The Rare Decay D^0 -> gamma gamma

We present a calculation of the rare decay mode D^0 -> gamma gamma, in which the long distance contributions are expected to be dominant. Using the Heavy Quark Chiral Perturbation Theory Lagrangian with a strong g coupling as recently determined by CLEO from the D^* -> D pi width, we consider both the anomaly contribution which relates to the annihilation part of the weak Lagrangian and the one-loop pi, K diagrams. The loop contributions which are proportional to g and contain the a_1 Wilson coefficient are found to dominate the decay amplitude, which turns out to be mainly parity violating. The branching ratio is then calculated to be (1.0+-0.5)x10^(-8). Observation of an order of magnitude larger branching ratio could be indicative of new physics.Comment: 16 pages, 5 figures, additional reference and several remarks added, results unchange

Air and water pollution over time and industries with stochastic dominance

We employ a stochastic dominance (SD) approach to analyze the components that contribute to environmental degradation over time. The variables include countries\u2019 greenhouse gas (GHG) emissions and water pollution. Our approach is based on pair-wise SD tests. First, we study the dynamic progress of each separate variable over time, from 1990 to 2005, within 5-year horizons. Then, pair-wise SD tests are used to study the major industry contributors to the overall GHG emissions and water pollution at any given time, to uncover the industry which contributes the most to total emissions and water pollution. While CO2 emissions increased in the first order SD sense over 15 years, water pollution increased in a second-order SD sense. Electricity and heat production were the major contributors to the CO2 emissions, while the food industry gradually became the major water polluting industry over time. SD sense over 15 years, water pollution increased in a second-order SD sense. Electricity and heat production were the major contributors to the CO2 emissions, while the food industry gradually

A benchmarking exercise for environmental contours

Environmental contours are used to simplify the process of design response analysis. A wide variety of contour methods exist; however, there have been a very limited number of comparisons of these methods to date. This paper is the output of an open benchmarking exercise, in which contributors developed contours based on their preferred methods and submitted them for a blind comparison study. The exercise had two components—one, focusing on the robustness of contour methods across different offshore sites and, the other, focusing on characterizing sampling uncertainty. Nine teams of researchers contributed to the benchmark. The analysis of the submitted contours highlighted significant differences between contours derived via different methods. For example, the highest wave height value along a contour varied by as much as a factor of two between some submissions while the number of metocean data points or observations that fell outside a contour deviated by an order of magnitude between the contributions (even for contours with a return period shorter than the duration of the record). These differences arose from both different joint distribution models and different contour construction methods, however, variability from joint distribution models appeared to be higher than variability from contour construction methods