On linear cellular automata

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Wolfram cellular automata are considered and their operation is demonstrated using an example of traffic flow simulation. For the class of one-dimensional elementary cellular automata, the concept of linearity is introduced in the language of Zhegalkin operators. An algorithm for finding linear Zhegalkin operators with multipliers of three variables is presented. The algorithm is implemented in Python.

Full Text

Restricted Access

About the authors

V. R. Kulikov

Siberian State University

Author for correspondence.
Email: v.r.kulikov@mail.ru
Russian Federation, Krasnoyarsk

А. А. Kytmanov

MIREA – Russian Technological University

Email: aakytm@gmail.com
Russian Federation, Moscow

А. О. Poroshin

Siberian State University

Email: poroshin.012332@gmail.com
Russian Federation, Krasnoyarsk

I. V. Timofeev

Kirensky Institute of Physics, Federal Research Center KSC SB RAS; Siberian State University

Email: tiv@iph.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk

D. P. Fedchenko

Kirensky Institute of Physics, Federal Research Center KSC SB RAS; Siberian State University

Email: fdp@iph.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk

References

  1. von Neumann J. Theory of Self-Reproducing Automata, Ed. by Burks, A.W., Urbana: Illinois Univ. Press, 1966.
  2. Tsetlin M.L. Some problems of finite state machine behavior, Dokl. Akad. Nauk SSSR, 1961, vol. 139, no. 4, pp. 830–833.
  3. Conway J. et al. The game of life, Sci. Amer., vol. 223, no. 4, p. 4.
  4. Batty M. Cities as Complex systems: Scaling, interaction, networks, dynamics and urban morphologies, in Encyclopedia of Complexity and Systems Science, 2009, pp. 1041–1071.
  5. Ghosh P. et al. Application of cellular automata and Markov-chain model in geospatial environmental modeling—A review, Remote Sens. Appl.: Soc. Env., 2017, vol. 5, pp. 64–77.
  6. Introduction to Mathemetical Modeling of Traffic Flows, Ed. by Gasnikov, A. et al. Litres, 2022 [in Russian].
  7. Fronczak P. et al. Cellular automata approach to modeling self-organized periodic patterns in nanoparticle-doped liquid crystals, Phys. Rev. E., 2022, vol. 106, no. 4, p. 44705.
  8. Janssens K.G.F. An introductory review of cellular automata modeling of moving grain boundaries in polycrystalline materials, Math. Comput. in Simul., 2010, vol. 80, no. 7, pp. 1361–1381.
  9. Lemont B.K. and Seybold P.G. Cellular automata modeling of complex biochemical systems, in Encyclopedia of Complexity and Systems Science, 2015.
  10. Kozhoridze G., Dor E.B., and Sternberg M. Assessing the dynamics of plant species invasion in Eastern-Mediterranean Coastal Dunes Using Cellular Automata Modeling and Satellite Time-Series Analyses, Remote Sens., 2022, vol. 14, no. 4, p. 1014.
  11. Wolfram S. Statistical mechanics of cellular automata, Rev. Modern Phys., 1983, vol. 55, no. 3., p. 601.
  12. Wolfram S. et al. A New Kind of Science, Champaign: Wolfram Media, 2002, vol. 5, p. 130.
  13. Tomassini M., Sipper M., and Perrenoud M. On the generation of high-quality random numbers by two-dimensional cellular automata, IEEE Trans. Comput., 2000, vol. 49, no. 10, pp. 1146–1151.
  14. Walus K. et al. RAM design using quantum-dot cellular automata, NanoTechnology Conference, 2003, Vol. 2, pp. 160–163.
  15. Cagigas-Muniz D. et al. Efficient simulation execution of cellular automata on GPU, Simul. Modell. Pract. Theory, 2022, vol. 118, p. 102519.
  16. Sato T. Decidability for some problems of linear cellular automata over finite commutative rings, Inf. Proc. Lett., 993, vol 46, no. 3, pp. 151–155.
  17. Martin A. et al. Reversibility of linear cellular automata, Appl. Math. Comput., 2011, vol. 217, no. 21, pp. 8360–8366.
  18. Martin del Rey A., Casado Vara R., and Hernández S. D. Reversibility of symmetric linear cellular automata with radius r = 3, Mathematics, 2019, vol. 7, no. 9, p. 816.
  19. Zhegalkin I.I. Arithmetization of symbolic logic, Mat. Sb., vol. 35, no. 3–4, pp. 311–377.
  20. Fedchenko D.P., Novikov V.V., and Timofeev I.V. Photonic topological insulators of the Rudner type in terms of of tricolor cellular automata, Uch. Zap. Fiz. Fakul’teta MGU, 2021, No. 5, p. 2150302.
  21. Fedchenko D.P., Kim P.N., and Timofeev I.V. Photonic topological insulator based on frustrated total internal reflection in array of coupled prism resonators, Symmetry, 2022, vol. 14, no. 12, p. 2673.
  22. Gal’perin G.A. and Zemlyakov A.N. Mathematical Billiards: Billiard Problems and Related Problems of Mathematics and Mechanics, Moscow: Nauka, 1990 [in Russian].

Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1. The rule of the cellular automaton with the Wolfram code W=254.

Download (29KB)
3. Fig. 2. The first 50 cycles of a cellular automaton with the Wolfram code W= 30 with a single-point initial state.

Download (244KB)
4. Fig. 3. All the rules of the cellular automaton, for which the state of the cell depends only on the states of neighboring cells.

Download (551KB)
5. Fig. 4. An element of a transport network modeled using a cellular automaton.

Download (198KB)
6. Fig. 5. The result of modeling the congestion of the transport network.

Download (184KB)
7. Fig. 6. Actions of Zhegalkin operators with multipliers of two variables.

Download (613KB)
8. Fig. 7. Zhegalkin linear operators with multipliers of three variables.

Download (266KB)
9. Fig. 8. Algorithm 1

Download (154KB)
10. Fig. 9. Algorithm 2

Download (267KB)
11. Fig. 10. Algorithm 3

Download (219KB)
12. Fig. 11. Algorithm 4

Download (368KB)

Copyright (c) 2024 Russian Academy of Sciences

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies