Modelling cost-effective air pollution abatement: a multi-period linear programming approach

Improvements in air quality for some criteria pollutants in Sydney, Wollongong and the Lower Hunter have been achieved, whilst further improvements are required for others.Environmental Economics and Policy,

On the fourth root prescription for dynamical staggered fermions

With the aim of resolving theoretical issues associated with the fourth root prescription for dynamical staggered fermions in Lattice QCD simulations, we consider the problem of finding a viable lattice Dirac operator D such that (det D_{staggered})^{1/4} = det D. Working in the flavour field representation we show that in the free field case there is a simple and natural candidate D satisfying this relation, and we show that it has acceptable locality behavior: exponentially local with localisation range vanishing ~ (a/m)^{1/2} for lattice spacing a -> 0. Prospects for the interacting case are also discussed, although we do not solve this case here.Comment: 29 pages, 2 figures; some revision and streamlining of the discussions; results unchanged; to appear in PR

Approximate Inference for Constructing Astronomical Catalogs from Images

We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.Comment: accepted to the Annals of Applied Statistic

Low‐temperature homoepitaxial growth on nonplanar Si substrates

The kinetics associated with the breakdown of epitaxy at low temperatures are studied for growth onto a number of Si surfaces, including (001), (117), (115), and (113). These surfaces are all initially generated at trench edges on a single patterned substrate. Growth on each of these surfaces at low temperatures is shown to result in a well‐defined crystalline‐to‐amorphous transition. The epitaxial thicknesses hepi have been measured over a range of substrate temperatures below 280 °C, and activation energies characteristic of this transition were determined. In general, the breakdown in epitaxy occurs such that hepi(001)≳hepi(117)≳hepi(115)≳hepi(113). Growth at slightly higher temperatures, Tsubstrate≳300 °C, shows a different microstructure than that at lower temperatures. Epitaxial growth continues for longer times on (113) facets, as compared with (001). These results are discussed in terms of a recently proposed model explaining the breakdown of epitaxy at lower temperatures and an epitaxial temperature for Si.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70710/2/JAPIAU-76-9-5185-1.pd

Effect of hydrogen on surface roughening during Si homoepitaxial growth

Hydrogen is shown to have a strong influence on the evolution of surface morphology during low temperature (310 °C) Si(100) homoepitaxy. Molecular beam epitaxy growth in the presence of deuterium shows a surface roughness within the epitaxial film that increases rapidly until the Si film exhibits a crystalline to amorphous transition. The rate at which the surface roughens depends critically on the partial pressure of deuterium. Although the kinetics of growth are sensitive to small pressures (4×10−8 Torr) of D, it appears that the breakdown of epitaxy does not result from a ‘‘critical’’ D concentration at the surface. This work suggests that the crystalline to amorphous transition, instead, results from increased roughening during epitaxy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71213/2/APPLAB-63-26-3571-1.pd