10,336 research outputs found
Effective Theories for Circuits and Automata
Abstracting an effective theory from a complicated process is central to the
study of complexity. Even when the underlying mechanisms are understood, or at
least measurable, the presence of dissipation and irreversibility in
biological, computational and social systems makes the problem harder. Here we
demonstrate the construction of effective theories in the presence of both
irreversibility and noise, in a dynamical model with underlying feedback. We
use the Krohn-Rhodes theorem to show how the composition of underlying
mechanisms can lead to innovations in the emergent effective theory. We show
how dissipation and irreversibility fundamentally limit the lifetimes of these
emergent structures, even though, on short timescales, the group properties may
be enriched compared to their noiseless counterparts.Comment: 11 pages, 9 figure
Accelerating Scientific Discovery by Formulating Grand Scientific Challenges
One important question for science and society is how to best promote
scientific progress. Inspired by the great success of Hilbert's famous set of
problems, the FuturICT project tries to stimulate and focus the efforts of many
scientists by formulating Grand Challenges, i.e. a set of fundamental, relevant
and hardly solvable scientific questions.Comment: To appear in EPJ Special Topics. For related work see
http://www.futurict.eu and http://www.soms.ethz.c
Complex network analysis and nonlinear dynamics
This chapter aims at reviewing complex network and nonlinear dynamical
models and methods that were either developed for or applied to socioeconomic
issues, and pertinent to the theme of New Economic Geography. After an introduction
to the foundations of the field of complex networks, the present summary
introduces some applications of complex networks to economics, finance, epidemic
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issue
Efficiency of Human Activity on Information Spreading on Twitter
Understanding the collective reaction to individual actions is key to
effectively spread information in social media. In this work we define
efficiency on Twitter, as the ratio between the emergent spreading process and
the activity employed by the user. We characterize this property by means of a
quantitative analysis of the structural and dynamical patterns emergent from
human interactions, and show it to be universal across several Twitter
conversations. We found that some influential users efficiently cause
remarkable collective reactions by each message sent, while the majority of
users must employ extremely larger efforts to reach similar effects. Next we
propose a model that reproduces the retweet cascades occurring on Twitter to
explain the emergent distribution of the user efficiency. The model shows that
the dynamical patterns of the conversations are strongly conditioned by the
topology of the underlying network. We conclude that the appearance of a small
fraction of extremely efficient users results from the heterogeneity of the
followers network and independently of the individual user behavior.Comment: 29 pages, 10 figure
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