29,306 research outputs found
Insights from ARPES for an undoped, four-layered, two-gap high-T_c superconductor
An undoped cuprate with apical fluorine and inner (i) and outer (o)
CuO2-layers is a 60 K superconductor whose Fermi surface (FS) has large n- and
p-doped sheets with the SC gap on the n-sheet twice that on the p -sheet (Y.
Chen et al.). The Fermi surface is not reproduced by the LDA, but the screening
must be substantially reduced due to electronic correlations, and oxygen in the
o-layers must be allowed to dimple outwards. This charges the i-layers by
0.01|e|, causes an 0.4 eV Madelung-potential difference between the i and o
-layers, quenches the i-o hopping, and localizes the n-sheets onto the
i-layers, thus protecting their d-wave pairs from being broken by scattering on
impurities in the BaF layers. The correlation-reduced screening strengthens the
coupling to z-axis phonons.Comment: 4 pages, 3 figure
Identification of Long-lived Charged Particles using Time-Of-Flight Systems at the Upgraded LHC detectors
We study the impact of picosecond precision timing detection systems on the
LHC experiments' long-lived particle search program during the HL-LHC era. We
develop algorithms that allow us to reconstruct the mass of such charged
particles and perform particle identification using the time-of-flight
measurement. We investigate the reach for benchmark scenarios as a function of
the timing resolution, and find sensitivity improvement of up to a factor of
ten, depending on the new heavy particle mass.Comment: 20 pages, 13 figure
Semi-supervised Multi-sensor Classification via Consensus-based Multi-View Maximum Entropy Discrimination
In this paper, we consider multi-sensor classification when there is a large
number of unlabeled samples. The problem is formulated under the multi-view
learning framework and a Consensus-based Multi-View Maximum Entropy
Discrimination (CMV-MED) algorithm is proposed. By iteratively maximizing the
stochastic agreement between multiple classifiers on the unlabeled dataset, the
algorithm simultaneously learns multiple high accuracy classifiers. We
demonstrate that our proposed method can yield improved performance over
previous multi-view learning approaches by comparing performance on three real
multi-sensor data sets.Comment: 5 pages, 4 figures, Accepted in 40th IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP 15
GhostVLAD for set-based face recognition
The objective of this paper is to learn a compact representation of image
sets for template-based face recognition. We make the following contributions:
first, we propose a network architecture which aggregates and embeds the face
descriptors produced by deep convolutional neural networks into a compact
fixed-length representation. This compact representation requires minimal
memory storage and enables efficient similarity computation. Second, we propose
a novel GhostVLAD layer that includes {\em ghost clusters}, that do not
contribute to the aggregation. We show that a quality weighting on the input
faces emerges automatically such that informative images contribute more than
those with low quality, and that the ghost clusters enhance the network's
ability to deal with poor quality images. Third, we explore how input feature
dimension, number of clusters and different training techniques affect the
recognition performance. Given this analysis, we train a network that far
exceeds the state-of-the-art on the IJB-B face recognition dataset. This is
currently one of the most challenging public benchmarks, and we surpass the
state-of-the-art on both the identification and verification protocols.Comment: Accepted by ACCV 201
Anisotropies in insulating LaSrCuO: angular resolved photoemission and optical absorption
Due to the orthorhombic distortion of the lattice, the electronic hopping
integrals along the and diagonals, the orthorhombic directions, are
slightly different. We calculate their difference in the LDA and find
meV. We argue that electron
correlations in the insulating phase of LaSrCuO, i. e. at
doping dramatically enhance the -splitting between the - and -hole valleys. In particular, we predict
that the intensity of both angle-resolved photoemission and of optical
absorption is very different for the and nodal points
Surface-wave interferometry on single subwavelength slit-groove structures fabricated on gold films
We apply the technique of far-field interferometry to measure the properties
of surface waves generated by two-dimensional (2D) single subwavelength
slit-groove structures on gold films. The effective surface index of refraction
measured for the surface wave propagating over a distance of more than 12
microns is determined to be 1.016 with a measurement uncertainty of 0.004, to
within experimental uncertainty of the expected bound surface plasmon-polariton
(SPP) value for a Au/Air interface of 1.018. We compare these measurements to
finite-difference-time-domain (FDTD) numerical simulations of the optical field
transmission through these devices. We find excellent agreement between the
measurements and the simulations for the surface index of refraction. The
measurements also show that the surface wave propagation parameter exhibits
transient behavior close to the slit, evolving smoothly from greater values
asymptotically toward the value expected for the SPP over the first 2-3 microns
of slit-groove distance. This behavior is confirmed by the FDTD simulations
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