Quantitative analysis of critical-window profiles for autocatalytic emergence

Primarily AI-generated textHuman understanding: some partsmath.PR — Probability

Contributed by Michael Mislan ↗

Version 1 / Oct 17, 2026 / CC BY 4.0

Abstract

The critical-window law for reflexively autocatalytic and food-generated (RAF) sets in the reversible binary-polymer model states that, when the mean number of reactions catalysed per molecule grows like λn\lambda n, the RAF probability converges to Sν(1−e−λ)S_\nu(1-\mathrm{e}^{-\lambda}), where SνS_\nu is the probability that ordinary reversible closure of the food set is unbounded in an infinite field of independently open reaction channels. The law is known for the ordered split-position catalogue (ν=sp\nu=\mathrm{sp}) and for the commuting-factor quotient catalogue (ν=qt\nu=\mathrm{qt}). It is an existence theorem: it names the limit but says nothing effective about its value, its shape near zero, or what a finite network actually does. This paper answers those three questions. For both profiles, a construction gives a terminating algorithm which, given rational openness aa and rational tolerance ε\varepsilon, returns a rational interval of width below ε\varepsilon containing Sν(a)S_\nu(a), with an explicit approximation error 1/m+(2L+1−2)(1−aL+1)r1/m+(2^{L+1}-2)(1-a^{L+1})^r for a computable seed length LL and record index rr, uniform on every openness interval bounded away from zero. The key estimate is a finite-cap record contraction proved without conditioning on survival and without independence between repair attempts. Second, tracking total word length along productive closure histories replaces a coefficient of order (Jr)\binom{J}{r} over enormous channel caps by Crν≤36r2r(r−1)/2C_r^\nu\le36^r2^{r(r-1)/2}, giving log⁡Sν(a)≤−log⁡2(1/a)/(2log⁡2)+O(log⁡(1/a))\log S_\nu(a)\le-\log^2(1/a)/(2\log2)+O(\log(1/a)) and exact certificates such as Sν(10−20)<10−629S_\nu(10^{-20})<10^{-629}. Third, at fixed word length nn the probability that some singleton RAF exists is exactly 1−(1−p)2481-(1-p)^{248} (split) or 1−(1−p)2341-(1-p)^{234} (quotient), so the finite RAF probability is linear in pp at zero while the limiting profile is flatter than every power; this order-of-limits effect is quantified with rational two-sided predictions and two fully explicit examples at n=16n=16. Further results give strict monotonicity of the profile, an effective global modulus of continuity, terminating inverse-probability brackets, and non-analyticity at zero. The effective evaluator, its error contract with the finite catalytic model and productive-history extraction are checked in Lean~4; the printed numerical bounds are checked by the accompanying replay script; the sharper counting theorem, the singleton law and the regularity results have conventional proofs and are labelled as such.

Provenance statement

The text is primarily AI-generated. AI systems assisted the mathematical development, computations and Lean formalization under human direction; human understanding covers some parts of the work.

Formalizations

References

  1. de Moura, Leonardo; Ullrich, Sebastian. The Lean 4 theorem prover and programming language. Automated Deduction – CADE 28, vol. 12699, pp. 625–635. 2021DOI
  2. Eigen, Manfred. Selforganization of matter and the evolution of biological macromolecules. Naturwissenschaften, vol. 58, no. 10, pp. 465–523. 1971DOI
  3. Grimmett, Geoffrey. Percolation. Springer, vol. 321. 1999DOI
  4. Harris, Theodore E. A lower bound for the critical probability in a certain percolation process. Mathematical Proceedings of the Cambridge Philosophical Society, vol. 56, no. 1, pp. 13–20. 1960DOI
  5. Hordijk, Wim; Hein, Jotun; Steel, Mike. Autocatalytic sets and the origin of life. Entropy, vol. 12, no. 7, pp. 1733–1742. 2010DOI
  6. Hordijk, Wim; Kauffman, Stuart A.; Steel, Mike. Required levels of catalysis for emergence of autocatalytic sets in models of chemical reaction systems. International Journal of Molecular Sciences, vol. 12, no. 5, pp. 3085–3101. 2011DOI
  7. Hordijk, Wim; Smith, Joshua I.; Steel, Mike. Algorithms for detecting and analysing autocatalytic sets. Algorithms for Molecular Biology, vol. 10, pp. 15. 2015DOI
  8. Hordijk, Wim; Steel, Mike. Detecting autocatalytic, self-sustaining sets in chemical reaction systems. Journal of Theoretical Biology, vol. 227, no. 4, pp. 451–461. 2004DOI
  9. Hordijk, Wim; Steel, Mike. Autocatalytic sets in polymer networks with variable catalysis distributions. Journal of Mathematical Chemistry, vol. 54, no. 10, pp. 1997–2021. 2016DOI
  10. Hordijk, Wim; Steel, Mike. Chasing the tail: The emergence of autocatalytic networks. Biosystems, vol. 152, pp. 1–10. 2017DOI
Show all 24 referencesShow fewer references
  1. Hordijk, Wim; Steel, Mike; Kauffman, Stuart. The structure of autocatalytic sets: Evolvability, enablement, and emergence. Acta Biotheoretica, vol. 60, no. 4, pp. 379–392. 2012DOI
  2. Hordijk, Wim; Steel, Mike; Kauffman, Stuart A. Molecular diversity required for the formation of autocatalytic sets. Life, vol. 9, no. 1, pp. 23. 2019DOI
  3. Kauffman, Stuart A. Autocatalytic sets of proteins. Journal of Theoretical Biology, vol. 119, no. 1, pp. 1–24. 1986DOI
  4. Kauffman, Stuart A. The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press. 1993
  5. Lothaire, M. Combinatorics on Words. Cambridge University Press. 1997DOI
  6. Lyndon, Roger C.; Schützenberger, Marcel-Paul. The equation aM=bNcPa^M=b^Nc^P in a free group. Michigan Mathematical Journal, vol. 9, no. 4, pp. 289–298. 1962DOI
  7. Mislan, Michael. A nontrivial critical window for autocatalytic emergence in the binary polymer model. 2026. Preprint, version 1.0, 16 October 2026. Zenodo. https://doi.org/10.5281/zenodo.23422223DOI
  8. Mossel, Elchanan; Steel, Mike. Random biochemical networks: the probability of self-sustaining autocatalysis. Journal of Theoretical Biology, vol. 233, no. 3, pp. 327–336. 2005DOI
  9. Steel, Mike. The emergence of a self-catalysing structure in abstract origin-of-life models. Applied Mathematics Letters, vol. 13, no. 3, pp. 91–95. 2000DOI
  10. Steel, Mike; Hordijk, Wim; Xavier, Joana C. Autocatalytic networks in biology: structural theory and algorithms. Journal of the Royal Society Interface, vol. 16, no. 151, pp. 20180808. 2019DOI
  11. The mathlib Community. The Lean mathematical library. Proceedings of the 9th ACM SIGPLAN International Conference on Certified Programs and Proofs (CPP 2020), pp. 367–381. 2020DOI
  12. Varanasi, Varun. Emergence-of-Autocatalysis-in-Prebiotic-Reaction-Networks: public source and data repository. 2026. Reaction generator and catalysis sampler; immutable commit 314f1e664cd7a8ccc97eed950f28d33311d0b5ef. https://github.com/VJ-Varanasi/Emergence-of-Autocatalysis-in-Prebiotic-Reaction-Networks/tree/314f1e664cd7a8ccc97eed950f28d33311d0b5eflink
  13. Varanasi, Varun; Korenaga, Jun. Emergence of autocatalysis in prebiotic reaction networks. Physical Review E, vol. 113, pp. 044304. 2026DOI
  14. Weihrauch, Klaus. Computable Analysis: An Introduction. Springer. 2000DOI

Version history

  1. v1Submitted by Michael MislanInitial depositCurrentOct 17, 2026