957 resultados para Dimension quantique


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A method for the explicit determination of the polar decomposition (and the related problem of finding tensor square roots) when the underlying vector space dimension n is arbitrary (but finite), is proposed. The method uses the spectral resolution, and avoids the determination of eigenvectors when the tensor is invertible. For any given dimension n, an appropriately constructed van der Monde matrix is shown to play a key role in the construction of each of the component matrices (and their inverses) in the polar decomposition.

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A scheme for denoting the absolute spatial orientation of molecules and molecular fragments is presented; this is based on three angular deviations - one for each spatial dimension - with respect to a reference orientation, which is itself defined with the help of certain features of the Cahn-Ingold-Prelog stereochemical notation. The new scheme helps in reconstructing the three-dimensional characteristics of molecules from purely verbal descriptors, and may thus find application in various information storage and retrieval processes (e.,-. encrypting holograms, etc.).

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Consider a sequence of closed, orientable surfaces of fixed genus g in a Riemannian manifold M with uniform upper bounds on the norm of mean curvature and area. We show that on passing to a subsequence, we can choose parametrisations of the surfaces by inclusion maps from a fixed surface of the same genus so that the distance functions corresponding to the pullback metrics converge to a pseudo-metric and the inclusion maps converge to a Lipschitz map. We show further that the limiting pseudo-metric has fractal dimension two. As a corollary, we obtain a purely geometric result. Namely, we show that bounds on the mean curvature, area and genus of a surface F subset of M, together with bounds on the geometry of M, give an upper bound on the diameter of F. Our proof is modelled on Gromov's compactness theorem for J-holomorphic curves.

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Near-wall structures in turbulent natural convection at Rayleigh numbers of $10^{10}$ to $10^{11}$ at A Schmidt number of 602 are visualized by a new method of driving the convection across a fine membrane using concentration differences of sodium chloride. The visualizations show the near-wall flow to consist of sheet plumes. A wide variety of large-scale flow cells, scaling with the cross-section dimension, are observed. Multiple large-scale flow cells are seen at aspect ratio (AR)= 0.65, while only a single circulation cell is detected at AR= 0.435. The cells (or the mean wind) are driven by plumes coming together to form columns of rising lighter fluid. The wind in turn aligns the sheet plumes along the direction of shear. the mean wind direction is seen to change with time. The near-wall dynamics show plumes initiated at points, which elongate to form sheets and then merge. Increase in rayleigh number results in a larger number of closely and regularly spaced plumes. The plume spacings show a common log–normal probability distribution function, independent of the rayleigh number and the aspect ratio. We propose that the near-wall structure is made of laminar natural-convection boundary layers, which become unstable to give rise to sheet plumes, and show that the predictions of a model constructed on this hypothesis match the experiments. Based on these findings, we conclude that in the presence of a mean wind, the local near-wall boundary layers associated with each sheet plume in high-rayleigh-number turbulent natural convection are likely to be laminar mixed convection type.

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It has been well recognized now that the blast furnace aerodynamics can be represented more accurately under the decreasing gas velocity condition. Therefore, gas-fines study has been carried out in a packed bed under the decreasing gas velocity condition. Gas and fines flow equations have been developed and solved, for two-dimensional case using finite volume method. To take into account the turbulence, k-e turbulent flow model has also been developed in two-dimension. The model's predictions have been validated against the published experimental data for the increasing gas velocity case, as no experimental data are available in open literature for the decreasing gas velocity. This study shows the difference in the results for increasing and decreasing gas velocity cases under various conditions which have been reported here. Implication of the results to the blast furnace condition has also been discussed.

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In this study, we investigated nonlinear measures of chaos of QT interval time series in 28 normal control subjects, 36 patients with panic disorder and 18 patients with major depression in supine and standing postures. We obtained the minimum embedding dimension (MED) and the largest Lyapunov exponent (LLE) of instantaneous heart rate (HR) and QT interval series. MED quantifies the system's complexity and LLE predictability. There was a significantly lower MED and a significantly increased LLE of QT interval time series in patients. Most importantly, nonlinear indices of QT/HR time series, MEDqthr (MED of QT/HR) and LLEqthr (LLE of QT/HR), were highly significantly different between controls and both patient groups in either posture. Results remained the same even after adjusting for age. The increased LLE of QT interval time, series in patients with anxiety and depression is in line with our previous findings of higher QTvi (QT variability index, a log ratio of QT variability corrected for mean QT squared divided by heart rate variability corrected for mean heart rate squared) in these patients, using linear techniques. Increased LLEqthr (LLE of QT/HR) may be a more sensitive tool to study cardiac repolarization and a valuable addition to the time domain measures such as QTvi. This is especially important in light of the finding that LLEqthr correlated poorly and nonsignificantly with QTvi. These findings suggest an increase in relative cardiac sympathetic activity and a decrease in certain aspects of cardiac vagal function in patients with anxiety as well as depression. The lack of correlation between QTvi and LLEqthr suggests that this nonlinear index is a valuable addition to the linear measures. These findings may also help to explain the higher incidence of cardiovascular mortality in patients with anxiety and depressive disorders. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

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An axis-parallel box in $b$-dimensional space is a Cartesian product $R_1 \times R_2 \times \cdots \times R_b$ where $R_i$ (for $1 \leq i \leq b$) is a closed interval of the form $[a_i, b_i]$ on the real line. For a graph $G$, its boxicity is the minimum dimension $b$, such that $G$ is representable as the intersection graph of (axis-parallel) boxes in $b$-dimensional space. The concept of boxicity finds application in various areas of research like ecology, operation research etc. Chandran, Francis and Sivadasan gave an $O(\Delta n^2 \ln^2 n)$ randomized algorithm to construct a box representation for any graph $G$ on $n$ vertices in $\lceil (\Delta + 2)\ln n \rceil$ dimensions, where $\Delta$ is the maximum degree of the graph. They also came up with a deterministic algorithm that runs in $O(n^4 \Delta )$ time. Here, we present an $O(n^2 \Delta^2 \ln n)$ deterministic algorithm that constructs the box representation for any graph in $\lceil (\Delta + 2)\ln n \rceil$ dimensions.

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Design and characterization of a new shape memory alloy wire based Poly Phase Motor has been reported in this paper. The motor can be used either in stepping mode or in servo mode of operation. Each phase of the motor consists of an SMA wire with a spring in series. The principle of operation of the poly phase motor is presented. The motor resembles a stepper motor in its functioning though the actuation principles are different and hence has been characterized similar to a stepper motor. The motor can be actuated in either direction with different phase sequencing methods, which are presented in this work. The motor is modelled and simulated and the results of simulations and experiments are presented. The experimental model of the motor is of dimension 150mm square, 20mm thick and uses SMA wire of 0·4mm diameter and 125mm of length in each phase.

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Recently, the demand of the steel having superior chemical and physical properties has increased for which the content of carbon must be in ultra low range. There are many processes which can produce low carbon steel such as Tank degasser and RH (Rheinstahl-Heraeus) processes. It has been claimed that using a new process, called REDA (Revolutionary Degassing Activator), one can achieve the carbon content below 10ppm in less time. REDA process in terms of installment cost is in between tank degasser and RH processes. As such, REDA process has not been studied thoroughly. Fluid flow phenomena affect the decarburization rate the most besides the chemical reaction rate. Therefore, momentum balance equations along with k-ε turbulent model have been solved for gas and liquid phases in two-dimension (2D) for REDA process. The fluid flow phenomena have been studied in details for this process by varying gas flow rate, depth of immersed snorkel in the steel, diameter of the snorkel and change in vacuum pressure. It is found that design of snorkel affects the mixing process of the bath significantly.

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We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d=2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article [ A. Patel and M. A. Rahaman Phys. Rev. A 82 032330 (2010)] provides an O(√NlnN) algorithm, which is not optimal. The scaling behavior can be improved to O(√NlnN) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi Phys. Rev. A 78 012310 (2008). We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.

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In this paper we are concerned with finding the maximum throughput that a mobile ad hoc network can support. Even when nodes are stationary, the problem of determining the capacity region has long been known to be NP-hard. Mobility introduces an additional dimension of complexity because nodes now also have to decide when they should initiate route discovery. Since route discovery involves communication and computation overhead, it should not be invoked very often. On the other hand, mobility implies that routes are bound to become stale resulting in sub-optimal performance if routes are not updated. We attempt to gain some understanding of these effects by considering a simple one-dimensional network model. The simplicity of our model allows us to use stochastic dynamic programming (SDP) to find the maximum possible network throughput with ideal routing and medium access control (MAC) scheduling. Using the optimal value as a benchmark, we also propose and evaluate the performance of a simple threshold-based heuristic. Unlike the optimal policy which requires considerable state information, the heuristic is very simple to implement and is not overly sensitive to the threshold value used. We find empirical conditions for our heuristic to be near-optimal as well as network scenarios when our simple heuristic does not perform very well. We provide extensive numerical and simulation results for different parameter settings of our model.

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A geometric and non parametric procedure for testing if two finite set of points are linearly separable is proposed. The Linear Separability Test is equivalent to a test that determines if a strictly positive point h > 0 exists in the range of a matrix A (related to the points in the two finite sets). The algorithm proposed in the paper iteratively checks if a strictly positive point exists in a subspace by projecting a strictly positive vector with equal co-ordinates (p), on the subspace. At the end of each iteration, the subspace is reduced to a lower dimensional subspace. The test is completed within r ≤ min(n, d + 1) steps, for both linearly separable and non separable problems (r is the rank of A, n is the number of points and d is the dimension of the space containing the points). The worst case time complexity of the algorithm is O(nr3) and space complexity of the algorithm is O(nd). A small review of some of the prominent algorithms and their time complexities is included. The worst case computational complexity of our algorithm is lower than the worst case computational complexity of Simplex, Perceptron, Support Vector Machine and Convex Hull Algorithms, if d