Entity

Time filter

Source Type

Palma, Spain

Arbona A.,IAC3 UIB | Bona C.,IAC3 UIB | Masso J.,IAC3 UIB | Minano B.,IAC3 UIB | Plastino A.,National University of La Plata
Physica A: Statistical Mechanics and its Applications | Year: 2016

We define a benchmark for definitions of complexity in systems with spatio-temporal dynamics and employ it in the study of Collective Motion. We show that LMC's complexity displays interesting properties in such systems, while a statistical complexity model (SCM) based on autocorrelation reasonably meets our perception of complexity. However this SCM is not as general as desirable, as it does not merely depend on the system's Probability Distribution Function. Inspired by the notion of Fisher information, we develop a SCM candidate, which we call the Fisher-gradient complexity, which exhibits nice properties from the viewpoint of our benchmark. © 2015 Elsevier B.V. All rights reserved. Source


Arbona A.,IAC3 UIB | Bona C.,IAC3 UIB | Minano B.,IAC3 UIB | Plastino A.,National University of La Plata
Physica A: Statistical Mechanics and its Applications | Year: 2014

The definition of complexity through Statistical Complexity Measures (SCM) has recently seen major improvements. Mostly, the effort is concentrated in measures on time series. We propose a SCM definition for spatial dynamical systems. Our definition is in line with the trend to combine entropy with measures of structure (such as disequilibrium). We study the behaviour of our definition against the vectorial noise model of Collective Motion. From a global perspective, we show how our SCM is minimal at both the microscale and macroscale, while it reaches a maximum at the ranges that define the mesoscale in this model. From a local perspective, the SCM is minimum both in highly ordered and disordered areas, while it reaches a maximum at the edges between such areas. These characteristics suggest this is a good candidate for detecting the mesoscale of arbitrary dynamical systems as well as regions where the complexity is maximal in such systems. © 2014 Elsevier B.V. All rights reserved. Source


Arbona A.,IAC3 UIB | Artigues A.,IAC3 UIB | Bona-Casas C.,IAC3 UIB | Bona-Casas C.,University of Amsterdam | And 5 more authors.
Computer Physics Communications | Year: 2013

Simflowny is a software platform which aims to formalize the main elements of a simulation flow. It allows users to manage (i) formal representations of physical models based on Initial Value Problems (hyperbolic, parabolic and mixed-type partial differential equations), (ii) simulation problems based on such models, and (iii) discretization schemes to translate the problem to a finite mesh. Additionally, Simflowny generates automatically code for general-purpose simulation frameworks. This paper first presents an introductory example of such problems. Then, formal representations are explained. Afterwards, it summarizes the platform's architecture. Finally, validation results are provided. © 2013 Elsevier B.V. All rights reserved. Source

Discover hidden collaborations