62,779 research outputs found
On the energy momentum dispersion in the lattice regularization
For a free scalar boson field and for U(1) gauge theory finite volume
(infrared) and other corrections to the energy-momentum dispersion in the
lattice regularization are investigated calculating energy eigenstates from the
fall off behavior of two-point correlation functions. For small lattices the
squared dispersion energy defined by is in both cases
negative ( is the Euclidean space-time dimension and the
energy of momentum eigenstates). Observation of has
been an accepted method to demonstrate the existence of a massless photon
() in 4D lattice gauge theory, which we supplement here by a study of
its finite size corrections. A surprise from the lattice regularization of the
free field is that infrared corrections do {\it not} eliminate a difference
between the groundstate energy and the mass parameter of the free
scalar lattice action. Instead, the relation is
derived independently of the spatial lattice size.Comment: 9 pages, 2 figures. Parts of the paper have been rewritten and
expanded to clarify the result
Fiber Orientation Estimation Guided by a Deep Network
Diffusion magnetic resonance imaging (dMRI) is currently the only tool for
noninvasively imaging the brain's white matter tracts. The fiber orientation
(FO) is a key feature computed from dMRI for fiber tract reconstruction.
Because the number of FOs in a voxel is usually small, dictionary-based sparse
reconstruction has been used to estimate FOs with a relatively small number of
diffusion gradients. However, accurate FO estimation in regions with complex FO
configurations in the presence of noise can still be challenging. In this work
we explore the use of a deep network for FO estimation in a dictionary-based
framework and propose an algorithm named Fiber Orientation Reconstruction
guided by a Deep Network (FORDN). FORDN consists of two steps. First, we use a
smaller dictionary encoding coarse basis FOs to represent the diffusion
signals. To estimate the mixture fractions of the dictionary atoms (and thus
coarse FOs), a deep network is designed specifically for solving the sparse
reconstruction problem. Here, the smaller dictionary is used to reduce the
computational cost of training. Second, the coarse FOs inform the final FO
estimation, where a larger dictionary encoding dense basis FOs is used and a
weighted l1-norm regularized least squares problem is solved to encourage FOs
that are consistent with the network output. FORDN was evaluated and compared
with state-of-the-art algorithms that estimate FOs using sparse reconstruction
on simulated and real dMRI data, and the results demonstrate the benefit of
using a deep network for FO estimation.Comment: A shorter version is accepted by MICCAI 201
Economic value of pollination services on crops in Benin, West Africa
Pollinators provide pollination services that are crucial for sexual reproduction of many flowering plants. Beside wind and water, pollination services are provided by animals but mainly by insects. They improve the quality and the quantity of many crops. This study aimed at accessing the economic value of pollination services on selected crops in 2010 in Benin. Thus, 29 valued crops were considered and their individual pollination service values obtained from literature. At national scale, the individual gains in production due to pollination services of the selected crops were summed. In this study, all crops used for the calculation require pollination services and their economic added values were estimated to about 99,866.44 billion of local currency (FCFA) (that equal US $ 199.21 million) in 2010. This contributes substantially to the economy of Benin (3.03% of GDP). These results reveal the need to pay more attention to pollinators and their services in agricultural policies definition in Benin. We suggest a rational use of pesticides in agriculture and the preference of traditional practices in agriculture such as the preservation of few native plants in farming areas to give opportunity to conserve pollinators in these areas.Keywords: Added value, agriculture, conservation, pollinators
GHZ-type and W-type entangled coherent states: generation and Bell-type inequality tests without photon counting
We study GHZ-type and W-type three-mode entangled coherent states. Both the
types of entangled coherent states violate Mermin's version of the Bell
inequality with threshold photon detection (i.e., without photon counting).
Such an experiment can be performed using linear optics elements and threshold
detectors with significant Bell violations for GHZ-type entangled coherent
states. However, to demonstrate Bell-type inequality violations for W-type
entangled coherent states, additional nonlinear interactions are needed. We
also propose an optical scheme to generate W-type entangled coherent states in
free-traveling optical fields. The required resources for the generation are a
single-photon source, a coherent state source, beam splitters, phase shifters,
photodetectors, and Kerr nonlinearities. Our scheme does not necessarily
require strong Kerr nonlinear interactions, i.e., weak nonlinearities can be
used for the generation of the W-type entangled coherent states. Furthermore,
it is also robust against inefficiencies of the single-photon source and the
photon detectors.Comment: 8 pages, 5 figures, to be published in Phys. Rev.
Multi-lepton signals from the top-prime quark at the LHC
We analyze the collider signatures of models with a vector-like top-prime
quark and a massive color-octet boson. The top-prime quark mixes with the top
quark in the Standard Model, leading to richer final states than ones that are
investigated by experimental collaborations. We discuss the multi-lepton final
states, and show that they can provide increased sensitivity to models with a
top-prime quark and gluon-prime. Searches for new physics in high multiplicity
events are an important component of the LHC program and complementary to
analyses that have been performed.Comment: 7 pages, 4 figures, 2 table
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Spectral signature of ice clouds in the far-infrared region: Single-scattering calculations and radiative sensitivity study
Characterization of the surface roughness of sand particles using an advanced fractal approach
The surface roughness of soil grains affects the mechanical behaviour of soils, but the characterization of real soil grain roughness is still limited in both quantity and quality. A new method is proposed, which applies the power spectral density (PSD), typically used in tribology, to optical interferometry measurements of soil grain surfaces. The method was adapted to characterize the roughness of soil grains separately from their shape, allowing the scale of the roughness to be determined in the form of a wavevector range. The surface roughness can be characterized by a roughness value and a fractal dimension, determined based on the stochastic formation process of the surface. When combined with other parameters, the fractal dimension provides additional information about the surface structure and roughness to the value of roughness alone. Three grain sizes of a quarzitic sand were tested. The parameters determined from the PSD analysis were input directly into a Weierstrass–Mandelbrot function to reconstruct successfully a fractal surface
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