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Bootstrap Percolation in High Dimensions

Published online by Cambridge University Press:  12 August 2010

JÓZSEF BALOGH
Affiliation:
Department of Mathematics, University of Illinois, 1409 W. Green Street, Urbana, IL 61801 and Department of Mathematics, University of California, San Diego, La Jolla, CA 92093 (e-mail: [email protected])
BÉLA BOLLOBÁS
Affiliation:
Trinity College, Cambridge CB2 1TQ, England and Department of Mathematical Sciences, The University of Memphis, Memphis, TN 38152, USA (e-mail: [email protected])
ROBERT MORRIS
Affiliation:
IMPA, Estrada Dona Castorina 110, Jardim Botânico, Rio de Janeiro, RJ, Brasil (e-mail: [email protected])

Abstract

In r-neighbour bootstrap percolation on a graph G, a set of initially infected vertices AV(G) is chosen independently at random, with density p, and new vertices are subsequently infected if they have at least r infected neighbours. The set A is said to percolate if eventually all vertices are infected. Our aim is to understand this process on the grid, [n]d, for arbitrary functions n = n(t), d = d(t) and r = r(t), as t → ∞. The main question is to determine the critical probability pc([n]d, r) at which percolation becomes likely, and to give bounds on the size of the critical window. In this paper we study this problem when r = 2, for all functions n and d satisfying d ≫ log n.

The bootstrap process has been extensively studied on [n]d when d is a fixed constant and 2 ⩽ rd, and in these cases pc([n]d, r) has recently been determined up to a factor of 1 + o(1) as n → ∞. At the other end of the scale, Balogh and Bollobás determined pc([2]d, 2) up to a constant factor, and Balogh, Bollobás and Morris determined pc([n]d, d) asymptotically if d ≥ (log log n)2+ϵ, and gave much sharper bounds for the hypercube.

Here we prove the following result. Let λ be the smallest positive root of the equation so λ ≈ 1.166. Then if d is sufficiently large, and moreover as d → ∞, for every function n = n(d) with d ≫ log n.

Type
Paper
Copyright
Copyright © Cambridge University Press 2010

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References

[1]Adler, J. and Lev, U. (2003) Bootstrap percolation: Visualizations and applications. Braz. J. Phys. 33 641644.CrossRefGoogle Scholar
[2]Aizenman, M. and Lebowitz, J. L. (1988) Metastability effects in bootstrap percolation. J. Phys. A 21 38013813.CrossRefGoogle Scholar
[3]Ajtai, M., Komlós, J. and Szemerédi, E. (1982) Largest random component of a k-cube. Combinatorica 2 17.CrossRefGoogle Scholar
[4]Balogh, J. and Bollobás, B. (2006) Bootstrap percolation on the hypercube. Probab. Theory Rel. Fields 134 624648.Google Scholar
[5]Balogh, J., Bollobás, B., Duminil-Copin, H. and Morris, R. The sharp threshold for bootstrap percolation in all dimensions. In preparation.Google Scholar
[6]Balogh, J., Bollobás, B. and Morris, R. (2009) Majority bootstrap percolation on the hypercube. Combin. Probab. Comput. 18 1751.Google Scholar
[7]Balogh, J., Bollobás, B. and Morris, R. (2009) Bootstrap percolation in three dimensions. Ann. Probab. 37 13291380.CrossRefGoogle Scholar
[8]Balogh, J., Bollobás, B. and Morris, R. Bootstrap percolation in high dimensions. Manuscript: arXiv:0907.3097.Google Scholar
[9]Balogh, J., Peres, Y. and Pete, G. (2006) Bootstrap percolation on infinite trees and non-amenable groups. Combin. Probab. Comput. 15 715730.CrossRefGoogle Scholar
[10]Balogh, J. and Pittel, B. (2007) Bootstrap percolation on random regular graphs. Random Struct. Alg. 30 257286.CrossRefGoogle Scholar
[11]van den Berg, J. and Kesten, H. (1985) Inequalities with applications to percolation and reliability. J. Appl. Probab. 22 556589.Google Scholar
[12]Bollobás, B. (2001) Random Graphs, 2nd edn, Cambridge University Press.Google Scholar
[13]Bollobás, B., Kohayakawa, Y. and Łuczak, T. (1992) The evolution of random subgraphs of the cube. Random Struct. Alg. 3 5590.Google Scholar
[14]Borgs, C., Chayes, J. T., van der Hofstad, R., Slade, G. and Spencer, J. (2006) Random subgraphs of finite graphs III: The phase transition for the n-cube. Combinatorica 26 395410.Google Scholar
[15]Cerf, R. and Cirillo, E. N. M. (1999) Finite size scaling in three-dimensional bootstrap percolation. Ann. Probab. 27 18371850.CrossRefGoogle Scholar
[16]Cerf, R. and Manzo, F. (2002) The threshold regime of finite volume bootstrap percolation. Stochastic Proc. Appl. 101 6982.Google Scholar
[17]Chalupa, J., Leath, P. L. and Reich, G. R. (1979) Bootstrap percolation on a Bethe lattice. J. Phys. C 12 L31L35.Google Scholar
[18]Duminil-Copin, H. and Holroyd, A. Sharp metastability for threshold growth models. In preparation.Google Scholar
[19]Erdős, P. and Hanani, H. (1963) On a limit theorem in combinatorial analysis. Publ. Math. Debrecen 10 1013.Google Scholar
[20]Erdős, P. and Spencer, J. (1979) Evolution of the n-cube. Comput. Math. Appl. 5 3339.CrossRefGoogle Scholar
[21]Fontes, L. R. and Schonmann, R. H. (2008) Bootstrap percolation on homogeneous trees has 2 phase transitions. J. Statist. Phys. 132 839861.CrossRefGoogle Scholar
[22]Fontes, L. R., Schonmann, R. H. and Sidoravicius, V. (2002) Stretched exponential fixation in stochastic Ising models at zero temperature. Commun. Math. Phys. 228 495518.Google Scholar
[23]Gravner, J., Holroyd, A. and Morris, R. A sharper threshold for bootstrap percolation in two dimensions. Submitted.Google Scholar
[24]van der Hofstad, R. and Slade, G. (2005) Asymptotic expansion in n −1 for percolation critical values on the n-cube and ℤn. Random Struct. Alg. 27 331357.Google Scholar
[25]van der Hofstad, R. and Slade, G. (2006) Expansion in n −1 for percolation critical values on the n-cube and ℤn: the first three terms. Combin. Probab. Comput. 15 695713.Google Scholar
[26]Holroyd, A. (2003) Sharp metastability threshold for two-dimensional bootstrap percolation. Probab. Theory Rel. Fields 125 195224.CrossRefGoogle Scholar
[27]Janson, S. (2009) On percolation in random graphs with given vertex degrees. Electronic J. Probab. 14 Paper 5, 86118.Google Scholar
[28]Morris, R. Zero-temperature Glauber dynamics on ℤd. Probab. Theory Rel. Fields, to appear.Google Scholar
[29]Nanda, S., Newman, C. M. and Stein, D. (2000) Dynamics of Ising spin systems at zero temperature. In On Dobrushin's Way: From Probability Theory to Statistical Mechanics (Minlos, R., Shlosman, S. and Suhov, Y., eds), Vol. 198 of Amer. Math. Soc. Transl. Ser. 2, AMS, pp. 183–194.Google Scholar
[30]Newman, C. M. and Stein, D. (2000) Zero-temperature dynamics of Ising spin systems following a deep quench: Results and open problems. Physica A 279 159168.Google Scholar
[31]Pete, G. (1998) Disease processes and bootstrap percolation. Thesis for Diploma at the Bolyai Institute, József Attila University, Szeged, Hungary.Google Scholar
[32]Rödl, V. (1985) On a packing and covering problem. Europ. J. Combin. 6 6978.Google Scholar
[33]Schonmann, R. H. (1992) On the behaviour of some cellular automata related to bootstrap percolation. Ann. Probab. 20 174193.Google Scholar