Browsing by Subject "Three dimensional (3D)"

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    Memory-efficient multilevel physical optics algorithm for fast computation of scattering from three-dimensional complex targets
    (IEEE, 2007) Manyas, Alp; Gürel, Levent
    Multilevel physical optics (MLPO) algorithm provides a speed-up for computing the physical-optics integral over complex bodies for a range of aspect angles and frequencies. On the other hand, when computation of the RCS pattern as a function of θ, φ, and frequency is desired, the O N3 memory complexity of the algorithm may prevent the solution of electrically large problems. In this paper, we propose an improved version of the MLPO algorithm, for which the memory complexity is reduced to O N2 log N . The algorithm is based on the aggregation of only some portion of the scattering patterns at each aggregation step. This way, memory growth in each step is prevented, and a significant amount of saving is achieved.
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    Simple test for hidden variables in spin-1 systems
    (2008) Klyachko, A. A.; Can, M. A.; Binicioǧlu, S.; Shumovsky, A. S.
    We resolve an old problem about the existence of hidden parameters in a three-dimensional quantum system by constructing an appropriate Bell's type inequality. This reveals the nonclassical nature of most spin-1 states. We shortly discuss some physical implications and an underlying cause of this nonclassical behavior, as well as a perspective of its experimental verification. © 2008 The American Physical Society.
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    Solution of large-scale scattering problems with the multilevel fast multipole algorithm parallelized on distributed-memory architectures
    (IEEE, 2007) Ergül, Özgür; Gürel, Levent
    We present the solution of large-scale scattering problems involving three-dimensional closed conducting objects with arbitrary shapes. With an efficient parallelization of the multilevel fast multipole algorithm on relatively inexpensive computational platforms using distributed-memory architectures, we perform the iterative solution of integral-equation formulations that are discretized with tens of millions of unknowns. In addition to canonical problems, we also present the solution of real-life problems involving complicated targets with large dimensions.