Nonextremality, chemical potential, and the infrared limit of large N thermal QCD

Nonextremal solution with warped resolved-deformed conifold background is important to study the infrared limit of large N thermal QCD. Earlier works in this direction have not taken into account all the backreactions on the geometry, namely from the branes, fluxes, and black-hole carefully. In the present work we make some progress in this direction by solving explicitly the supergravity equations of motions in the presence of the backreaction from the black hole. The backreactions from the branes and the fluxes on the other hand and to the order that we study, are comparatively suppressed. Our analysis reveal, among other things, how the resolution parameter would depend on the horizon radius and how the renormalization group flows of the coupling constants should be understood in these scenarios, including their effects on the background three-form fluxes. We also study the effect of switching on a chemical potential in the background and, in a particularly simplified scenario, compute the actual value of the chemical potential for our case.

Integrated parallelization of computations and visualization for large-scale applications

Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.

Large nonlinear refraction and two photon absorption in ferroelectric Bi2VO5.5 thin films

Ferroelectric c-oriented Bi2VO5.5 (BVO) thin films (thickness approximate to 300 nm) were fabricated by pulsed laser deposition on corning glass substrates. Nonlinear refractive index (n(2)) and two photon absorption coefficient (beta) were measured by Z-scan technique at 532 nm wavelength delivering pulses with 10 ns duration. Relatively large values of n(2) = 2.05 +/- 0.2 x 10(-10) cm(2)/W and beta = 9.36 +/- 0.3 cm/MW were obtained for BVO thin films. Origin of the large optical nonlinearities in BVO thin films was discussed based on bond-orbital theory of transition metal oxides. (c) 2012 Elsevier B.V. All rights reserved.

Models for the estimation of life of stator insulation in large rotating machines

Epoxy resin bonded mica splitting is the insulation of choice for machine stators. However, this system is seen to be relatively weak under time varying mechanical stress, in particular the vibration causing delamination of mica and deboning of mica from the resin matrix. The situation is accentuated under the combined action of electrical, thermal and mechanical stress. Physical and probabilistic models for failure of such systems have been proposed by one of the authors of this paper earlier. This paper presents a pragmatic accelerated failure data acquisition and analytical paradigm under multi factor coupled stress, Electrical, Thermal. The parameters of the phenomenological model so developed are estimated based on sound statistical treatment of failure data.

Analysis of large-amplitude stratospheric mountain wave event observed from the AIRS and MLS sounders over the western Himalayan region

Mountain waves in the stratosphere have been observed over elevated topographies using both nadir-looking and limb-viewing satellites. However, the characteristics of mountain waves generated over the Himalayan Mountain range and the adjacent Tibetan Plateau are relatively less explored. The present study reports on three-dimensional (3-D) properties of a mountain wave event that occurred over the western Himalayan region on 9 December 2008. Observations made by the Atmospheric Infrared Sounder on board the Aqua and Microwave Limb Sounder on board the Aura satellites are used to delineate the wave properties. The observed wave properties such as horizontal (lambda(x), lambda(y)) and vertical (lambda(z)) wavelengths are 276 km (zonal), 289 km (meridional), and 25 km, respectively. A good agreement is found between the observed and modeled/analyzed vertical wavelength for a stationary gravity wave determined using the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds. The analysis of both the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis and MERRA winds shows that the waves are primarily forced by strong flow across the topography. Using the 3-D properties of waves and the corrected temperature amplitudes, we estimated wave momentum fluxes of the order of similar to 0.05 Pa, which is in agreement with large-amplitude mountain wave events reported elsewhere. In this regard, the present study is considered to be very much informative to the gravity wave drag schemes employed in current general circulation models for this region.

EXIT Chart Based Design of Irregular LDPC Codes for Large-MIMO Systems

In this letter, we characterize the extrinsic information transfer (EXIT) behavior of a factor graph based message passing algorithm for detection in large multiple-input multiple-output (MIMO) systems with tens to hundreds of antennas. The EXIT curves of a joint detection-decoding receiver are obtained for low density parity check (LDPC) codes of given degree distributions. From the obtained EXIT curves, an optimization of the LDPC code degree profiles is carried out to design irregular LDPC codes matched to the large-MIMO channel and joint message passing receiver. With low complexity joint detection-decoding, these codes are shown to perform better than off-the-shelf irregular codes in the literature by about 1 to 1.5 dB at a coded BER of 10(-5) in 16 x 16, 64 x 64 and 256 x 256 MIMO systems.

Multiuser detection in large-dimension multicode MIMO-CDMA systems with higher-order modulation

In this paper, we are interested in high spectral efficiency multicode CDMA systems with large number of users employing single/multiple transmit antennas and higher-order modulation. In particular, we consider a local neighborhood search based multiuser detection algorithm which offers very good performance and complexity, suited for systems with large number of users employing M-QAM/M-PSK. We apply the algorithm on the chip matched filter output vector. We demonstrate near-single user (SU) performance of the algorithm in CDMA systems with large number of users using 4-QAM/16-QAM/64-QAM/8-PSK on AWGN, frequency-flat, and frequency-selective fading channels. We further show that the algorithm performs very well in multicode multiple-input multiple-output (MIMO) CDMA systems as well, outperforming other linear detectors and interference cancelers reported in the literature for such systems. The per-symbol complexity of the search algorithm is O(K2n2tn2cM), K: number of users, nt: number of transmit antennas at each user, nc: number of spreading codes multiplexed on each transmit antenna, M: modulation alphabet size, making the algorithm attractive for multiuser detection in large-dimension multicode MIMO-CDMA systems with M-QAM.

Near-optimal large-MIMO detection using randomized MCMC and randomized search algorithms

Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

A hybrid RTS-BP algorithm for improved detection of large-MIMO M-QAM signals

Low-complexity near-optimal detection of large-MIMO signals has attracted recent research. Recently, we proposed a local neighborhood search algorithm, namely reactive tabu search (RTS) algorithm, as well as a factor-graph based belief propagation (BP) algorithm for low-complexity large-MIMO detection. The motivation for the present work arises from the following two observations on the above two algorithms: i) Although RTS achieved close to optimal performance for 4-QAM in large dimensions, significant performance improvement was still possible for higher-order QAM (e.g., 16-, 64-QAM). ii) BP also achieved near-optimal performance for large dimensions, but only for {±1} alphabet. In this paper, we improve the large-MIMO detection performance of higher-order QAM signals by using a hybrid algorithm that employs RTS and BP. In particular, motivated by the observation that when a detection error occurs at the RTS output, the least significant bits (LSB) of the symbols are mostly in error, we propose to first reconstruct and cancel the interference due to bits other than LSBs at the RTS output and feed the interference cancelled received signal to the BP algorithm to improve the reliability of the LSBs. The output of the BP is then fed back to RTS for the next iteration. Simulation results show that the proposed algorithm performs better than the RTS algorithm, and semi-definite relaxation (SDR) and Gaussian tree approximation (GTA) algorithms.

Parabolized stability equation models for predicting large-scale mixing noise of turbulent round jets

Parabolized stability equation (PSE) models are being deve loped to predict the evolu-tion of low-frequency, large-scale wavepacket structures and their radiated sound in high-speed turbulent round jets. Linear PSE wavepacket models were previously shown to be in reasonably good agreement with the amplitude envelope and phase measured using a microphone array placed just outside the jet shear layer. 1,2 Here we show they also in very good agreement with hot-wire measurements at the jet center line in the potential core,for a different set of experiments. 3 When used as a model source for acoustic analogy, the predicted far field noise radiation is in reasonably good agreement with microphone measurements for aft angles where contributions from large -scale structures dominate the acoustic field. Nonlinear PSE is then employed in order to determine the relative impor-tance of the mode interactions on the wavepackets. A series of nonlinear computations with randomized initial conditions are use in order to obtain bounds for the evolution of the modes in the natural turbulent jet flow. It was found that n onlinearity has a very limited impact on the evolution of the wavepackets for St≥0. 3. Finally, the nonlinear mechanism for the generation of a low-frequency mode as the difference-frequency mode 4,5 of two forced frequencies is investigated in the scope of the high Reynolds number jets considered in this paper.

Yielding and large deviations in micellar gels: a model

We present a simple model that can be used to account for the rheological behaviour observed in recent experiments on micellar gels. The model combines attachment detachment kinetics with stretching due to shear, and shows well-defined jammed and flowing states. The large-deviation function (LDF) for the coarse-grained velocity becomes increasingly non-quadratic as the applied force F is increased, in a range near the yield threshold. The power fluctuations are found to obey a steady-state fluctuation relation (FR) at small F. However, the FR is violated when F is near the transition from the flowing to the jammed state although the LDF still exists; the antisymmetric part of the LDF is found to be nonlinear in its argument. Our approach suggests that large fluctuations and motion in a direction opposite to an imposed force are likely to occur in a wider class of systems near yielding.

Accelerating Reduction for Enabling Fast Multiplication over Large Binary Fields

In this paper we present a hardware-software hybrid technique for modular multiplication over large binary fields. The technique involves application of Karatsuba-Ofman algorithm for polynomial multiplication and a novel technique for reduction. The proposed reduction technique is based on the popular repeated multiplication technique and Barrett reduction. We propose a new design of a parallel polynomial multiplier that serves as a hardware accelerator for large field multiplications. We show that the proposed reduction technique, accelerated using the modified polynomial multiplier, achieves significantly higher performance compared to a purely software technique and other hybrid techniques. We also show that the hybrid accelerated approach to modular field multiplication is significantly faster than the Montgomery algorithm based integrated multiplication approach.

Fine scale characterization of surface/subsurface and nanosized debris particles on worn Cu-10 % Pb nanocomposites

The identification of the damage mechanisms involved in the wear process demands the finer scale characterization of the surface, as well as the subsurface region of the wear scar region, and to this end, this article discusses the results obtained with Cu-10 wt% Pb-based metallic nanocomposites using a host of characterization techniques, including transmission electron microscopy and ion milling microscopy. Apart from finer scale characterization to understand deformation and cracking during the wear process, X-ray photoelectron spectroscopy analysis of wear debris confirms the occurrence of oxidation of Pb phase to Pb3O4. In order to understand the role of oxides on friction and wear, sliding wear tests in argon were also carried out and such tests did not result in the formation of any tribo-oxides, as confirmed using electron probe microanalysis. Conclusively, oxidative wear is attributed as the dominant wear mechanism in ambient conditions for Cu-10 wt% Pb composite.

Effect of crystallite size and clustering in influencing the stability of phases of a very large tetragonality ferroelectric system 0.6BiFeO(3)-0.4PbTiO(3)

The role of crystallite size and clustering in influencing the stability of the structures of a large tetragonality ferroelectric system 0.6BiFeO(3)-0.4PbTiO(3) was investigated. The system exhibits cubic phase for a crystallite size similar to 25 nm, three times larger than the critical size reported for one of its end member PbTiO3. With increased degree of clustering for the same average crystallite size, partial stabilization of the ferroelectric tetragonal phase takes place. The results suggest that clustering helps in reducing the depolarization energy without the need for increasing the crystallite size of free particles.

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.