17,291 research outputs found
Investigation of the Galactic Magnetic Field with Ultra-High Energy Cosmic Rays
We present a method to correct for deflections of ultra-high energy cosmic
rays in the galactic magnetic field. We perform these corrections by simulating
the expected arrival directions of protons using a parameterization of the
field derived from Faraday rotation and synchrotron emission measurements. To
evaluate the method we introduce a simulated astrophysical scenario and two
observables designed for testing cosmic ray deflections. We show that protons
can be identified by taking advantage of the galactic magnetic field pattern.
Consequently, cosmic ray deflection in the galactic field can be verified
experimentally. The method also enables searches for directional correlations
of cosmic rays with source candidates.Comment: 12 pages, 3 figures, presented at the Eur. Phys. Soc. Conf. on High
Energy Physics, Jul. 2015, Vienna, Austria, and the 34th Intern. Cosmic Ray
Conf., Jul. 2015, The Hague, The Netherland
Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing
In the past decade, tracking health trends using social media data has shown
great promise, due to a powerful combination of massive adoption of social
media around the world, and increasingly potent hardware and software that
enables us to work with these new big data streams. At the same time, many
challenging problems have been identified. First, there is often a mismatch
between how rapidly online data can change, and how rapidly algorithms are
updated, which means that there is limited reusability for algorithms trained
on past data as their performance decreases over time. Second, much of the work
is focusing on specific issues during a specific past period in time, even
though public health institutions would need flexible tools to assess multiple
evolving situations in real time. Third, most tools providing such capabilities
are proprietary systems with little algorithmic or data transparency, and thus
little buy-in from the global public health and research community. Here, we
introduce Crowdbreaks, an open platform which allows tracking of health trends
by making use of continuous crowdsourced labelling of public social media
content. The system is built in a way which automatizes the typical workflow
from data collection, filtering, labelling and training of machine learning
classifiers and therefore can greatly accelerate the research process in the
public health domain. This work introduces the technical aspects of the
platform and explores its future use cases
Production of Jet Pairs at Large Relative Rapidity in Hadron-Hadron Collisions as a Probe of the Perturbative Pomeron
The production of jet pairs with small transverse momentum and large relative
rapidity in high energy hadron-hadron collisions is studied. The rise of the
parton-level cross section with increasing rapidity gap is a fundamental
prediction of the BFKL `perturbative pomeron' equation of Quantum
Chromodynamics. However, at fixed collider energy it is difficult to
disentangle this effect from variations in the cross section due to the parton
distributions. It is proposed to study instead the distribution in the
azimuthal angle difference of the jets as a function of the rapidity gap. The
flattening of this distribution with increasing dijet rapidity gap is shown to
be a characteristic feature of the BFKL behaviour. Predictions for the Fermilab
proton-antiproton collider are presented.Comment: 17 pages, 11 figures, preprint DTP/94/0
Learning to Understand by Evolving Theories
In this paper, we describe an approach that enables an autonomous system to
infer the semantics of a command (i.e. a symbol sequence representing an
action) in terms of the relations between changes in the observations and the
action instances. We present a method of how to induce a theory (i.e. a
semantic description) of the meaning of a command in terms of a minimal set of
background knowledge. The only thing we have is a sequence of observations from
which we extract what kinds of effects were caused by performing the command.
This way, we yield a description of the semantics of the action and, hence, a
definition.Comment: KRR Workshop at ICLP 201
Forward-Invariance and Wong-Zakai Approximation for Stochastic Moving Boundary Problems
We discuss a class of stochastic second-order PDEs in one space-dimension
with an inner boundary moving according to a possibly non-linear, Stefan-type
condition. We show that proper separation of phases is attained, i.e., the
solution remains negative on one side and positive on the other side of the
moving interface, when started with the appropriate initial conditions. To
extend results from deterministic settings to the stochastic case, we establish
a Wong-Zakai type approximation. After a coordinate transformation the problems
are reformulated and analysed in terms of stochastic evolution equations on
domains of fractional powers of linear operators.Comment: 46 page
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