Skip to main content

Computing Threshold Circuits with Void Reactions in Step Chemical Reaction Networks

  • Conference paper
  • First Online:
Machines, Computations, and Universality (MCU 2024)

Abstract

We introduce a new model of step Chemical Reaction Networks (step CRNs), motivated by the step-wise addition of materials in standard lab procedures. Step CRNs have ordered reactants that transform into products via reaction rules over a series of steps. We study an important subset of weak reaction rules, void rules, in which chemical species may only be deleted but never changed. We demonstrate the capabilities of these simple limited systems to simulate threshold circuits and compute functions using various configurations of rule sizes and step constructions, and prove that without steps, void rules are incapable of these computations, which further motivates the step model. Additionally, we prove the coNP-completeness of verifying if a given step CRN computes a function, holding even for O(1) step systems.

This research was supported in part by National Science Foundation Grant CCF-2329918.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    We assume that \(f(\cdot )\) is given in the form of a circuit \(c_f\). We leave as future work the complexity of other representations such as a truth table.

References

  1. Alaniz, R.M., et al.: Reachability in restricted chemical reaction networks (2022). arXiv:2211.12603

  2. Anderson, R., et al.: Computing threshold circuits with bimolecular void reactions in step chemical reaction networks. In: Proceedings of the 21st International Conference on Unconventional Computation and Natural Computation, UCNC 2024 (2024, to appear)

    Google Scholar 

  3. Angluin, D., Aspnes, J., Diamadi, Z., Fischer, M.J., Peralta, R.: Computation in networks of passively mobile finite-state sensors. Disturb. Comput. 18(4), 235–253 (2006). https://doi.org/10.1007/s00446-005-0138-3

    Article  MATH  Google Scholar 

  4. Angluin, D., Aspnes, J., Eisenstat, D.: A simple population protocol for fast robust approximate majority. Distrib. Comput. 21, 87–102 (2008)

    Article  MATH  Google Scholar 

  5. Angluin, D., Aspnes, J., Eisenstat, D., Ruppert, E.: The computational power of population protocols. Distrib. Comput. (2007)

    Google Scholar 

  6. Aris, R.: Prolegomena to the rational analysis of systems of chemical reactions. Arch. Ration. Mech. Anal. 19(2), 81–99 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  7. Aris, R.: Prolegomena to the rational analysis of systems of chemical reactions II. Some addenda. Arch. Ration. Mech. Anal. 27(5), 356–364 (1968)

    Article  MathSciNet  MATH  Google Scholar 

  8. Arkin, A., Ross, J.: Computational functions in biochemical reaction networks. Biophys. J . 67(2), 560–578 (1994)

    Article  MATH  Google Scholar 

  9. Aviram, A.: Molecules for memory, logic, and amplification. J. Am. Chem. Soc. 110(17), 5687–5692 (1988)

    Article  MATH  Google Scholar 

  10. Cardelli, L., Kwiatkowska, M., Whitby, M.: Chemical reaction network designs for asynchronous logic circuits. Nat. Comput. 17, 109–130 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  11. Cardelli, L., Tribastone, M., Tschaikowski, M.: From electric circuits to chemical networks. Nat. Comput. 19, 237–248 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  12. Chen, H.L., Doty, D., Soloveichik, D.: Deterministic function computation with chemical reaction networks. Nat. Comput. 13(4), 517–534 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  13. Cook, M., Soloveichik, D., Winfree, E., Bruck, J.: Programmability of chemical reaction networks. In: Algorithmic Bioprocesses, pp. 543–584. Springer, Cham (2009)

    Google Scholar 

  14. Dalchau, N., Chandran, H., Gopalkrishnan, N., Phillips, A., Reif, J.: Probabilistic analysis of localized DNA hybridization circuits. ACS Synth. Biol. 4(8), 898–913 (2015)

    Article  MATH  Google Scholar 

  15. Ellis, S.J., Klinge, T.H., Lathrop, J.I.: Robust chemical circuits. Biosystems 186, 103983 (2019)

    Article  MATH  Google Scholar 

  16. Fan, D., Wang, J., Han, J., Wang, E., Dong, S.: Engineering DNA logic systems with non-canonical DNA-nanostructures: basic principles, recent developments and bio-applications. Sci. China Chem. 65(2), 284–297 (2022)

    Article  MATH  Google Scholar 

  17. Hjelmfelt, A., Weinberger, E.D., Ross, J.: Chemical implementation of neural networks and turing machines. Proc. Natl. Acad. Sci. 88(24), 10983–10987 (1991)

    Article  MATH  Google Scholar 

  18. Jiang, H., Riedel, M.D., Parhi, K.K.: Digital logic with molecular reactions. In: International Conference on Computer-Aided Design, ICCAD 2013, pp. 721–727. IEEE (2013)

    Google Scholar 

  19. Karp, R.M., Miller, R.E.: Parallel program schemata. J. Comput. Syst. Sci. 3(2), 147–195 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  20. Mailloux, S., Guz, N., Zakharchenko, A., Minko, S., Katz, E.: Majority and minority gates realized in enzyme-biocatalyzed systems integrated with logic networks and interfaced with bioelectronic systems. J. Phys. Chem. B 118(24), 6775–6784 (2014)

    Article  Google Scholar 

  21. Petri, C.A.: Kommunikation mit Automaten. Ph.D. thesis, Rheinisch-Westfälischen Institutes für Instrumentelle Mathematik an der Universität Bonn (1962)

    Google Scholar 

  22. Qian, L., Winfree, E.: Scaling up digital circuit computation with DNA strand displacement cascades. Science 332(6034), 1196–1201 (2011)

    Article  MATH  Google Scholar 

  23. Qian, L., Winfree, E.: A simple DNA gate motif for synthesizing large-scale circuits. J. R. Soc. Interface 8(62), 1281–1297 (2011)

    Article  MATH  Google Scholar 

  24. Sergeev, I.S.: Upper bounds for the formula size of symmetric Boolean functions. Russ. Math. 58, 30–42 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  25. Soloveichik, D., Cook, M., Winfree, E., Bruck, J.: Computation with finite stochastic chemical reaction networks. Nat. Comput. 7(4), 615–633 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  26. Soloveichik, D., Seelig, G., Winfree, E.: DNA as a universal substrate for chemical kinetics. Proc. Natl. Acad. Sci. 107(12), 5393–5398 (2010)

    Article  MATH  Google Scholar 

  27. Thachuk, C., Condon, A.: Space and energy efficient computation with DNA strand displacement systems. In: International Workshop on DNA-Based Computers (2012)

    Google Scholar 

  28. Wang, B., Thachuk, C., Ellington, A.D., Winfree, E., Soloveichik, D.: Effective design principles for leakless strand displacement systems. Proc. Natl. Acad. Sci. 115(52), E12182–E12191 (2018)

    Article  MATH  Google Scholar 

  29. Winfree, E.: Chemical reaction networks and stochastic local search. In: DNA Computing and Molecular Programming, DNA 2019. Springer (2019)

    Google Scholar 

  30. Xiao, W., Zhang, X., Zhang, Z., Chen, C., Shi, X.: Molecular full adder based on DNA strand displacement. IEEE Access 8, 189796–189801 (2020)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tim Wylie .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Anderson, R. et al. (2025). Computing Threshold Circuits with Void Reactions in Step Chemical Reaction Networks. In: Formenti, E., Durand-Lose, J. (eds) Machines, Computations, and Universality. MCU 2024. Lecture Notes in Computer Science, vol 15270. Springer, Cham. https://doi.org/10.1007/978-3-031-81202-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-81202-6_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-81201-9

  • Online ISBN: 978-3-031-81202-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics