery of formulas for mathematical constants, such as the Ramanujan Machine project, relied on exhaustive search. Despite several successful discoveries, exhaustive search remains limited by the space of options that can be covered and by the need for vast amounts of computational resources. Here we propose a fundamentally different method to search for conjectures on mathematical constants: through analysis of integer sequences. We introduce the Enumerated Signed-continuedfraction Massey Approve (ESMA) algorithm, which builds on the Berlekamp-Massey algorithm to identify patterns in integer sequences that represent mathematical constants. The ESMA algorithm found various known formulas for e, e 2 , tan(1), and ratios of values of Bessel functions. The algorithm further discovered a large number of new conjectures for these constants, some providing simpler representations and some providing faster numerical convergence than the corresponding simple continued fractions. Along with the algorithm, we present mathematical tools for manipulating continued fractions. Specifically, we present novel transformations of continued fractions with alternating positive and negative signs in the numerators, showing how to convert them to polynomial continued fractions and to simple continued fractions. These connections enable us to characterize what space of constants can be found by ESMA and quantify its algorithmic advantage in certain scenarios. Altogether, this work continues in the development of augmenting mathematical intuition by computer algorithms, to help reveal mathematical structures and accelerate mathematical research.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers2
- From Euler to AI: Unifying Formulas for Mathematical ConstantsTomer Raz, Michael Shalyt, Elyasheev Leibtag, Rotem Kalisch et al.NeurIPS 2025 · 4 citations
- The Ramanujan Library - Automated Discovery on the Hypergraph of Integer RelationsItay Beit Halachmi, Ido KaminerICLR 2025
Related papers
- Unsupervised Discovery of Formulas for Mathematical ConstantsMichael Shalyt, Uri Seligmann, Itay Beit Halachmi, Ofir David et al.NeurIPS 2024 · 2 citations
- Learning Program Synthesis for Integer Sequences from ScratchThibault Gauthier, Josef UrbanAAAI 2023 · 12 citations
- Deep symbolic regression for recurrence predictionStéphane d'Ascoli, Pierre-Alexandre Kamienny, Guillaume Lample, François ChartonICML 2022 · 22 citations
- Progressive Self-Learning for Domain Adaptation on Symbolic Regression of Integer SequencesYaohui Zhu, Kaiming Sun, Zhengdong Luo, Lingfeng WangAAAI 2025
- AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical FunctionsEsteban Real, Mirko Rossini, Connal de Souza, Manav Garg et al.ICML 2026
