Skip to main content
Log in

Anderson Polymer in a Fractional Brownian Environment: Asymptotic Behavior of the Partition Function

  • Published:
Journal of Theoretical Probability Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

We consider the Anderson polymer partition function

$$\begin{aligned} u(t):=\mathbb {E}^X\left[ e^{\int _0^t \mathrm {d}B^{X(s)}_s}\right] \,, \end{aligned}$$

where \(\{B^{x}_t\,;\, t\ge 0\}_{x\in \mathbb {Z}^d}\) is a family of independent fractional Brownian motions all with Hurst parameter \(H\in (0,1)\), and \(\{X(t)\}_{t\in \mathbb {R}^{\ge 0}}\) is a continuous-time simple symmetric random walk on \(\mathbb {Z}^d\) with jump rate \(\kappa \) and started from the origin. \(\mathbb {E}^X\) is the expectation with respect to this random walk. We prove that when \(H\le 1/2\), the function u(t) almost surely grows asymptotically like \(e^{\lambda t}\), where \(\lambda >0\) is a deterministic number. More precisely, we show that as t approaches \(+\infty \), the expression \(\{\frac{1}{t}\log u(t)\}_{t\in \mathbb {R}^{>0}}\) converges both almost surely and in the \(\hbox {L}^1\) sense to some positive deterministic number \(\lambda \). For \(H>1/2\), we first show that \(\lim _{t\rightarrow \infty } \frac{1}{t}\log u(t)\) exists both almost surely and in the \(\hbox {L}^1\) sense and equals a strictly positive deterministic number (possibly \(+\infty \)); hence, almost surely u(t) grows asymptotically at least like \(e^{\alpha t}\) for some deterministic constant \(\alpha >0\). On the other hand, we also show that almost surely and in the \(\hbox {L}^1\) sense, \(\limsup _{t\rightarrow \infty } \frac{1}{t\sqrt{\log t}}\log u(t)\) is a deterministic finite real number (possibly zero), hence proving that almost surely u(t) grows asymptotically at most like \(e^{\beta t\sqrt{\log t}}\) for some deterministic positive constant \(\beta \). Finally, for \(H>1/2\) when \(\mathbb {Z}^d\) is replaced by a circle endowed with a Hölder continuous covariance function, we show that \(\limsup _{t\rightarrow \infty } \frac{1}{t}\log u(t)\) is a deterministic finite positive real number, hence proving that almost surely u(t) grows asymptotically at most like \(e^{c t}\) for some deterministic positive constant c.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Borodin, A., Corwin, I.: Moments and Lyapunov exponents for the parabolic Anderson model. Ann. Appl. Probab. 24(3), 1172–1198 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  2. Carmona, R.A., Molchanov, S.A.: Parabolic Anderson problem and intermittency. Mem. Am. Math. Soc 108(518), viii+125 (1994)

    MathSciNet  MATH  Google Scholar 

  3. Comets, F., Cranston, M.: Overlaps and pathwise localization in the Anderson polymer model. Stoch. Process. Appl. 123(6), 2446–2471 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cranston, M., Mountford, T.S., Shiga, T.: Lyapunov exponents for the parabolic Anderson model. Acta Math. Univ. Comenian. 71(2), 163–188 (2002)

    MathSciNet  MATH  Google Scholar 

  5. Cranstonm, M.: Properties of the parabolic Anderson model and the Anderson polymer model. ISRN Probability and Statistics (2013)

  6. Derriennic, Y., Hachem, B.: Sur la convergence en moyenne des suites presque sous-additives. Math. Z. 198(2), 221–224 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  7. Erhard, D., den Hollander, F., Maillard, G.: The parabolic Anderson model in a dynamic random environment: space-time ergodicity for the quenched Lyapunov exponent. Probab. Theory Related Fields 162(1–2), 1–46 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  8. Gärtner, J., den Hollander, F., Maillard, G.: Quenched Lyapunov exponent for the parabolic Anderson model in a dynamic random environment. Probability in Complex Physical Systems. Volume 11 of Springer Proceedings of Mathematics, pp. 159–193. Springer, Heidelberg (2012)

  9. Gärtner, J., König, W.: The parabolic Anderson model. In: Interacting Stochastic Systems, pp. 153–179. Springer, Berlin (2005)

  10. Grinstead, C.M., Snell, J.L.: Introduction to Probability. American Mathematical Society, Providence (1997)

    MATH  Google Scholar 

  11. Janson, S.: Gaussian Hilbert Spaces. Cambridge University Press, Cambridge (1997)

    Book  MATH  Google Scholar 

  12. Kalbasi, K., Mountford, T.S.: Feynman-Kac representation for the parabolic Anderson model driven by fractional noise. J. Funct. Anal. 269(5), 1234–1263 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  13. König, W.: The Parabolic Anderson Model: Random Walk in Random Potential. Birkhäuser, Basel (2016)

    Book  MATH  Google Scholar 

  14. Ledoux, M.: The Concentration of Measure Phenomenon, Volume 89 of Mathematical Surveys and Monographs. American Mathematical Society, Providence (2001)

    Google Scholar 

  15. Lifshits, M.: Lectures on Gaussian Processes. Springer, Berlin (2012)

    Book  MATH  Google Scholar 

  16. Mishura, Y.S.: Stochastic Calculus for Fractional Brownian Motion and Related Processes. Springer, Berlin (2008)

    Book  MATH  Google Scholar 

  17. Mitzenmacher, M., Upfal, E.: Probability and Computing. Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, Cambridge (2005)

    Book  MATH  Google Scholar 

  18. Nualart, D.: Stochastic integration with respect to fractional Brownian motion and applications. Stochastic models (Mexico City. 2002), Volume 336 Contemporary Mathematics, pp. 3–39. American Mathematical Society, Providence (2003)

  19. Protter, P.E.: Stochastic integration and differential equations, 2nd edn. Version 2.1. Springer, Berlin (2005)

  20. Qian, H.: Fractional Brownian motion and fractional Gaussian noise. In: Processes with Long-Range Correlations, pp. 22–33. Springer, Berlin (2003)

  21. Robbins, H.: A remark on Stirling’s formula. Am. Math. Monthly 62, 26–29 (1955)

    MathSciNet  MATH  Google Scholar 

  22. Rovira, C., Tindel, S.: On the Brownian-directed polymer in a Gaussian random environment. J. Funct. Anal. 222(1), 178–201 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  23. Üstünel, A.S., Zakai, M.: Transformation of Measure on Wiener Space. Springer Monographs in Mathematics. Springer, Berlin (2000)

    Book  MATH  Google Scholar 

  24. Viens, F.G., Zhang, T.: Almost sure exponential behavior of a directed polymer in a fractional Brownian environment. J. Funct. Anal. 255(10), 2810–2860 (2008)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kamran Kalbasi.

Additional information

Kamran Kalbasi: Supported by Swiss National Science Foundation (SNF).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kalbasi, K., Mountford, T.S. & Viens, F.G. Anderson Polymer in a Fractional Brownian Environment: Asymptotic Behavior of the Partition Function. J Theor Probab 31, 1429–1468 (2018). https://doi.org/10.1007/s10959-017-0756-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10959-017-0756-2

Keywords

Mathematics Subject Classification (2010)

Navigation