14,063 research outputs found
Predictability of catastrophic events: material rupture, earthquakes, turbulence, financial crashes and human birth
We propose that catastrophic events are "outliers" with statistically
different properties than the rest of the population and result from mechanisms
involving amplifying critical cascades. Applications and the potential for
prediction are discussed in relation to the rupture of composite materials,
great earthquakes, turbulence and abrupt changes of weather regimes, financial
crashes and human parturition (birth).Comment: Latex document of 22 pages including 6 ps figures, in press in PNA
Critical Market Crashes
This review is a partial synthesis of the book ``Why stock market crash''
(Princeton University Press, January 2003), which presents a general theory of
financial crashes and of stock market instabilities that his co-workers and the
author have developed over the past seven years. The study of the frequency
distribution of drawdowns, or runs of successive losses shows that large
financial crashes are ``outliers'': they form a class of their own as can be
seen from their statistical signatures. If large financial crashes are
``outliers'', they are special and thus require a special explanation, a
specific model, a theory of their own. In addition, their special properties
may perhaps be used for their prediction. The main mechanisms leading to
positive feedbacks, i.e., self-reinforcement, such as imitative behavior and
herding between investors are reviewed with many references provided to the
relevant literature outside the confine of Physics. Positive feedbacks provide
the fuel for the development of speculative bubbles, preparing the instability
for a major crash. We demonstrate several detailed mathematical models of
speculative bubbles and crashes. The most important message is the discovery of
robust and universal signatures of the approach to crashes. These precursory
patterns have been documented for essentially all crashes on developed as well
as emergent stock markets, on currency markets, on company stocks, and so on.
The concept of an ``anti-bubble'' is also summarized, with two forward
predictions on the Japanese stock market starting in 1999 and on the USA stock
market still running. We conclude by presenting our view of the organization of
financial markets.Comment: Latex 89 pages and 38 figures, in press in Physics Report
Coupled ocean-atmosphere dynamics of the 2017 extreme coastal El Niño.
In March 2017, sea surface temperatures off Peru rose above 28 °C, causing torrential rains that affected the lives of millions of people. This coastal warming is highly unusual in that it took place with a weak La Niña state. Observations and ocean model experiments show that the downwelling Kelvin waves caused by strong westerly wind events over the equatorial Pacific, together with anomalous northerly coastal winds, are important. Atmospheric model experiments further show the anomalous coastal winds are forced by the coastal warming. Taken together, these results indicate a positive feedback off Peru between the coastal warming, atmospheric deep convection, and the coastal winds. These coupled processes provide predictability. Indeed, initialized on as early as 1 February 2017, seasonal prediction models captured the extreme rainfall event. Climate model projections indicate that the frequency of extreme coastal El Niño will increase under global warming
Predictability of Critical Transitions
Critical transitions in multistable systems have been discussed as models for
a variety of phenomena ranging from the extinctions of species to
socio-economic changes and climate transitions between ice-ages and warm-ages.
From bifurcation theory we can expect certain critical transitions to be
preceded by a decreased recovery from external perturbations. The consequences
of this critical slowing down have been observed as an increase in variance and
autocorrelation prior to the transition. However especially in the presence of
noise it is not clear, whether these changes in observation variables are
statistically relevant such that they could be used as indicators for critical
transitions. In this contribution we investigate the predictability of critical
transitions in conceptual models. We study the quadratic integrate-and-fire
model and the van der Pol model, under the influence of external noise. We
focus especially on the statistical analysis of the success of predictions and
the overall predictability of the system. The performance of different
indicator variables turns out to be dependent on the specific model under study
and the conditions of accessing it. Furthermore, we study the influence of the
magnitude of transitions on the predictive performance
A Reconfigurable Vector Instruction Processor for Accelerating a Convection Parametrization Model on FPGAs
High Performance Computing (HPC) platforms allow scientists to model
computationally intensive algorithms. HPC clusters increasingly use
General-Purpose Graphics Processing Units (GPGPUs) as accelerators; FPGAs
provide an attractive alternative to GPGPUs for use as co-processors, but they
are still far from being mainstream due to a number of challenges faced when
using FPGA-based platforms. Our research aims to make FPGA-based high
performance computing more accessible to the scientific community. In this work
we present the results of investigating the acceleration of a particular
atmospheric model, Flexpart, on FPGAs. We focus on accelerating the most
computationally intensive kernel from this model. The key contribution of our
work is the architectural exploration we undertook to arrive at a solution that
best exploits the parallelism available in the legacy code, and is also
convenient to program, so that eventually the compilation of high-level legacy
code to our architecture can be fully automated. We present the three different
types of architecture, comparing their resource utilization and performance,
and propose that an architecture where there are a number of computational
cores, each built along the lines of a vector instruction processor, works best
in this particular scenario, and is a promising candidate for a generic
FPGA-based platform for scientific computation. We also present the results of
experiments done with various configuration parameters of the proposed
architecture, to show its utility in adapting to a range of scientific
applications.Comment: This is an extended pre-print version of work that was presented at
the international symposium on Highly Efficient Accelerators and
Reconfigurable Technologies (HEART2014), Sendai, Japan, June 911, 201
An Earth-system prediction initiative for the twenty-first century
International audienceSome scientists have proposed the Earth-System Prediction Initiative (EPI) at the 2007 GEO Summit in Cape Town, South Africa. EPI will draw upon coordination between international programs for Earth system observations, prediction, and warning, such as the WCRP, WWRP, GCOS, and hence contribute to GEO and the GEOSS. It will link with international organizations, such as the International Council for Science (ICSU), Intergovernmental Oceanographic Commission (IOC), UNEP, WMO, and World Health Organization (WHO). The proposed initiative will provide high-resolution climate models that capture the properties of regional high-impact weather events, such as tropical cyclones, heat wave, and sand and dust storms associated within multi-decadal climate projections of climate variability and change. Unprecedented international collaboration and goodwill are necessary for the success of EPI
Dragon-kings: mechanisms, statistical methods and empirical evidence
This introductory article presents the special Discussion and Debate volume
"From black swans to dragon-kings, is there life beyond power laws?" published
in Eur. Phys. J. Special Topics in May 2012. We summarize and put in
perspective the contributions into three main themes: (i) mechanisms for
dragon-kings, (ii) detection of dragon-kings and statistical tests and (iii)
empirical evidence in a large variety of natural and social systems. Overall,
we are pleased to witness significant advances both in the introduction and
clarification of underlying mechanisms and in the development of novel
efficient tests that demonstrate clear evidence for the presence of
dragon-kings in many systems. However, this positive view should be balanced by
the fact that this remains a very delicate and difficult field, if only due to
the scarcity of data as well as the extraordinary important implications with
respect to hazard assessment, risk control and predictability.Comment: 20 page
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