Classification of Random Walks and Green’s Theorem on Infinite Homogeneous Trees

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P. Swarnambigai, N. Nathiya, K. Kalaivani, Kamaleldin Abodayeh

Abstract

In the context of random walks whose states are the vertices of an infinite tree, a classification of random walks is given as transient or recurrent. On the infinite homogeneous trees with the assumption that the transition probability between any two neighboring states are the same, a form of the classical Green’s formula is derived. As a consequence, two versions of the mean-value property for median functions are obtained.

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References

  1. V. Anandam, Harmonic Functions and Potentials on Finite or Infinite Networks, Springer, Berlin, Heidelberg, 2011. https://doi.org/10.1007/978-3-642-21399-1.
  2. V. Anandam, Some Potential-Theoretic Techniques in Non-Reversible Markov Chains, Rend. Circ. Mat. Palermo 62 (2013), 273–284. https://doi.org/10.1007/s12215-013-0124-8.
  3. S. Axler, P. Bourdon, W. Ramey, Harmonic Function Theory, Springer, New York, 2001. https://doi.org/10.1007/978-1-4757-8137-3.
  4. P. Barthelemy, J. Bertolotti, D.S. Wiersma, A Lévy Flight for Light, Nature 453 (2008), 495–498. https://doi.org/10.1038/nature06948.
  5. E. Bendito, A. Carmona, A.M. Encinas, Solving Boundary Value Problems on Networks Using Equilibrium Measures, J. Funct. Anal. 171 (2000), 155–176. https://doi.org/10.1006/jfan.1999.3528.
  6. M. Brelot, Éleménts de la Théorie Classique du Potentiel, 3rd Edition, Centre de Documentation Universitaire, Paris, 1965.
  7. R.J. Duffin, Discrete Potential Theory, Duke Math. J. 20 (1953), 233–251. https://doi.org/10.1215/s0012-7094-53-02023-7.
  8. E. Eisenriegler, Random Walks in Polymer Physics, in: H. Meyer-Ortmanns, A. Klümper (Eds.), Field Theoretical Tools for Polymer and Particle Physics, Springer Berlin Heidelberg, 1998: pp. 1–24. https://doi.org/10.1007/BFb0106874.
  9. Y.J. Gao, F.M. Zhang, Q. Guo, C. Li, Research on the Searching Performance of Flower Pollination Algorithm With Three Random Walks, J. Intell. Fuzzy Syst. 35 (2018), 333–341. https://doi.org/10.3233/jifs-169592.
  10. G.F. Lawler, Introduction to Stochastic Processes, Chapman & Hall, 1995. https://doi.org/10.1201/9781315273600.
  11. N.C. Le, M.T. Dao, H.L. Nguyen, T.N. Nguyen, H. Vu, An Application of Random Walk on Fake Account Detection Problem: A Hybrid Approach, in: 2020 RIVF International Conference on Computing and Communication Technologies (RIVF), IEEE, Ho Chi Minh, Vietnam, 2020: pp. 1–6. https://doi.org/10.1109/RIVF48685.2020.9140749.
  12. L. Li, G. Xu, Y. Zhang, M. Kitsuregawa, Random Walk Based Rank Aggregation to Improving Web Search, Knowl.- Based Syst. 24 (2011), 943–951. https://doi.org/10.1016/j.knosys.2011.04.001.
  13. T. Lyons, A Simple Criterion for Transience of a Reversible Markov Chain, Ann. Probab. 11 (1983), 393–402. https://doi.org/10.1214/aop/1176993604.
  14. S. McGuinness, Recurrent Networks and a Theorem of Nash-Williams, J. Theor. Probab. 4 (1991),. 87–100. https://doi.org/10.1007/bf01046995.
  15. C.S.J.A. Nash-Williams, Random Walk and Electric Currents in Networks, Math. Proc. Camb. Phil. Soc. 55 (1959), 181–194. https://doi.org/10.1017/s0305004100033879.
  16. T. Kayano, M. Yamasaki, Discrete Dirichlet Integral Formula, Discr. Appl. Math. 22 (1988), 53–68. https://doi.org/10.1016/0166-218x(88)90122-9.
  17. D. Reible, S. Mohanty, A Levy Flight–Random Walk Model for Bioturbation, Environ. Toxicol. Chem. 21 (2002), 875–881. https://doi.org/10.1002/etc.5620210426.
  18. N. Shatnawi, S. Sahran, M.F. Nasrudin, Memory-Based Bees Algorithm with Lévy Flights for Multilevel Image Thresholding, in: D.T. Pham, N. Hartono (Eds.), Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach, Springer International Publishing, Cham, 2023: pp. 175–191. https://doi.org/10.1007/978-3-031-14537-7_11.
  19. P.M. Soardi, Potential Theory on Infinite Networks, Springer, Berlin, Heidelberg, 1994. https://doi.org/10.1007/BFb0073995.
  20. J. Zhang, Application of Random Walk for Disease Prediction, Highlights Sci. Eng. Technol. 16 (2022), 78–85. https://doi.org/10.54097/hset.v16i.2412.