303 research outputs found
Bubbling and Large-Scale Structures in Avalanche Dynamics
Using a simple lattice model for granular media, we present a scenario of
self-organization that we term self-organized structuring where the steady
state has several unusual features: (1) large scale space and/or time
inhomogeneities and (2) the occurrence of a non-trivial peaked distribution of
large events which propagate like ``bubbles'' and have a well-defined frequency
of occurrence. We discuss the applicability of such a scenario for other models
introduced in the framework of self-organized criticality.Comment: 5 pages RevTex, 4 eps figure
General scores for accessibility and inequality measures in urban areas
In the last decades, the acceleration of urban growth has led to an
unprecedented level of urban interactions and interdependence. This situation
calls for a significant effort among the scientific community to come up with
engaging and meaningful visualizations and accessible scenario simulation
engines. The present paper gives a contribution in this direction by providing
general methods to evaluate accessibility in cities based on public
transportation data. Through the notion of isochrones, the accessibility
quantities proposed measure the performance of transport systems at connecting
places and people in urban systems. Then we introduce scores rank cities
according to their overall accessibility. We highlight significant inequalities
in the distribution of these measures across the population, which are found to
be strikingly similar across various urban environments. Our results are
released through the interactive platform: www.citychrone.org, aimed at
providing the community at large with a useful tool for awareness and
decision-making
Measuring complexity with zippers
Physics concepts have often been borrowed and independently developed by
other fields of science. In this perspective a significant example is that of
entropy in Information Theory. The aim of this paper is to provide a short and
pedagogical introduction to the use of data compression techniques for the
estimate of entropy and other relevant quantities in Information Theory and
Algorithmic Information Theory. We consider in particular the LZ77 algorithm as
case study and discuss how a zipper can be used for information extraction.Comment: 10 pages, 3 figure
Dynamically Driven Renormalization Group
We present a detailed discussion of a novel dynamical renormalization group
scheme: the Dynamically Driven Renormalization Group (DDRG). This is a general
renormalization method developed for dynamical systems with non-equilibrium
critical steady-state. The method is based on a real space renormalization
scheme driven by a dynamical steady-state condition which acts as a feedback on
the transformation equations. This approach has been applied to open non-linear
systems such as self-organized critical phenomena, and it allows the analytical
evaluation of scaling dimensions and critical exponents. Equilibrium models at
the critical point can also be considered. The explicit application to some
models and the corresponding results are discussed.Comment: Revised version, 50 LaTex pages, 6 postscript figure
Language Trees and Zipping
In this letter we present a very general method to extract information from a
generic string of characters, e.g. a text, a DNA sequence or a time series.
Based on data-compression techniques, its key point is the computation of a
suitable measure of the remoteness of two bodies of knowledge. We present the
implementation of the method to linguistic motivated problems, featuring highly
accurate results for language recognition, authorship attribution and language
classification.Comment: 5 pages, RevTeX4, 1 eps figure. In press in Phys. Rev. Lett. (January
2002
Subjectivity and complexity of facial attractiveness
The origin and meaning of facial beauty represent a longstanding puzzle.
Despite the profuse literature devoted to facial attractiveness, its very
nature, its determinants and the nature of inter-person differences remain
controversial issues. Here we tackle such questions proposing a novel
experimental approach in which human subjects, instead of rating natural faces,
are allowed to efficiently explore the face-space and 'sculpt' their favorite
variation of a reference facial image. The results reveal that different
subjects prefer distinguishable regions of the face-space, highlighting the
essential subjectivity of the phenomenon.The different sculpted facial vectors
exhibit strong correlations among pairs of facial distances, characterising the
underlying universality and complexity of the cognitive processes, and the
relative relevance and robustness of the different facial distances.Comment: 15 pages, 5 figures. Supplementary information: 26 pages, 13 figure
Dynamical correlations in the escape strategy of Influenza A virus
The evolutionary dynamics of human Influenza A virus presents a challenging
theoretical problem. An extremely high mutation rate allows the virus to
escape, at each epidemic season, the host immune protection elicited by
previous infections. At the same time, at each given epidemic season a single
quasi-species, that is a set of closely related strains, is observed. A
non-trivial relation between the genetic (i.e., at the sequence level) and the
antigenic (i.e., related to the host immune response) distances can shed light
into this puzzle. In this paper we introduce a model in which, in accordance
with experimental observations, a simple interaction rule based on spatial
correlations among point mutations dynamically defines an immunity space in the
space of sequences. We investigate the static and dynamic structure of this
space and we discuss how it affects the dynamics of the virus-host interaction.
Interestingly we observe a staggered time structure in the virus evolution as
in the real Influenza evolutionary dynamics.Comment: 14 pages, 5 figures; main paper for the supplementary info in
arXiv:1303.595
Maximum entropy models capture melodic styles
We introduce a Maximum Entropy model able to capture the statistics of
melodies in music. The model can be used to generate new melodies that emulate
the style of the musical corpus which was used to train it. Instead of using
the body interactions of order Markov models, traditionally used in
automatic music generation, we use a nearest neighbour model with pairwise
interactions only. In that way, we keep the number of parameters low and avoid
over-fitting problems typical of Markov models. We show that long-range musical
phrases don't need to be explicitly enforced using high-order Markov
interactions, but can instead emerge from multiple, competing, pairwise
interactions. We validate our Maximum Entropy model by contrasting how much the
generated sequences capture the style of the original corpus without
plagiarizing it. To this end we use a data-compression approach to discriminate
the levels of borrowing and innovation featured by the artificial sequences.
The results show that our modelling scheme outperforms both fixed-order and
variable-order Markov models. This shows that, despite being based only on
pairwise interactions, this Maximum Entropy scheme opens the possibility to
generate musically sensible alterations of the original phrases, providing a
way to generate innovation
Phase ordering and symmetries of the Potts model
We have studied the ordering of the q-colours Potts model in two dimensions
on a square lattice. On the basis of our observations we propose that if q is
large enough the system is not able to break global and local null
magnetisation symmetries at zero temperature: when q<4 the system forms domains
with a size proportional to the system size while for q>4 it relaxes towards a
non-equilibrium phase with energy larger than the ground state energy, in
agreement with the previous findings of De Oliveira et al. (M. J. de Oliveira,
A. Petri, T. Tome, Europhys. Lett., 65, 20 (2004)).Comment: 6 pages, 3 figures; minor text rewordings and changes in figures
styl
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