Many body effects and internal transitions of confined excitons in GaAs and CdTe quantum wells

Many body effects contribute significantly to the energy states of electron-hole pairs confined in quantum wells in the presence of excess electrons. We present results of optically detected resonance spectroscopy of the internal transitions of photo-excited electron-hole pairs in the presence of excess electrons for GaAs QWs and CdTe QWs. Compared to the case of isolated negatively charged excitons, excess electrons produce a large blue shift of the internal transitions in modulation-doped GaAs quantum wells (QWs) for filling factor <2, and similar effects are found in CdTe QWs. For filling factor >2 no internal transitions are observed. These measurements demonstrate the strong effects of electron-electron correlations on the internal transitions of charged excitons in these quasi-2D systems and the importance of magnetic translation invariance. In the presence of excess electrons, the observed internal transitions are those of a magnetoplasmon bound to a mobile valence band hole.     

Computing Aviation Sparing Policies: Solving a Large Nonlinear Integer Program

Deployed US Navy aircraft carriers must stock a large number of spare parts to support the various types of aircraft embarked on the ship. The sparing policy determines the spares that will be stocked on the ship to keep the embarked aircraft ready to fly. Given a fleet of ten or more aircraft carriers and a cost of approximately 50 million dollars per carrier plus the cost of spares maintained in warehouses in the United States, the sparing problem constitutes a significant portion of the Navy’s resources. The objective of this work is to find a minimum-cost sparing policy that meets the readiness requirements of the embarked aircraft. This is a very large, nonlinear, integer optimization problem. The cost function is piecewise linear and convex while the constraint mapping is highly nonlinear. The distinguishing characteristics of this problem from an optimization viewpoint are that a large number of decision variables are required to be integer and that the nonlinear constraint functions are essentially “black box” functions; that is, they are very difficult (and expensive) to evaluate and their derivatives are not available. Moreover, they are not convex. Integer programming problems with a large number of variables are difficult to solve in general and most successful approaches to solving nonlinear integer problems have involved linear approximation and relaxation techniques that, because of the complexity of the constraint functions, are inappropriate for attacking this problem. We instead employ a pattern search method to each iteration of an interior point-type algorithm to solve the relaxed version of the problem. From the solution found by the pattern search on each interior point iteration, we begin another pattern search on the integer lattice to find a good integer solution. The best integer solution found across all interations is returned as the optimal solution. The pattern searches are distributed across a local area network of non-dedicated, heterogeneous computers in an office environment, thus, drastically reducing the time required to find the solution.     

Multicriteria Semi-Obnoxious Network Location Problems (MSNLP) with Sum and Center Objectives

Locating a facility is often modeled as either the maxisum or the minisum problem, reflecting whether the facility is undesirable (obnoxious) or desirable. But many facilities are both desirable and undesirable at the same time, e.g., an airport. This can be modeled as a multicriteria network location problem, where some of the sum-objectives are maximized (push effect) and some of the sum-objectives are minimized (pull effect).We present a polynomial time algorithm for this model along with some basic theoretical results, and generalize the results also to incorporate maximin and minimax objectives. In fact, the method works for any piecewise linear objective functions. Finally, we present some computational results.     

Effects of a controlled N2 and O2 addition to Ar on the analytical parameters of the GD-OES

The influence of the controlled addition of N₂ and of O₂ to Ar on the analytical parameters of a dc glow discharge has been investigated for bulk samples of the pure metals Al, Ti, Fe, Ni, Cu, and Ag. The constant voltage discharge mode at 1000 V was applied with a mean power of about 1 W/mm². The N₂ and O₂ concentrations in the discharge gas Ar were varied in the range 0–3 mass-%, corresponding to a partial pressure of about 4 · 10^?3 hPa. The general effect of the gaseous addition is the decrease of the sputtering rate with an increasing concentration of N₂ or O₂. Atomic processes, which might be responsible for the observed effects, are discussed.