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 $E_{\rm dis}^2=E_{\vec{k}}^2-E_0^2-4\sum_{i=1}^{d-1}\sin(k_i/2)^2$ is in both cases negative ($d$ is the Euclidean space-time dimension and $E_{\vec{k}}$ the energy of momentum $\vec{k}$ eigenstates). Observation of $E_{\rm dis}^2=0$ has been an accepted method to demonstrate the existence of a massless photon ($E_0=0$) 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 $E_0$ and the mass parameter $M$ of the free scalar lattice action. Instead, the relation $E_0=\cosh^{-1} (1+M^2/2)$ 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

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