14,556 research outputs found
A Mathematical Model for the Dynamics and Synchronization of Cows
We formulate a mathematical model for daily activities of a cow (eating,
lying down, and standing) in terms of a piecewise affine dynamical system. We
analyze the properties of this bovine dynamical system representing the single
animal and develop an exact integrative form as a discrete-time mapping. We
then couple multiple cow "oscillators" together to study synchrony and
cooperation in cattle herds. We comment on the relevant biology and discuss
extensions of our model. With this abstract approach, we not only investigate
equations with interesting dynamics but also develop interesting biological
predictions. In particular, our model illustrates that it is possible for cows
to synchronize \emph{less} when the coupling is increased.Comment: to appear in Physica
Global Patterns of Synchronization in Human Communications
Social media are transforming global communication and coordination. The data
derived from social media can reveal patterns of human behavior at all levels
and scales of society. Using geolocated Twitter data, we have quantified
collective behaviors across multiple scales, ranging from the commutes of
individuals, to the daily pulse of 50 major urban areas and global patterns of
human coordination. Human activity and mobility patterns manifest the synchrony
required for contingency of actions between individuals. Urban areas show
regular cycles of contraction and expansion that resembles heartbeats linked
primarily to social rather than natural cycles. Business hours and circadian
rhythms influence daily cycles of work, recreation, and sleep. Different urban
areas have characteristic signatures of daily collective activities. The
differences are consistent with a new emergent global synchrony that couples
behavior in distant regions across the world. A globally synchronized peak that
includes exchange of ideas and information across Europe, Africa, Asia and
Australasia. We propose a dynamical model to explain the emergence of global
synchrony in the context of increasing global communication and reproduce the
observed behavior. The collective patterns we observe show how social
interactions lead to interdependence of behavior manifest in the
synchronization of communication. The creation and maintenance of temporally
sensitive social relationships results in the emergence of complexity of the
larger scale behavior of the social system.Comment: 20 pages, 12 figures. arXiv admin note: substantial text overlap with
arXiv:1602.0621
Middlewareâs message : the financial technics of codata
In this paper, I will argue for the relevance of certain distinctive features of messaging systems, namely those in which data (a) can be sent and received asynchronously, (b) can be sent to multiple simultaneous recipients and (c) is received as a âpotentially infiniteâ flow of unpredictable events. I will describe the social technology of the stock ticker, a telegraphic device introduced at the New York Stock Exchange in the 1860s, with reference to early twentieth century philosophers of synchronous experience (Bergson), simultaneous sign interpretations (Mead and Peirce), and flows of discrete events (Bachelard). Then, I will show how the tickerâs data flows developed into the 1990s-era technologies of message queues and message brokers, which distinguished themselves through their asynchronous implementation of ticker-like message feeds sent between otherwise incompatible computers and terminals. These latter systemsâ characteristic âpublish/subscribeâ communication pattern was one in which conceptually centralized (if logically distributed) flows of messages would be âpublished,â and for which âsubscribersâ would be spontaneously notified when events of interest occurred. This paradigmâcommon to the so-called âmessage-oriented middlewareâ systems of the late 1990sâwould re-emerge in different asynchronous distributed system contexts over the following decades, from âpush mediaâ to Twitter to the Internet of Things
Synchronization in complex networks
Synchronization processes in populations of locally interacting elements are
in the focus of intense research in physical, biological, chemical,
technological and social systems. The many efforts devoted to understand
synchronization phenomena in natural systems take now advantage of the recent
theory of complex networks. In this review, we report the advances in the
comprehension of synchronization phenomena when oscillating elements are
constrained to interact in a complex network topology. We also overview the new
emergent features coming out from the interplay between the structure and the
function of the underlying pattern of connections. Extensive numerical work as
well as analytical approaches to the problem are presented. Finally, we review
several applications of synchronization in complex networks to different
disciplines: biological systems and neuroscience, engineering and computer
science, and economy and social sciences.Comment: Final version published in Physics Reports. More information
available at http://synchronets.googlepages.com
Low-dimensional behavior of Kuramoto model with inertia in complex networks
Low-dimensional behavior of large systems of globally coupled oscillators has
been intensively investigated since the introduction of the Ott-Antonsen
ansatz. In this report, we generalize the Ott-Antonsen ansatz to second-order
Kuramoto models in complex networks. With an additional inertia term, we find a
low-dimensional behavior similar to the first-order Kuramoto model, derive a
self-consistent equation and seek the time-dependent derivation of the order
parameter. Numerical simulations are also conducted to verify our analytical
results.Comment: 6 figure
Robustness of Synchrony in Complex Networks and Generalized Kirchhoff Indices
In network theory, a question of prime importance is how to assess network
vulnerability in a fast and reliable manner. With this issue in mind, we
investigate the response to parameter changes of coupled dynamical systems on
complex networks. We find that for specific, non-averaged perturbations, the
response of synchronous states critically depends on the overlap between the
perturbation vector and the eigenmodes of the stability matrix of the
unperturbed dynamics. Once averaged over properly defined ensembles of such
perturbations, the response is given by new graph topological indices, which we
introduce as generalized Kirchhoff indices. These findings allow for a fast and
reliable method for assessing the specific or average vulnerability of a
network against changing operational conditions, faults or external attacks.Comment: 5 pages + supplemental material Fina
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