IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v354y2005icp641-662.html
   My bibliography  Save this article

Topology regulates pattern formation capacity of binary cellular automata on graphs

Author

Listed:
  • Marr, Carsten
  • Hütt, Marc-Thorsten

Abstract

We study the effect of topology variation on the dynamic behavior of a system with local update rules. We implement one-dimensional binary cellular automata on graphs with various topologies by formulating two sets of degree-dependent rules, each containing a single parameter. We observe that changes in graph topology induce transitions between different dynamic domains (Wolfram classes) without a formal change in the update rule. Along with topological variations, we study the pattern formation capacities of regular, random, small-world and scale-free graphs. Pattern formation capacity is quantified in terms of two entropy measures, which for standard cellular automata allow a qualitative distinction between the four Wolfram classes. A mean-field model explains the dynamic behavior of random graphs. Implications for our understanding of information transport through complex, network-based systems are discussed.

Suggested Citation

  • Marr, Carsten & Hütt, Marc-Thorsten, 2005. "Topology regulates pattern formation capacity of binary cellular automata on graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 641-662.
  • Handle: RePEc:eee:phsmap:v:354:y:2005:i:c:p:641-662
    DOI: 10.1016/j.physa.2005.02.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437105001512
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2005.02.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    2. Andreas Wagner & David Fell, 2000. "The Small World Inside Large Metabolic Networks," Working Papers 00-07-041, Santa Fe Institute.
    3. Farkas, I. & Jeong, H. & Vicsek, T. & Barabási, A.-L. & Oltvai, Z.N., 2003. "The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 601-612.
    4. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    5. A. Barrat & M. Weigt, 2000. "On the properties of small-world network models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 13(3), pages 547-560, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Goodrich, Christopher S. & Matache, Mihaela T., 2007. "The stabilizing effect of noise on the dynamics of a Boolean network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 334-356.
    2. Beck, Gary L. & Matache, Mihaela T., 2008. "Dynamical behavior and influence of stochastic noise on certain generalized Boolean networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(19), pages 4947-4958.
    3. Carvunis, Anne-Ruxandra & Latapy, Matthieu & Lesne, Annick & Magnien, Clémence & Pezard, Laurent, 2006. "Dynamics of three-state excitable units on Poisson vs. power-law random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 595-612.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lawford, Steve & Mehmeti, Yll, 2020. "Cliques and a new measure of clustering: With application to U.S. domestic airlines," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Serra, Roberto & Villani, Marco & Agostini, Luca, 2004. "On the dynamics of random Boolean networks with scale-free outgoing connections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 665-673.
    3. Hütt, M.-Th. & Lüttge, U., 2005. "The interplay of synchronization and fluctuations reveals connectivity levels in networks of nonlinear oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 207-226.
    4. Carvunis, Anne-Ruxandra & Latapy, Matthieu & Lesne, Annick & Magnien, Clémence & Pezard, Laurent, 2006. "Dynamics of three-state excitable units on Poisson vs. power-law random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 595-612.
    5. Gerhardt, Günther J.L. & Lemke, Ney & Corso, Gilberto, 2006. "Network clustering coefficient approach to DNA sequence analysis," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 1037-1045.
    6. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    7. Chen, Qinghua & Shi, Dinghua, 2004. "The modeling of scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 240-248.
    8. Wang, Huan & Xu, Chuan-Yun & Hu, Jing-Bo & Cao, Ke-Fei, 2014. "A complex network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 166-176.
    9. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    10. Robert Boyer & Denis Boyer & Gilles Laferté, 2007. "La connexion des réseaux comme facteur de changement institutionnel : l'exemple des vins de Bourgogne," PSE Working Papers halshs-00587708, HAL.
    11. Salcedo-Sanz, S. & Cuadra, L., 2019. "Quasi scale-free geographically embedded networks over DLA-generated aggregates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1286-1305.
    12. Emerson, I. Arnold & Gothandam, K.M., 2012. "Network analysis of transmembrane protein structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 905-916.
    13. Li, Chunguang, 2009. "Memorizing morph patterns in small-world neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 240-246.
    14. Xue-Yan Zhang & Tian-Yuan He & Chuan-Yun Xu & Ke-Fei Cao & Xu-Sheng Zhang, 2023. "Theoretical investigation of the pathway-based network of type 2 diabetes mellitus-related genes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-13, June.
    15. Dassisti, M. & Carnimeo, L., 2013. "A small-world methodology of analysis of interchange energy-networks: The European behaviour in the economical crisis," Energy Policy, Elsevier, vol. 63(C), pages 887-899.
    16. Wang, Huan & Hu, Jing-Bo & Xu, Chuan-Yun & Zhang, De-Hai & Yan, Qian & Xu, Ming & Cao, Ke-Fei & Zhang, Xu-Sheng, 2016. "A pathway-based network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 928-939.
    17. Andrea De Martino & Daniele De Martino & Roberto Mulet & Andrea Pagnani, 2014. "Identifying All Moiety Conservation Laws in Genome-Scale Metabolic Networks," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-11, July.
    18. Tsuchiya, Masa & Selvarajoo, Kumar & Piras, Vincent & Tomita, Masaru & Giuliani, Alessandro, 2009. "Local and global responses in complex gene regulation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1738-1746.
    19. Tsonis, A.A. & Roebber, P.J., 2004. "The architecture of the climate network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 497-504.
    20. Pagani, Giuliano Andrea & Aiello, Marco, 2013. "The Power Grid as a complex network: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2688-2700.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:354:y:2005:i:c:p:641-662. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.