35 resultados para Distances stellaires


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This work considers the problem of fitting data on a Lie group by a coset of a compact subgroup. This problem can be seen as an extension of the problem of fitting affine subspaces in n to data which can be solved using principal component analysis. We show how the fitting problem can be reduced for biinvariant distances to a generalized mean calculation on an homogeneous space. For biinvariant Riemannian distances we provide an algorithm based on the Karcher mean gradient algorithm. We illustrate our approach by some examples on SO(n). © 2010 Springer -Verlag Berlin Heidelberg.

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We report room temperature operation of telecom wavelength single-photon detectors for high bit rate quantum key distribution (QKD). Room temperature operation is achieved using InGaAs avalanche photodiodes integrated with electronics based on the self-differencing technique that increases avalanche discrimination sensitivity. Despite using room temperature detectors, we demonstrate QKD with record secure bit rates over a range of fiber lengths (e.g., 1.26 Mbit/s over 50 km). Furthermore, our results indicate that operating the detectors at room temperature increases the secure bit rate for short distances. © 2014 AIP Publishing LLC.

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We demonstrate quantum key distribution (QKD) with bidirectional 10 Gb/s classical data channels in a single fiber using dense wavelength division multiplexing. Record secure key rates of 2.38 Mbps and fiber distances up to 70km are achieved. Data channels are simultaneously monitored for error-free operation. The robustness of QKD is further demonstrated with a secure key rate of 445 kbps over 25km, obtained in the presence of data lasers launching conventional 0 dBm power. We discuss the fundamental limit for the QKD performance in the multiplexing environment. © 2014 AIP Publishing LLC.

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Surprisingly expensive to compute wall distances are still used in a range of key turbulence and peripheral physics models. Potentially economical, accuracy improving differential equation based distance algorithms are considered. These involve elliptic Poisson and hyperbolic natured Eikonal equation approaches. Numerical issues relating to non-orthogonal curvilinear grid solution of the latter are addressed. Eikonal extension to a Hamilton-Jacobi (HJ) equation is discussed. Use of this extension to improve turbulence model accuracy and, along with the Eikonal, enhance Detached Eddy Simulation (DES) techniques is considered. Application of the distance approaches is studied for various geometries. These include a plane channel flow with a wire at the centre, a wing-flap system, a jet with co-flow and a supersonic double-delta configuration. Although less accurate than the Eikonal, Poisson method based flow solutions are extremely close to those using a search procedure. For a moving grid case the Poisson method is found especially efficient. Results show the Eikonal equation can be solved on highly stretched, non-orthogonal, curvilinear grids. A key accuracy aspect is that metrics must be upwinded in the propagating front direction. The HJ equation is found to have qualitative turbulence model improving properties. © 2003 by P. G. Tucker.

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THERE ARE MANY different kinds of robots: factory automation systems that weld and assemble car engines; machines that place chocolates into boxes; medical devices that support surgeons in operations requiring high-precision manipulation; cars that drive automatically over long distances; vehicles for planetary exploration; mechanisms for powerline or oil platform inspection; toys and educational toolkits for schools and universities; service robots that deliver meals, clean floors, or mow lawns; and "companion robots" that are real partners for humans and share our daily lives. In a sense, all these robots are inspired by biological systems; it's just a matter of degree. A driverless vehicle imitates animals moving autonomously in the world.© 2012 ACM.