Nonquasi-static charge model for common double-gate MOSFETs adapted to gate oxide thickness asymmetry

With the unique quasi-linear relationship between the surface potentials along the channel, recently we have proposed a quasi-static terminal charge model for common double-gate MOSFETs, which might have asymmetric gate oxide thickness. In this brief, we extend this concept to develop the nonquasi-static (NQS) charge model for the same by solving the governing continuity equations. The proposed NQS model shows good agreement against TCAD simulations and appears to be useful for efficient circuit simulation.

Black hole formation at the correspondence point

We study the process of bound state formation in a D-brane collision. We consider two mechanisms for bound state formation. The first, operative at weak coupling in the worldvolume gauge theory, is pair creation of W-bosons. The second, operative at strong coupling, corresponds to formation of a large black hole in the dual supergravity. These two processes agree qualitatively at intermediate coupling, in accord with the correspondence principle of Horowitz and Polchinski. We show that the size of the bound state and time scale for formation of a bound state agree at the correspondence point. The time scale involves matching a parametric resonance in the gauge theory to a quasinormal mode in supergravity.

Transverse single spin asymmetry in e plus p(up arrow) -> e plus J/psi plus X and transverse momentum dependent evolution of the Sivers function

We extend our analysis of transverse single spin asymmetry in electroproduction of J/psi to include the effect of the scale evolution of the transverse momentum dependent (TMD) parton distribution functions and gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS, and eRHIC energies using the color evaporation model of charmonium production, using an analytically obtained approximate solution of TMD evolution equations discussed in the literature. We find that there is a reduction in the asymmetry compared with our predictions for the earlier case considered by us, wherein the Q(2) dependence came only from DGLAP evolution of the unpolarized gluon densities and a different parametrization of the TMD Sivers function was used.

Black hole formation in fuzzy sphere collapse

We study the collapse of a fuzzy sphere, that is a spherical membrane built out of D0-branes, in the Banks-Fischler-Shenker-Susskind model. At weak coupling, as the sphere shrinks, open strings are produced. If the initial radius is large then open string production is not important and the sphere behaves classically. At intermediate initial radius the backreaction from open string production is important but the fuzzy sphere retains its identity. At small initial radius the sphere collapses to form a black hole. The crossover between the later two regimes is smooth and occurs at the correspondence point of Horowitz and Polchinski.

Plasmons in spatially separated rolled-up electron-hole double-layer systems

Using the two-component random phase approximation, we report the collective mode spectrum of a quasi-one-dimensional spatially separated electron-hole double-layer system characterized by rolled-up type-II band aligned quantum wells. We find two intra-subband collective excitations, which can be classified into optic and acoustic plasmon branches, and several inter-subband plasmon modes. At the long wavelength limit and up to a given wave vector, our model predicts and admits an undamped acoustic branch, which always lies in the gap between the intra-subband electron and hole continua, and an undamped optic branch residing within the gap between the inter-subband electron and hole continua, for all values of the electron-hole charge separations. This theoretical investigation suggests that the low-energy and Landau-undamped plasmon modes might exist based on quasi-one-dimensional, two-component spatially separated electron-hole plasmas, and their possibility could be experimentally examined. (C) 2013 AIP Publishing LLC.

Radiatively inefficient accretion flow simulations with cooling: implications for black hole transients

We study the effects of optically thin radiative cooling on the structure of radiatively inefficient accretion flows (RIAFs). The flow structure is geometrically thick, and independent of the gas density and cooling, if the cooling time is longer than the viscous time-scale (i.e. t(cool) greater than or similar to t(visc)). For higher densities, the gas can cool before it can accrete and forms the standard geometrically thin, optically thick Shakura-Sunyaev disc. For usual cooling processes (such as bremsstrahlung), we expect an inner hot flow and an outer thin disc. For a short cooling time the accretion flow separates into two phases: a radiatively inefficient hot coronal phase and a cold thin disc. We argue that there is an upper limit on the density of the hot corona corresponding to a critical value of t(cool)/t(ff)( similar to 10-100), the ratio of the cooling time and the free-fall time. Based on our simulations, we have developed a model for transients observed in black hole X-ray binaries (XRBs). An XRB in a quiescent hot RIAF state can transition to a cold blackbody-dominated state because of an increase in the mass accretion rate. The transition from a thin disc to a RIAF happens because of mass exhaustion due to accretion; the transition happens when the cooling time becomes longer than the viscous time at inner radii. Since the viscous time-scale for a geometrically thin disc is quite long, the high-soft state is expected to be long-lived. The different time-scales in black hole transients correspond to different physical processes such as viscous evolution, cooling and free fall. Our model captures the overall features of observed state transitions in XRBs.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Simultaneous feature selection and clustering using particle swarm optimization

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem.

Cooperative Particle Swarm Optimization Based Receiver for Large-Dimension MIMO-ZPSC Systems

In this paper, we propose a cooperative particle swarm optimization (CPSO) based channel estimation/equalization scheme for multiple-input multiple-output zero-padded single-carrier (MIMO-ZPSC) systems with large dimensions in frequency selective channels. We estimate the channel state information at the receiver in time domain using a PSO based algorithm during training phase. Using the estimated channel, we perform information symbol detection in the frequency domain using FFT based processing. For this detection, we use a low complexity OLA (OverLap Add) likelihood ascent search equalizer which uses minimum mean square (MMSE) equalizer solution as the initial solution. Multiple iterations between channel estimation and data detection are carried out which significantly improves the mean square error and bit error rate performance of the receiver.

Group testing based spectrum hole search using a simple sub-nyquist sampling scheme

In this paper, we consider the problem of finding a spectrum hole of a specified bandwidth in a given wide band of interest. We propose a new, simple and easily implementable sub-Nyquist sampling scheme for signal acquisition and a spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy in the frequency domain by testing a group of adjacent subbands in a single test. The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent sub-bands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes. We extend this framework to a multi-stage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including non-contiguous spectrum hole search. Further, we provide the analytical means to optimize the hypothesis tests with respect to the detection thresholds, number of samples and group size to minimize the detection delay under a given error rate constraint. Depending on the sparsity and SNR, the proposed algorithms can lead to significantly lower detection delays compared to a conventional bin-by-bin energy detection scheme; the latter is in fact a special case of the group test when the group size is set to 1. We validate our analytical results via Monte Carlo simulations.

Particle size, morphology and color tunable ZnO:Eu3+ nanophosphors via plant latex mediated green combustion synthesis

Efficient ZnO:Eu3+ (1-11 mol%) nanophosphors were prepared for the first time by green synthesis route using Euphorbia tirucalli plant latex. The final products were well characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), etc. The average particle size of ZnO:Eu3+ (7 mol%) was found to be in the range 27-47 nm. With increase of plant latex, the particle size was reduced and porous structure was converted to spherical shaped particles. Photoluminescence (PL) spectra indicated that the peaks situated at similar to 590, 615, 648 and 702 nm were attributed to the D-5(0) -> F-7(j(j=1,2,3,4)) transitions of Eu3+ ions. The highest PL intensity was recorded for 7 mol% with Eu3+ ions and 26 ml plant latex concentration. The PL intensity increases with increase of plant latex concentration up to 30 ml and there after it decreases. The phosphor prepared by this method show spherical shaped particles, excellent chromaticity co-ordinates in the white light region which was highly useful for WLED's. Further, present method was reliable, environmentally friendly and alternative to economical routes. (c) 2013 Elsevier B.V. All rights reserved.

Recrystallization and Ag3Sn Particle Redistribution During Thermomechanical Treatment of Bulk Sn-Ag-Cu Solder Alloys

Sn-Ag-Cu (SAC) solders are susceptible to appreciable microstructural coarsening during storage or service. This results in evolution of joint properties over time and thereby influences the long-term reliability of microelectronic packages. Accurate reliability prediction of SAC solders requires prediction of microstructural evolution during service. Microstructure evolution in two SAC solder alloys, such as, Sn-3.0Ag-0.5Cu (SAC 305) and Sn-1.0Ag-0.5 Cu (SAC 105), under different thermomechanical excursions, including isothermal aging at 150 degrees C and thermomechanical cycling (TMC) was studied. In general, between 200 and 600 cycles during TMC, recrystallization of the Sn matrix was observed, along with redistribution of Ag3Sn particles because of dissolution and reprecipitation. These latter effects have not been reported before. It was also observed that the Sn grains recrystallized near precipitate clusters in eutectic channels during extended isothermal aging. The relative orientation of Sn grains in proeutectic colonies did not change during isothermal aging.

Transverse single spin asymmetry in e+p↑→e+J/ψ+X and transverse momentum dependent evolution of the Sivers function

We extend our analysis of transverse single spin asymmetry in electroproduction of J/ψ to include the effect of the scale evolution of the transverse momentum dependent (TMD) parton distribution functions and gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS, and eRHIC energies using the color evaporation model of charmonium production, using an analytically obtained approximate solution of TMD evolution equations discussed in the literature. We find that there is a reduction in the asymmetry compared with our predictions for the earlier case considered by us, wherein the Q2 dependence came only from DGLAP evolution of the unpolarized gluon densities and a different parametrization of the TMD Sivers function was used.

Large deviation function and fluctuation theorem for classical particle transport

We analytically evaluate the large deviation function in a simple model of classical particle transfer between two reservoirs. We illustrate how the asymptotic long-time regime is reached starting from a special propagating initial condition. We show that the steady-state fluctuation theorem holds provided that the distribution of the particle number decays faster than an exponential, implying analyticity of the generating function and a discrete spectrum for its evolution operator.