Convergence of Discretized Light Cone Quantization in the small mass limit

I discuss the slow convergence of Discretized Light Cone Quantization (DLCQ) in the small mass limit and suggest a solution.Comment: 8 pages, 5 Postscript figures, uses boxedeps.te

Fodder Shrubs for Improving Incomes of Dairy Farmers in the East African Highlands

Smallholder dairying is an important enterprise in the highlands of E Africa. Farm sizes average 1-2ha and zero-grazing, cut-and-carry systems predominate. Inadequate protein reduces milk production and forces many farmers to spend scarce cash on commercial dairy meal supplements. In 1991, on-farm trials on fodder shrubs were started in Embu District as a collaborative venture of the Kenya Agricultural Research Institute, the Kenya Forestry Research Institute, and the World Agroforestry Centre. Calliandra calothyrsus was released to farmers in 1995 and was followed by Leucaena trichandra, mulberry (Morus alba), and Sesbania sesban. Farmers produce seedlings of calliandra and trichandra in nurseries; mulberry is planted using cuttings. Farmers plant the shrubs in hedges along field and farm boundaries, on contour bunds, and intercropped with Napier grass. Within 1 year after planting, shrubs are ready to be pruned for feeding livestock. Most farmers cut them at a height of about 1m to ensure that they do not shade the adjacent crops (Franzel et al., 2003)

ImageNet Large Scale Visual Recognition Challenge

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The challenge has been run annually from 2010 to present, attracting participation from more than fifty institutions. This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field of large-scale image classification and object detection, and compare the state-of-the-art computer vision accuracy with human accuracy. We conclude with lessons learned in the five years of the challenge, and propose future directions and improvements.Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional reference

Transverse Lattice Approach to Light-Front Hamiltonian QCD

We describe a non-perturbative procedure for solving from first principles the light-front Hamiltonian problem of SU(N) pure gauge theory in D spacetime dimensions (D>2), based on enforcing Lorentz covariance of observables. A transverse lattice regulator and colour-dielectric link fields are employed, together with an associated effective potential. We argue that the light-front vacuum is necessarily trivial for large enough lattice spacing, and clarify why this leads to an Eguchi-Kawai dimensional reduction of observables to 1+1-dimensions in the infinite N limit. The procedure is then tested by explicit calculations for 2+1-dimensional SU(infinity) gauge theory, within a first approximation to the lattice effective potential. We identify a scaling trajectory which produces Lorentz covariant behaviour for the lightest glueballs. The predicted masses, in units of the measured string tension, are in agreement with recent results from conventional Euclidean lattice simulations. In addition, we obtain the potential between heavy sources and the structure of the glueballs from their light-front wavefunctions. Finally, we briefly discuss the extension of these calculations to 3+1-dimensions.Comment: 55 pages, uses macro boxedeps.tex, minor corrections in revised versio

Glueball calculations in large-N_c gauge theory

We use the light-front Hamiltonian of transverse lattice gauge theory to compute from first principles the glueball spectrum and light-front wavefunctions in the leading order of the 1/N_c colour expansion. We find 0^{++}, 2^{++}, and 1^{+-} glueballs having masses consistent with N_c=3 data available from Euclidean lattice path integral methods. The wavefunctions exhibit a light-front constituent gluon structure.Comment: 4 pages, 2 figures, uses macro boxedeps.tex, minor corrections in revised versio

Colour-Dielectric Gauge Theory on a Transverse Lattice

We investigate in some detail consequences of the effective colour-dielectric formulation of lattice gauge theory using the light-cone Hamiltonian formalism with a transverse lattice. As a quantitative test of this approach, we have performed extensive analytic and numerical calculations for 2+1-dimensional pure gauge theory in the large N limit. Because of Eguchi-Kawai reduction, one effectively studies a 1+1-dimensional gauge theory coupled to matter in the adjoint representation. We study the structure of coupling constant space for our effective potential by comparing with the physical results available from conventional Euclidean lattice Monte Carlo simulations of this system. In particular, we calculate and measure the scaling behaviour of the entire low-lying glueball spectrum, glueball wavefunctions, string tension, asymptotic density of states, and deconfining temperature. We employ a new hybrid DLCQ/wavefunction basis in our calculations of the light-cone Hamiltonian matrix elements, along with extrapolation in Tamm-Dancoff truncation, significantly reducing numerical errors. Finally we discuss, in light of our results, what further measurements and calculations could be made in order to systematically remove lattice spacing dependence from our effective potential a priori.Comment: 48 pages, Latex, uses macro boxedeps.tex, minor errors corrected in revised versio

Improved instrumental magnitude prediction expected from version 2 of the NASA SKY2000 master star catalog

The SKY2000 Master Star Catalog (MC), Version 2 and its predecessors have been designed to provide the basic astronomical input data needed for satellite acquisition and attitude determination on NASA spacecraft. Stellar positions and proper motions are the primary MC data required for operations support followed closely by the stellar brightness observed in various standard astronomical passbands. The instrumental red-magnitude prediction subsystem (REDMAG) in the MMSCAT software package computes the expected instrumental color index (CI) [sensor color correction] from an observed astronomical stellar magnitude in the MC and the characteristics of the stellar spectrum, astronomical passband, and sensor sensitivity curve. The computation is more error prone the greater the mismatch of the sensor sensitivity curve characteristics and those of the observed astronomical passbands. This paper presents the preliminary performance analysis of a typical red-sensitive CCDST during acquisition of sensor data from the two Ball CT-601 ST's onboard the Rossi X-Ray Timing Explorer (RXTE). A comparison is made of relative star positions measured in the ST FOV coordinate system with the expected results computed from the recently released Tycho Catalogue. The comparison is repeated for a group of observed stars with nearby, bright neighbors in order to determine the tracker behavior in the presence of an interfering, near neighbor (NN). The results of this analysis will be used to help define a new photoelectric photometric instrumental sensor magnitude system (S) that is based on several thousand bright star magnitudes observed with the PXTE ST's. This new system will be implemented in Version 2 of the SKY2000 MC to provide improved predicted magnitudes in the mission run catalogs

The SAMI Galaxy Survey: Satellite galaxies undergo little structural change during their quenching phase

At fixed stellar mass, satellite galaxies show higher passive fractions than centrals, suggesting that environment is directly quenching their star formation. Here, we investigate whether satellite quenching is accompanied by changes in stellar spin (quantified by the ratio of the rotational to dispersion velocity V/$\sigma$) for a sample of massive ($M_{*}>$10$^{10}$ M$_{\odot}$) satellite galaxies extracted from the SAMI Galaxy Survey. These systems are carefully matched to a control sample of main sequence, high $V/\sigma$ central galaxies. As expected, at fixed stellar mass and ellipticity, satellites have lower star formation rate (SFR) and spin than the control centrals. However, most of the difference is in SFR, whereas the spin decreases significantly only for satellites that have already reached the red sequence. We perform a similar analysis for galaxies in the EAGLE hydro-dynamical simulation and recover differences in both SFR and spin similar to those observed in SAMI. However, when EAGLE satellites are matched to their `true' central progenitors, the change in spin is further reduced and galaxies mainly show a decrease in SFR during their satellite phase. The difference in spin observed between satellites and centrals at $z\sim$0 is primarily due to the fact that satellites do not grow their angular momentum as fast as centrals after accreting into bigger halos, not to a reduction of $V/\sigma$ due to environmental effects. Our findings highlight the effect of progenitor bias in our understanding of galaxy transformation and they suggest that satellites undergo little structural change before and during their quenching phase.Comment: 11 pages, 7 figures. Accepted for publication in MNRA

A COMPUTATIONALLY CHEAP TRICK TO DETERMINE SHADOW IN A VOXEL MODEL

Representation of scenes on the Earth surface by using voxels is gaining attention because of its suitability for integrating heterogeneous data sources in simulations and quantitative models. Computation of shadows in such models is needed, for example, to obtain crop suitability of agricultural fields in the presence of trees and buildings, or to analyze urban heat island causes and effects. We present an efficient algorithm to compute which of the voxels in a dataset receive direct sunlight, given the solar azimuth and elevation angles. The algorithm can work with multiple (sparse and dense) voxel storage strategies