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Balls-in-Bins Processes with Feedback and Brownian Motion

Published online by Cambridge University Press:  01 January 2008

ROBERTO OLIVEIRA*
Affiliation:
IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA (e-mail: riolivei@us.ibm.com, rob.oliv@gmail.com)

Abstract

In a balls-in-bins process with feedback, balls are sequentially thrown into bins so that the probability that a bin with n balls obtains the next ball is proportional to f(n) for some function f. A commonly studied case where there are two bins and f(n) = np for p > 0, and our goal is to study the fine behaviour of this process with two bins and a large initial number t of balls. Perhaps surprisingly, Brownian Motions are an essential part of both our proofs.

For p > 1/2, it was known that with probability 1 one of the bins will lead the process at all large enough times. We show that if the first bin starts with balls (for constant λ∈ℝ), the probability that it always or eventually leads has a non-trivial limit depending on λ.

For p ≤ 1/2, it was known that with probability 1 the bins will alternate in leadership. We show, however, that if the initial fraction of balls in one of the bins is > 1/2, the time until it is overtaken by the remaining bin scales like Θ(t1+1/(1-2p)) for p < 1/2 and exp(Θ(t)) for p = 1/2. In fact, the overtaking time has a non-trivial distribution around the scaling factor, which we determine explicitly.

Our proofs use a continuous-time embedding of the balls-in-bins process (due to Rubin) and a non-standard approximation of the process by Brownian Motion. The techniques presented also extend to more general functions f.

Type
Paper
Copyright
Copyright © Cambridge University Press 2007

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References

[1]Albert, R. and Barabási, A.-L. (2002) Statistical mechanics of complex networks. Reviews of Modern Physics 74 4797. Available at arXiv: cond-mat/0106096.CrossRefGoogle Scholar
[2]Alon, N. and Spencer, J. (2000) The Probabilistic Method, 2nd edn, Wiley-Interscience Series in Discrete Mathematics, Wiley, New York.CrossRefGoogle Scholar
[3]Billingsley, P. (1999) Convergence of Probability Measures, 2nd edn, Wiley Series in Probability and Statistics, Wiley, New York.CrossRefGoogle Scholar
[4]Davis, B. (1990) Reinforced random walk. Probab. Theory Rel. Fields 84 203229.CrossRefGoogle Scholar
[5]Drinea, E., Enachescu, M., and Mitzenmacher, M. (2001) Variations on random graph models of the web. Harvard Technical Report TR-06-01.Google Scholar
[6]Drinea, E., Frieze, A., and Mitzenmacher, M. (2002) Balls in bins processes with feedback. In Proc. 11th Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, Philadelphia, PA, USA, pp. 308315.Google Scholar
[7]Khanin, K. and Khanin, R. (2001) A probabilistic model for the establishment of neuron polarity. J. Math. Biology 42 2640.CrossRefGoogle ScholarPubMed
[8]Krapivsky, P. L. and Redner, S. L. (2001) Organization of growing random networks. Phys. Rev. E 63 066123. Available at arXiv: cond-mat/0011094.CrossRefGoogle ScholarPubMed
[9]Mitzenmacher, M., Oliveira, R., and Spencer, J. (2004) A scaling result for explosive processes. Electron. J. Combin. 11 R31.CrossRefGoogle Scholar
[10]Oliveira, R. (2004) Preferential attachment. PhD thesis, Department of Mathematics, Courant Institute of Mathematical Sciences, New York University.Google Scholar
[11]Oliveira, R. (2005) The onset of dominance in balls-in-bins processes with feedback. Random Struct. Alg., to appear. Available at arXiv: math.PR/0510415.Google Scholar
[12]Oliveira, R. and Spencer, J. (2005) Avoiding an imminent defeat in a balls-in-bins process with feedback. Manuscript.Google Scholar
[13]Spencer, J. and Wormald, N. Explosive processes. Manuscript.Google Scholar