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Generating conjectures on fundamental constants with the Ramanujan Machine


Fundamental mathematical constants such as e and π are ubiquitous in diverse fields of science, from abstract mathematics and geometry to physics, biology and chemistry1,2. Nevertheless, for centuries new mathematical formulas relating fundamental constants have been scarce and usually discovered sporadically3,4,5,6. Such discoveries are often considered an act of mathematical ingenuity or profound intuition by great mathematicians such as Gauss and Ramanujan7. Here we propose a systematic approach that leverages algorithms to discover mathematical formulas for fundamental constants and helps to reveal the underlying structure of the constants. We call this approach ‘the Ramanujan Machine’. Our algorithms find dozens of well known formulas as well as previously unknown ones, such as continued fraction representations of π, e, Catalan’s constant, and values of the Riemann zeta function. Several conjectures found by our algorithms were (in retrospect) simple to prove, whereas others remain as yet unproved. We present two algorithms that proved useful in finding conjectures: a variant of the meet-in-the-middle algorithm and a gradient descent optimization algorithm tailored to the recurrent structure of continued fractions. Both algorithms are based on matching numerical values; consequently, they conjecture formulas without providing proofs or requiring prior knowledge of the underlying mathematical structure, making this methodology complementary to automated theorem proving8,9,10,11,12,13. Our approach is especially attractive when applied to discover formulas for fundamental constants for which no mathematical structure is known, because it reverses the conventional usage of sequential logic in formal proofs. Instead, our work supports a different conceptual framework for research: computer algorithms use numerical data to unveil mathematical structures, thus trying to replace the mathematical intuition of great mathematicians and providing leads to further mathematical research.

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Fig. 1: Conceptual flow of the wider concept of the Ramanujan Machine.
Fig. 2: The Meet-In-The-Middle Regular Formula algorithm.
Fig. 3: The Descent&Repel algorithm.
Fig. 4: Efficient computation of the Catalan constant with new PCFs.

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Data availability

All the results of the Ramanujan Machine project are shared in the paper, with newer updates appearing periodically on the project website.

Code availability

Code is available at: and the GitHub links therein.


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We thank M. Soljačić, B. Weiss, D. Soudry and D. Carmon for helpful discussions. I.K. is grateful for the support of R. Magid and B. Magid and for the support of the Azrieli Faculty Fellowship. Y.M. acknowledges the support and guidance of the Israeli Alpha Program for Excellent High-School Students.

Author information

Authors and Affiliations



G.R., G.P. and I.K. implemented the first proof-of-concept algorithms. G.R. implemented the first generation MITM-RF algorithm. S.G. and Y. Harris implemented the state-of-the-art MITM-RF algorithm. S.G. made the developments that led to the discovery of the ζ(3) and Catalan PCFs. Y.M. implemented the Descent&Repel algorithm. Y.M., S.G., U.M. and I.K found how to convert the Catalan PCFs into expressions with record approximation exponents and fast convergence rates. U.M., Y.M., G.R., S.G., Y. Harris and I.K. proposed parts of the algorithms and developed proofs for some of the conjectures. D.H. and Y. Hadad developed the online community. Y. Hadad, G.P. and I.K. came up with the conceptual flow of the wider concept. I.K. conceived the idea and led the research. All authors provided substantial input to all aspects of the project and to the writing of the paper.

Corresponding author

Correspondence to Ido Kaminer.

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The authors declare no competing interests.

Additional information

Peer review information Nature thanks Yang-Hui He, Doron Zeilberger and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Convergence rates of the PCFs.

The plots present the absolute difference between the PCF value and the corresponding fundamental constant (that is, the error) versus the number of terms calculated in the PCF. On the left are PCFs with exponential/super-exponential convergence rates, and on the right are PCFs that converge polynomially. The majority of previously known PCFs for π converge polynomially, whereas all of our newly found results converge exponentially.

Extended Data Table 1 RFs for π and e found in a proof-of-concept run of the Descent&Repel algorithm

Supplementary information

Supplementary Information

This file contains Supplementary Sections A–G, 6 Supplementary Tables, and a Supplementary Figure. The first section provides the results found by the Ramanujan Machine algorithms. The last section provides the new findings about the Catalan constant.

Peer Review File

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Raayoni, G., Gottlieb, S., Manor, Y. et al. Generating conjectures on fundamental constants with the Ramanujan Machine. Nature 590, 67–73 (2021).

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