Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

Visibility to discern local from nonlocal dynamic processes

Loading...
Thumbnail Image

Full text at PDC

Publication date

2017

Advisors (or tutors)

Editors

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier
Citations
Google Scholar

Citation

Bru Espino, A. L., Gómez Castro, D. «Visibility to Discern Local from Nonlocal Dynamic Processes». Physica A: Statistical Mechanics and Its Applications, vol. 471, abril de 2017, pp. 718-23. DOI.org (Crossref), https://doi.org/10.1016/j.physa.2016.12.078.

Abstract

We compare using visibility the usual Kardar–Parisi–Zhang (KPZ) universality class and a fractional Edward–Wilkinson (EWf) equation with correlated noise, which share the same kinetic roughening exponents. The KPZ universality class is described by an equation in terms of the usual derivatives, uncorrelated noise and therefore is intrinsically local. The second model includes fractional powers of the Laplace operator and correlated noise, both of which are nonlocal. From their scaling properties, one could be tempted to conclude that both dynamics belong to the same universality class, specifically, to the KPZ universality class. However, this is a wrong conclusion that calls the attention against the indiscriminate application of this approach in real systems without taking into consideration basic physical assumptions (e.g. locality). These examples reveal the necessity of finding new algorithms for detecting characteristics that remain unnoticed to classical scaling analysis, where only the two first moments of the interface distribution (mean and variance) are used to classify the dynamics. We show that visibility and, in particular, the kinetic roughening exponents of the visibility interface, are able to distinguish between these two dynamics which are confused by standard techniques.

Research Projects

Organizational Units

Journal Issue

Description

Keywords

Collections