868 research outputs found
Spin-lattice interactions of ions with unfilled F-shells measured by ESR in uniaxially stressed crystals
Spin-lattice interactions of ions with unfilled F-shells measured by electron spin resonance in uniaxially stressed crystal
Direct one-phonon spin-lattice relaxation times for Nd sup 3 plus and U sup 3 plus ions in CaF sub 2 in sites of tetragonal symmetry
Phonon spin-lattice relaxation times for uranium and neodymium ions in calcium fluorid
On the irreversibility of entanglement distillation
We investigate the irreversibility of entanglement distillation for a
symmetric d-1 parameter family of mixed bipartite quantum states acting on
Hilbert spaces of arbitrary dimension d x d. We prove that in this family the
entanglement cost is generically strictly larger than the distillable
entanglement, such that the set of states for which the distillation process is
asymptotically reversible is of measure zero. This remains true even if the
distillation process is catalytically assisted by pure state entanglement and
every operation is allowed, which preserves the positivity of the partial
transpose. It is shown, that reversibility occurs only in cases where the state
is quasi-pure in the sense that all its pure state entanglement can be revealed
by a simple operation on a single copy. The reversible cases are shown to be
completely characterized by minimal uncertainty vectors for entropic
uncertainty relations.Comment: 5 pages, revtex
Spin-lattice Interaction in Ruby Measured by ESR in Uniaxially Stressed Crystals
Spin-lattice Hamiltonian determined for chromium ions in ruby single crystal
Yet another breakdown point notion: EFSBP - illustrated at scale-shape models
The breakdown point in its different variants is one of the central notions
to quantify the global robustness of a procedure. We propose a simple
supplementary variant which is useful in situations where we have no obvious or
only partial equivariance: Extending the Donoho and Huber(1983) Finite Sample
Breakdown Point, we propose the Expected Finite Sample Breakdown Point to
produce less configuration-dependent values while still preserving the finite
sample aspect of the former definition. We apply this notion for joint
estimation of scale and shape (with only scale-equivariance available),
exemplified for generalized Pareto, generalized extreme value, Weibull, and
Gamma distributions. In these settings, we are interested in highly-robust,
easy-to-compute initial estimators; to this end we study Pickands-type and
Location-Dispersion-type estimators and compute their respective breakdown
points.Comment: 21 pages, 4 figure
Position and momentum observables on R and on R^3
We characterize all position and momentum observables on R and on R^3. We
study some of their operational properties and discuss their covariant joint
observables.Comment: 18 page
Analysis of the Spatial Distribution of Galaxies by Multiscale Methods
Galaxies are arranged in interconnected walls and filaments forming a cosmic
web encompassing huge, nearly empty, regions between the structures. Many
statistical methods have been proposed in the past in order to describe the
galaxy distribution and discriminate the different cosmological models. We
present in this paper results relative to the use of new statistical tools
using the 3D isotropic undecimated wavelet transform, the 3D ridgelet transform
and the 3D beamlet transform. We show that such multiscale methods produce a
new way to measure in a coherent and statistically reliable way the degree of
clustering, filamentarity, sheetedness, and voidedness of a datasetComment: 26 pages, 20 figures. Submitted to EURASIP Journal on Applied Signal
Processing (special issue on "Applications of Signal Processing in
Astrophysics and Cosmology"
Heartbeat Classification in Wearables Using Multi-layer Perceptron and Time-Frequency Joint Distribution of ECG
Heartbeat classification using electrocardiogram (ECG) data is a vital
assistive technology for wearable health solutions. We propose heartbeat
feature classification based on a novel sparse representation using
time-frequency joint distribution of ECG. Fundamental to this is a multi-layer
perceptron, which incorporates these signatures to detect cardiac arrhythmia.
This approach is validated with ECG data from MIT-BIH arrhythmia database.
Results show that our approach has an average 95.7% accuracy, an improvement of
22% over state-of-the-art approaches. Additionally, ECG sparse distributed
representations generates only 3.7% false negatives, reduction of 89% with
respect to existing ECG signal classification techniques.Comment: 6 pages, 7 figures, published in IEEE/ACM International Conference on
Connected Health: Applications, Systems and Engineering Technologies (CHASE
Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data
The Herschel Space Observatory of ESA was launched in May 2009 and is in
operation since. From its distant orbit around L2 it needs to transmit a huge
quantity of information through a very limited bandwidth. This is especially
true for the PACS imaging camera which needs to compress its data far more than
what can be achieved with lossless compression. This is currently solved by
including lossy averaging and rounding steps on board. Recently, a new theory
called compressed-sensing emerged from the statistics community. This theory
makes use of the sparsity of natural (or astrophysical) images to optimize the
acquisition scheme of the data needed to estimate those images. Thus, it can
lead to high compression factors.
A previous article by Bobin et al. (2008) showed how the new theory could be
applied to simulated Herschel/PACS data to solve the compression requirement of
the instrument. In this article, we show that compressed-sensing theory can
indeed be successfully applied to actual Herschel/PACS data and give
significant improvements over the standard pipeline. In order to fully use the
redundancy present in the data, we perform full sky map estimation and
decompression at the same time, which cannot be done in most other compression
methods. We also demonstrate that the various artifacts affecting the data
(pink noise, glitches, whose behavior is a priori not well compatible with
compressed-sensing) can be handled as well in this new framework. Finally, we
make a comparison between the methods from the compressed-sensing scheme and
data acquired with the standard compression scheme. We discuss improvements
that can be made on ground for the creation of sky maps from the data.Comment: 11 pages, 6 figures, 5 tables, peer-reviewed articl
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