The network of interactions among fluid elements and coherent structures gives rise to the
incredibly rich dynamics of vortical flows. These interactions can be described with the use …

Investigating spatiotemporal pattern and propagation mechanism of meteorological drought
is of great significance to develop early warning system for drought-affected regions and …

A bstract We present a novel technique for the analysis of proton-proton collision events
from the ATLAS and CMS experiments at the Large Hadron Collider. For a given final state …

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis
toolbox) open source software package for applying and combining modern methods of data …

Recurrence networks are a powerful nonlinear tool for time series analysis of complex
dynamical systems. While there are already many successful applications ranging from …

Agent-based models of opinion dynamics allow one to examine the spread of opinions
between entities and to study phenomena such as consensus, polarization, and …

El Niño exhibits distinct Eastern Pacific (EP) and Central Pacific (CP) types which are
commonly, but not always consistently, distinguished from each other by different signatures …

Complex network theory provides a powerful toolbox for studying the structure of statistical
interrelationships between multiple time series in various scientific disciplines. In this work …

Precipitation is one of the most important meteorological variables for defining the climate
dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The …

In studies of spatially confined networks, network measures can lead to false conclusions
since most measures are boundary-affected. This is especially the case if boundaries are …