arXiv Analytics

Sign in

arXiv:1602.00432 [cond-mat.stat-mech]AbstractReferencesReviewsResources

Scaling in erosion of landscapes: Renormalization group analysis of a model with infinitely many couplings

N. V. Antonov, P. I. Kakin

Published 2016-02-01Version 1

Standard field theoretic renormalization group is applied to the model of landscape erosion introduced by R. Pastor-Satorras and D. H. Rothman [Phys. Rev. Lett. 80: 4349 (1998); J. Stat. Phys. 93: 477 (1998)] yielding unexpected results: the model is multiplicatively renormalizable only if it involves infinitely many coupling constants ( i.e., the corresponding renormalization group equations involve infinitely many beta-functions). Despite this fact, the one-loop counterterm can be derived albeit in a closed form in terms of the certain function $V(h)$, entering the original stochastic equation, and its derivatives with respect to the height field $h$. Its Taylor expansion gives rise to the full infinite set of the one-loop renormalization constants, beta-functions and anomalous dimensions. Instead of a set of fixed points, there is a two-dimensional surface of fixed points that is likely to contain infrared attractive region(s). If that is the case, the model exhibits scaling behaviour in the infrared range. The corresponding critical exponents are nonuniversal through the dependence on the coordinates of the fixed point on the surface, but satisfy certain universal exact relations.

Comments: The authors thank the Organizers of the International Conference "Models in Quantum Field Theory V" for the opportunity to present the results of the research summarised in the paper
Categories: cond-mat.stat-mech
Related articles: Most relevant | Search more
Renormalization group analysis of a turbulent compressible fluid near $d = 4$ : Crossover between local and non-local scaling regimes
Effects of random environment on a self-organized critical system: Renormalization group analysis of a continuous model
Static approach to renormalization group analysis of stochastic models with spatially quenched disorder