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Tree Polymers in the Infinite Volume Limit at Critical Strong Disorder

Published online by Cambridge University Press:  14 July 2016

Torrey Johnson*
Affiliation:
Oregon State University
Edward C. Waymire*
Affiliation:
Oregon State University
*
Postal address: Department of Mathematics, Oregon State University, Corvallis, Oregon 97331, USA.
Postal address: Department of Mathematics, Oregon State University, Corvallis, Oregon 97331, USA.
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Abstract

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The almost-sure existence of a polymer probability in the infinite volume limit is readily obtained under general conditions of weak disorder from standard theory on multiplicative cascades or branching random walks. However, speculations in the case of strong disorder have been mixed. In this note existence of an infinite volume probability is established at critical strong disorder for which one has convergence in probability. Some calculations in support of a specific formula for the almost-sure asymptotic variance of the polymer path under strong disorder are also provided.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 2011 

References

Aidékon, E. (2011). Convergence in law of the minimum of a branching random walk. Preprint. Available at http://arxiv.org/abs/1101.1810v1.Google Scholar
Aidékon, E. and Shi, Z. (2011). Martingale ratio convergence in the branching random walk. Preprint. Available at http://arxiv.org/abs/1102.0217v1.Google Scholar
Bezerra, S., Tindel, S. and Viens, F. (2008). Superdiffusivity for a Brownian polymer in a continuous Gaussian environment. Ann. Prob. 36, 16421675.Google Scholar
Biggins, J. D. (1976). The first- and last-birth problem for a multitype age-dependent branching process. Adv. Appl. Prob. 8, 446459.Google Scholar
Biggins, J. D. and Kyprianou, A. E. (2004). Measure change in multitype branching. Ann. Prob. 36, 544581.Google Scholar
Bolthausen, E. (1989). A note on the diffusion of directed polymers in a random environment. Commun. Math. Phys. 123, 529534.Google Scholar
Bolthausen, E. (1991). On directed polymers in a random environment. In Selected Proceedings of the Sheffield Symposium on Applied Probability (Sheffield, 1989; IMS Lecture Notes Monogr. Ser. 18), eds Basawa, I. V. and Taylor, R. I., Institute of Mathematical Statistics, Hayward, CA, pp. 4147.Google Scholar
Kahane, J-P. (1989). Random multiplications, random coverings, multiplicative chaos. In Analysis at Urbana (Urbana, IL, 19861986; London Math. Soc. Lecture Note Ser. 137), Vol. I, Cambridge University Press, pp. 196-255.Google Scholar
Kahane, J-P. and Peyrière, J. (1976). Sur certaines martingales de Benoit Mandelbrot. Adv. Math. 22, 131145.Google Scholar
Waymire, E. C. and Williams, S. C. (1996). A cascade decomposition theory with applications to Markov and exchangeable cascades. Trans. Amer. Math. Soc. 348, 585632.Google Scholar
Waymire, E. C. and Williams, S. C. (2010). T-martingales, size biasing, and tree polymer cascades. In Recent Developments in Fractals and Related Fields, Birkhäuser, Boston, MA, pp. 353380.Google Scholar