Non-commutative Gross-Neveu model at large N

The non-commutative O(N) Gross-Neveu model is solved in the large N limit in two and three space-time dimensions. The commutative version of the two dimensional model is a renormalizable quantum field theory, both in a coupling constant expansion and an expansion in 1/N. The non-commutative version has a renormalizable coupling constant expansion where ultraviolet divergences can be removed by adjusting counterterms to each order. On the other hand, in a previous work, we showed that the non-commutative theory is not renormalizable in the large N expansion. This is argued to be due to a combined effect of asymptotic freedom and the ultraviolet/infrared mixing that occurs in a non-commutative field theory. In the present paper we will elaborate on this result and extend it to study the large N limit of the three dimensional Gross-Neveu model. We shall see that the large N limit of the three dimensional theory is also trivial when the ultraviolet cutoff is removed.Comment: 23 page

The Effects of Tank Operation and Design Characteristics on Water Quality in Distribution System Storage Tanks

From the Executive Summary Background: Regional water systems utilize storage facilities to meet demand variations and pressure requirements of their systems. These storage facilities drain and fill in response to system water demands and water level control settings. Storage tanks are typically placed in strategic locations to maintain a consistent pressure in the distribution system. Storage facilities should be designed and operated such that the water is mixed to prevent stagnant water (old water that remains in the tank for an extended period). Stagnant water can lead to water quality issues, such as low disinfectant residuals, potential for microbial contamination, disinfectant by-product formation, and nitrification in chloraminated waters. Many tanks have been built without consideration of mixing. These tanks might have a single inlet/outlet, high height to diameter ratio, or have other design characteristics that do not promote mixing. Whether by design or not, tanks without artificial mixing depend upon movement of water during the filling process to mix the tank. A wide array of storage tank types and geometries are utilized in South Dakota’s regional rural water systems. Greater understanding of the relationships of these tank characteristics on stored water quality would enable water systems to optimize the design and operation of their tanks. Objective of Study:The objective of this study was to examine the impacts of tank design and operation on mixing and water quality in storage tanks in South Dakota’s regional rural water systems. This objective was met through a literature review, a survey of system characteristics and evaluation of water quality data obtained from several storage tanks

Study of leakage currents in pCVD diamonds as function of the magnetic field

pCVD diamond sensors are regularly used as beam loss monitors in accelerators by measuring the ionization of the lost particles. In the past these beam loss monitors showed sudden increases in the dark leakage current without beam losses and these erratic leakage currents were found to decrease, if magnetic fields were present. Here we report on a systematic study of leakage currents inside a magnetic field. The decrease of erratic currents in a magnetic field was confirmed. On the contrary, diamonds without erratic currents showed an increase of the leakage current in a magnetic field perpendicular to the electric field for fields up to 0.6T, for higher fields it decreases. A preliminary model is introduced to explain the observations.Comment: 6 pages, 16 figures, poster at Hasselt Diamond Workshop, Mar 2009, accepted version for publicatio

CALCULATION OF RADIAL NEUTRON-FLUX DISTRIBUTION IN EGCR LATTICE CELL

The neutron flux distributions in an EGCR cell containing seven and clusters of 2.0 and 2.6a enriched uranium odde were obtained by using a one- velocity, one-dimensional P-3 solution to the neutron transport equation and adjusting fluxes in the fuel cluster in a manner which is consistent with previous comparisons of experiments and calculated distributions. Flux traverses in the outer rod perpendicular to diameter of the cluster are also presented. (auth

An experimental approach to estimating the value of grain moisture information to farmers in Bangladesh

In the developing world grain storage losses are high and in humid areas inadequate grain drying is often a source of storage problems. Farmers and traders depend on traditional grain moisture estimation methods which are subject to a wide error margin. Grain storage decisions could be improved if farmers and traders had a low cost grain moisture meter that fit their needs. The goal of this study was to determine the desired grain moisture meter functionality and to estimate the value of grain moisture measurement for small holder farmers and for small-scale grain traders, using Bangladesh as a case study. This study was based on interviews with 140 randomly selected Bangladeshi rice farmers in 2016 and 2017, discussions with millers at 30 rice mills and a voucher based moisture meter sales program. It shows that except for rice kept for seed and home consumption, most Bangladeshi farmers sell their rice shortly after harvest to satisfy cash needs and to eliminate storage risks. They say that they would store more rice on-farm if they had better storage methods including cost-effective grain moisture testing. Survey results show that the average farm storage loss was 52 kg or 563 Taka (US$6.78) annually. Using experimental economics methods, farmers were given the opportunity to purchase a probe type grain moisture meter through vouchers with a range of prices. Twenty three of the 140 of the participants (i.e. 16$4.67). No farmer purchased a voucher price over 800 Taka (US$10.00). Those who purchased moisture meters had larger farms and produced more rice than those who did not exercise the voucher. They were also younger on average, have more education and more off farm income than non-purchasers

A multi-scale multi-frequency deconvolution algorithm for synthesis imaging in radio interferometry

Aims : We describe MS-MFS, a multi-scale multi-frequency deconvolution algorithm for wide-band synthesis-imaging, and present imaging results that illustrate the capabilities of the algorithm and the conditions under which it is feasible and gives accurate results. Methods : The MS-MFS algorithm models the wide-band sky-brightness distribution as a linear combination of spatial and spectral basis functions, and performs image-reconstruction by combining a linear-least-squares approach with iterative $\chi^2$ minimization. This method extends and combines the ideas used in the MS-CLEAN and MF-CLEAN algorithms for multi-scale and multi-frequency deconvolution respectively, and can be used in conjunction with existing wide-field imaging algorithms. We also discuss a simpler hybrid of spectral-line and continuum imaging methods and point out situations where it may suffice. Results : We show via simulations and application to multi-frequency VLA data and wideband EVLA data, that it is possible to reconstruct both spatial and spectral structure of compact and extended emission at the continuum sensitivity level and at the angular resolution allowed by the highest sampled frequency.Comment: 17 pages, 11 figure

The application of compressive sampling to radio astronomy I: Deconvolution

Compressive sampling is a new paradigm for sampling, based on sparseness of signals or signal representations. It is much less restrictive than Nyquist-Shannon sampling theory and thus explains and systematises the widespread experience that methods such as the H\"ogbom CLEAN can violate the Nyquist-Shannon sampling requirements. In this paper, a CS-based deconvolution method for extended sources is introduced. This method can reconstruct both point sources and extended sources (using the isotropic undecimated wavelet transform as a basis function for the reconstruction step). We compare this CS-based deconvolution method with two CLEAN-based deconvolution methods: the H\"ogbom CLEAN and the multiscale CLEAN. This new method shows the best performance in deconvolving extended sources for both uniform and natural weighting of the sampled visibilities. Both visual and numerical results of the comparison are provided.Comment: Published by A&A, Matlab code can be found: http://code.google.com/p/csra/download

Modeling local terrain attributes in landscape-scale site-specific data using spatially lagged independent variable via cross regression

Analysis methods for landscape-scale site-specific agricultural datasets have been adapted from a wide range of quantitative disciplines. Due to spatial effects expected at landscape scales with respect to yield affecting factors, inference from aspatial analyses may lead to inefficient statistical inference. When spatial correlation exists within a random variable e.g. explanatory variables such as elevation or soil characteristics, spatial statistical methods can provide unbiased and efficient estimates on which to base economic analyses and farm management decisions. Simple continuous terrain variables derived from spatially lagged independent variable transformation of relative terrain position allowed models to be estimated using familiar linear aspatial models without introducing the problems associated with interpolated data in inferential spatial statistics. Using site-specific data from three example fields, cross regressive elevation variables complemented topographic attributes, rather than replacing them in a range of statistical models. Results indicated that cross regressive elevation variables, especially relative elevation, reduced estimation problems due to correlation among independent variables and bias arising from spatially interpolated data in statistical analysis

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another