114,714 research outputs found

    The Orbifold-String Theories of Permutation-Type: I. One Twisted BRST per Cycle per Sector

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    We resume our discussion of the new orbifold-string theories of permutation-type, focusing in the present series on the algebraic formulation of the general bosonic prototype and especially the target space-times of the theories. In this first paper of the series, we construct one twisted BRST system for each cycle jj in each twisted sector σ\sigma of the general case, verifying in particular the previously-conjectured algebra [Qi(σ),Qj(σ)]+=0[Q_{i}(\sigma),Q_{j}(\sigma)]_{+} =0 of the BRST charges. The BRST systems then imply a set of extended physical-state conditions for the matter of each cycle at cycle central charge c^j(σ)=26fj(σ)\hat{c}_{j}(\sigma)=26f_{j}(\sigma) where fj(σ)f_{j}(\sigma) is the length of cycle jj.Comment: 31 page

    A novel frequency-domain implementation of Tomlinson-Harashima precoding for SC-FDMA

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    Joint Tomlinson-Harashima precoding and optimum transmit power allocation for SC-FDMA

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    Frequency-domain precoding for single carrier frequency-division multiple access

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    Frequency-domain transmit processing for MIMO SC-FDMA in wideband propagation channels

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    Resource contrast in patterned peatlands increases along a climatic gradient

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    Copyright by the Ecological Society of America 2010, for personal or educational use only. Article is available at <http://dx.doi.org/10.1890/09-1313.1

    A Note on the Importance of Weak Convergence Rates for SPDE Approximations in Multilevel Monte Carlo Schemes

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    It is a well-known rule of thumb that approximations of stochastic partial differential equations have essentially twice the order of weak convergence compared to the corresponding order of strong convergence. This is already known for many approximations of stochastic (ordinary) differential equations while it is recent research for stochastic partial differential equations. In this note it is shown how the availability of weak convergence results influences the number of samples in multilevel Monte Carlo schemes and therefore reduces the computational complexity of these schemes for a given accuracy of the approximations.Comment: 16 pages, 3 figures, updated to version published in the Proceedings of MCQMC1
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