arXiv Analytics

Sign in

arXiv:1312.3357 [math.PR]AbstractReferencesReviewsResources

Polynomial chaos and scaling limits of disordered systems

Francesco Caravenna, Rongfeng Sun, Nikos Zygouras

Published 2013-12-11, updated 2016-10-24Version 3

Inspired by recent work of Alberts, Khanin and Quastel, we formulate general conditions ensuring that a sequence of multi-linear polynomials of independent random variables (called polynomial chaos expansions) converges to a limiting random variable, given by a Wiener chaos expansion over the d-dimensional white noise. A key ingredient in our approach is a Lindeberg principle for polynomial chaos expansions, which extends earlier work of Mossel, O'Donnell and Oleszkiewicz. These results provide a unified framework to study the continuum and weak disorder scaling limits of statistical mechanics systems that are disorder relevant, including the disordered pinning model, the (long-range) directed polymer model in dimension 1+1, and the two-dimensional random field Ising model. This gives a new perspective in the study of disorder relevance, and leads to interesting new continuum models that warrant further studies.

Comments: 55 pages. Final version. To appear in JEMS
Categories: math.PR
Subjects: 82B44, 82D60, 60K35
Related articles: Most relevant | Search more
arXiv:math/0702513 [math.PR] (Published 2007-02-17)
Scaling limits for gradient systems in random environment
arXiv:1507.00397 [math.PR] (Published 2015-07-02)
Scaling limits of a model for selection at two scales
arXiv:1408.4157 [math.PR] (Published 2014-08-18, updated 2014-08-22)
Compressive Sampling of Polynomial Chaos Expansions: Convergence Analysis and Sampling Strategies