Generalized reduction formula for Discrete Wigner functions of multiqubit systems

Density matrices and Discrete Wigner Functions are equally valid representations of multiqubit quantum states. For density matrices, the partial trace operation is used to obtain the quantum state of subsystems, but an analogous prescription is not available for discrete Wigner Functions. Further, the discrete Wigner function corresponding to a density matrix is not unique but depends on the choice of the quantum net used for its reconstruction. In the present work, we derive a reduction formula for discrete Wigner functions of a general multiqubit state which works for arbitrary quantum nets. These results would be useful for the analysis and classification of entangled states and the study of decoherence purely in a discrete phase space setting and also in applications to quantum computingComment: 7 Pages and zero figure

Spin flip of multiqubit states in discrete phase space

Time reversal and spin flip are discrete symmetry operations of substantial import to quantum information and quantum computation. Spin flip arises in the context of separability, quantification of entanglement and the construction of Universal NOT gates. The present work investigates the relationship between the quantum state of a multiqubit system represented by the Discrete Wigner Function (DWFs) and its spin-flipped counterpart. The two are shown to be related through a Hadamard matrix that is independent of the choice of the quantum net used for the tomographic reconstruction of the DWF. These results would be of interest to cases involving the direct tomographic reconstruction of the DWF from experimental data and in the analysis of entanglement related properties purely in terms of the Discrete Wigner function

Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (JuneSeptember) as compared to the dry season (NovemberJanuary). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA

Estimation of background carrier concentration in fully depleted GaN films

Buffer leakage is an important parasitic loss mechanism in AlGaN/GaN HEMTs and hence various methods are employed to grow semi-insulating buffer layers. Quantification of carrier concentration in such buffers using conventional capacitance based profiling techniques is challenging due to their fully depleted nature even at zero bias voltages. We provide a simple and effective model to extract carrier concentrations in fully depleted GaN films using capacitance-voltage (C-V) measurements. Extensive mercury probe C-V profiling has been performed on GaN films of differing thicknesses and doping levels in order to validate this model. Carrier concentrations as extracted from both the conventional C-V technique for partially depleted films having the same doping concentration, and Hall measurements show excellent agreement with those predicted by the proposed model thus establishing the utility of this technique. This model can be readily extended to estimate background carrier concentrations from the depletion region capacitances of HEMT structures and fully depleted films of any class of semiconductor materials.Comment: 16 pages, 6 figure

Growth Stress Induced Tunability of Dielectric Constant in Thin Films

It is demonstrated here that growth stress has a substantial effect on the dielectric constant of zirconia thin films. The correct combination of parameters - phase, texture and stress - is shown to yield films with high dielectric constant and best reported equivalent oxide thickness of 0.8 nm. The stress effect on dielectric constant is twofold, firstly, by the effect on phase transitions and secondly by the effect on interatomic distances. We discuss and explain the physical mechanisms involved in the interplay between the stress, phase changes and the dielectric constant in detail.Comment: 11 pages, 5 figure

High contrast imaging and thickness determination of graphene with in-column secondary electron microscopy

We report a new method for quantitative estimation of graphene layer thicknesses using high contrast imaging of graphene films on insulating substrates with a scanning electron microscope. By detecting the attenuation of secondary electrons emitted from the substrate with an in-column low-energy electron detector, we have achieved very high thickness-dependent contrast that allows quantitative estimation of thickness up to several graphene layers. The nanometer scale spatial resolution of the electron micrographs also allows a simple structural characterization scheme for graphene, which has been applied to identify faults, wrinkles, voids, and patches of multilayer growth in large-area chemical vapor deposited graphene. We have discussed the factors, such as differential surface charging and electron beam induced current, that affect the contrast of graphene images in detail.Comment: 5 pages, 4 figure

Optimal Resource Allocation to Minimize Last Mile Delivery Costs

This study focusses on a decision-making tool to assist an organization in planning for capacity needed for the Last Mile Delivery (LMD) services which is the most expensive part of the entire supply chain. Considering the use of Crowdsourcing for Logistics (CSL), the decision-making tool?s objective is to provide an optimal combination of fulltime, seasonal and CSL resources that lead to minimum operational LMD costs and meet the variable demand. To achieve this, a three phased approach is used, where in the first analytical phase an expected cost model is numerically validated. In the second stochastic program phase, the capacity and cost of the CSL resources are varied. Finally, in the third simulation phase, the approach is further extended to consider the daily employee attrition rate and unsatisfied demand being carried over to the next day. Lastly, the use of automation or newer technologies, such as robots, for LMD services is introduced in this simulation phase to show the benefits in terms of the operations costs. The results from the analytical model described the optimal values of fulltime and seasonal considering the utilization of CSL and experienced some penalty costs. In this case, the parameters being fixed, does not capture the differences due to the variability of CSL availability or costs, which is addressed in the stochastic program phase. Though the output from the stochastic model is higher, it does consider the variability in the CSL capacity and cost, which is practically observed. The simulation section gives a further refined optimal combination of fulltime, seasonal and CSL that meets the demand considering the attrition rate of fulltime and seasonal, and rollover the units by one day. Within this simulation, the consideration of automated delivery systems like using a robot for LMD services leads to further cost savings opportunity. Here, the fulltime delivery cost is benefited, with low utilization of seasonal and CSL limited for optimizing delivery strategy. In conclusion a tool is provided for aggregate delivery capacity planning that would consider an optimal combination of fulltime, seasonal and CSL resources lowering the LMD costs and meeting the variable demand