5,329 research outputs found
Constraints on the cosmic ray diffusion coefficient in the W28 region from gamma-ray observations
GeV and TeV gamma rays have been detected from the supernova remnant W28 and
its surroundings. Such emission correlates quite well with the position of
dense and massive molecular clouds and thus it is often interpreted as the
result of hadronic cosmic ray interactions in the dense gas. Constraints on the
cosmic ray diffusion coefficient in the region can be obtained, under the
assumption that the cosmic rays responsible for the gamma ray emission have
been accelerated in the past at the supernova remnant shock, and subsequently
escaped in the surrounding medium. In this scenario, gamma ray observations can
be explained only if the diffusion coefficient in the region surrounding the
supernova remnant is significantly suppressed with respect to the average
galactic one.Comment: To appear in the proceedings of "Journ\'ees de la SF2A 2010"
Marseille 21-24 June 2010, 4 pages, 4 figure
Quality Assurance Indicators of Long-Term Care in European Countries
This study reports on the quality indicators that were collected by the ANCIEN project partners in each country
considered in Work Package 5 (Quality in Long-Term Care). The main contribution of this report is a classification of
the quality assurance indicators in different European countries according to three dimensions: organisation type
(indicators applied to formal institutional care \u2013 FIC, formal home-based care \u2013 FHBC, formal home nursing care -
FHNC, and informal home care - IHC); quality dimensions (indicators about effectiveness, safety, patient value
responsiveness, or coordination) and system dimensions (input, process, or outcome indicators). The countries that
provided quality indicators, which are used at a national level or are recommended to be used at a local level by a
national authority, are: Estonia, Finland, France, Germany, Hungary, Italy, Latvia, the Netherlands, Spain, Sweden and
the United Kingdom. In total, we collected 390 quality indicators. Each quality indicator has been assigned to one or
more options in each dimension
Deep Strong Coupling Regime of the Jaynes-Cummings model
We study the quantum dynamics of a two-level system interacting with a
quantized harmonic oscillator in the deep strong coupling regime (DSC) of the
Jaynes-Cummings model, that is, when the coupling strength g is comparable or
larger than the oscillator frequency w (g/w > 1). In this case, the
rotating-wave approximation cannot be applied or treated perturbatively in
general. We propose an intuitive and predictive physical frame to describe the
DSC regime where photon number wavepackets bounce back and forth along parity
chains of the Hilbert space, while producing collapse and revivals of the
initial population. We exemplify our physical frame with numerical and
analytical considerations in the qubit population, photon statistics, and
Wigner phase space.Comment: Published version, note change of title: DSC regime of the JC mode
Zeno physics in ultrastrong circuit QED
We study the Zeno and anti-Zeno effects in a superconducting qubit
interacting strongly and ultrastrongly with a microwave resonator. Using a
model of a frequently measured two-level system interacting with a quantized
mode, we show different behaviors and total control of the Zeno times depending
on whether the rotating-wave approximation can be applied in the
Jaynes-Cummings model, or not. We exemplify showing the strong dependence of
our results with the properties of the initial field states and suggest
applications for quantum tomography.Comment: 5 pages, 3 figure
Digital Quantum Simulation of the Holstein Model in Trapped Ions
We propose the implementation of the Holstein model by means of digital
methods in a linear chain of trapped ions. We show how the simulation fidelity
scales with the generation of phononic excitations. We propose a decomposition
and a stepwise trapped-ion implementation of the Holstein Hamiltonian. Via
numerical simulations, we study how the protocol is affected by realistic
gates. Finally, we show how measurements of the size of the simulated polaron
can be performed.Comment: 5 pages + supplemental material, 3+3 figures. Accepted in Physical
Review Letter
Measuring Entanglement in a Photonic Embedding Quantum Simulator
Measuring entanglement is a demanding task that usually requires full
tomography of a quantum system, involving a number of observables that grows
exponentially with the number of parties. Recently, it was suggested that
adding a single ancillary qubit would allow for the efficient measurement of
concurrence, and indeed any entanglement monotone associated to antilinear
operations. Here, we report on the experimental implementation of such a
device---an embedding quantum simulator---in photonics, encoding the entangling
dynamics of a bipartite system into a tripartite one. We show that bipartite
concurrence can be efficiently extracted from the measurement of merely two
observables, instead of fifteen, without full tomographic information.Comment: Updated versio
A systematic comparison of supervised classifiers
Pattern recognition techniques have been employed in a myriad of industrial,
medical, commercial and academic applications. To tackle such a diversity of
data, many techniques have been devised. However, despite the long tradition of
pattern recognition research, there is no technique that yields the best
classification in all scenarios. Therefore, the consideration of as many as
possible techniques presents itself as an fundamental practice in applications
aiming at high accuracy. Typical works comparing methods either emphasize the
performance of a given algorithm in validation tests or systematically compare
various algorithms, assuming that the practical use of these methods is done by
experts. In many occasions, however, researchers have to deal with their
practical classification tasks without an in-depth knowledge about the
underlying mechanisms behind parameters. Actually, the adequate choice of
classifiers and parameters alike in such practical circumstances constitutes a
long-standing problem and is the subject of the current paper. We carried out a
study on the performance of nine well-known classifiers implemented by the Weka
framework and compared the dependence of the accuracy with their configuration
parameter configurations. The analysis of performance with default parameters
revealed that the k-nearest neighbors method exceeds by a large margin the
other methods when high dimensional datasets are considered. When other
configuration of parameters were allowed, we found that it is possible to
improve the quality of SVM in more than 20% even if parameters are set
randomly. Taken together, the investigation conducted in this paper suggests
that, apart from the SVM implementation, Weka's default configuration of
parameters provides an performance close the one achieved with the optimal
configuration
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