Distributed processing of a fractal array beamformer

Fractals have been proven as potential candidates for satellite flying formations, where its different elements represent a thinned array. The distributed and low power nature of the nodes in this network motivates distributed processing when using such an array as a beamformer. This paper proposes such initial idea, and demonstrates that benefits such as strictly limited local processing capability independent of the array’s dimension and local calibration can be bought at the expense of a slightly increased overall cost

Automation of NLO QCD and EW corrections with Sherpa and Recola

This publication presents the combination of the one-loop matrix-element generator Recola with the multipurpose Monte Carlo program Sherpa. Since both programs are highly automated, the resulting Sherpa+Recola framework allows for the computation of -in principle- any Standard Model process at both NLO QCD and EW accuracy. To illustrate this, three representative LHC processes have been computed at NLO QCD and EW: vector-boson production in association with jets, off-shell Z-boson pair production, and the production of a top-quark pair in association with a Higgs boson. In addition to fixed-order computations, when considering QCD corrections, all functionalities of Sherpa, i.e. particle decays, QCD parton showers, hadronisation, underlying events, etc. can be used in combination with Recola. This is demonstrated by the merging and matching of one-loop QCD matrix elements for Drell-Yan production in association with jets to the parton shower. The implementation is fully automatised, thus making it a perfect tool for both experimentalists and theorists who want to use state-of-the-art predictions at NLO accuracy.Comment: 38 pages, 29 figures. Matches the published version (few typos corrected

Amenities, local conditions and fiscal determinants of factor growth in rural America

This paper examines how amenities, asset indicators, and fiscal factors influence the growth in factors of production from 1972 to 1999 in the 466 non-metropolitan labor market areas in the continental United States. In developing our model of non-metropolitan factor markets, we combine the emphasis of Brown et al. (2003) on the affect of taxes and public expenditure policy on labor and capital formation with the emphasis of Beeson et al. (2001) on the importance of climate and natural features on localized population growth. We develop our own measure of capital stock in non-metropolitan areas using data from the Census of Manufacturing for 1967, 1972, 1977, 1982, 1987, and 1992. Results indicate that local taxes discourage both employment growth and manufacturing capital formation, but that local public infrastructure investment and the level of local entrepreneurship encourages employment growth. Amenities such as a favorable climate and the presence of surface water encourage the growth of employment, and greater local wealth, as measured by dividend, interest, and rent income, encourages the formation of manufacturing capital stock. Results fail to support an “export base” approach for rural economies where greater manufacturing capital stock encourages greater employment in a region.Rural areas ; Rural development

Anderson transition and thermal effects on electron states in amorphous silicon

I discuss the properties of electron states in amorphous Si based on large scale calculations with realistic several thousand atom models. A relatively simple model for the localized to extended (Anderson) transition is reviewed. Then, the effect of thermal disorder on localized electron states is considered. It is found that under readily accessible conditions, localized (midgap or band tail) states and their conjugate energies may fluctuate dramatically. The possible importance of non-adiabatic atomic dynamics to doped or photo-excited systems is briefly discussed.Comment: Was presented at ICAMS18, Snowbird UT, August 1999. Submitted to J. of Non-Cryst. Solid

Cyclic-by-row approximation of iterative polynomial EVD algorithms

A recent class of sequential matrix diagonalisation (SMD) algorithms have been demonstrated to provide a fast converging solution to iteratively approximating the polynomial eigenvalue decomposition of a parahermitian matrix. However, the calculation of an EVD, and the application of a full unitary matrix to every time lag of the parahermitian matrix in the SMD algorithm results in a high numerical cost. In this paper, we replace the EVD with a limited number of Givens rotations forming a cyclic-by-row Jacobi sweep. Simulations indicate that a considerable reduction in computational complexity compared to SMD can be achieved with a negligible sacrifice in diagonalisation performance, such that the benefits in applying the SMD are maintained

Row-shift corrected truncation of paraunitary matrices for PEVD algorithms

In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue decomposition (PEVD) of a parahermitian matrix are not unique. In particular, arbitrary shifts (delays) of polynomials in one row of a PU matrix yield another PU matrix that admits the same PEVD. To keep the order of such a PU matrix as low as possible, we pro- pose a row-shift correction. Using the example of an iterative PEVD algorithm with previously proposed truncation of the PU matrix, we demonstrate that a considerable shortening of the PU order can be accomplished when using row-corrected truncation

Impact of fast-converging PEVD algorithms on broadband AoA estimation

Polynomial matrix eigenvalue decomposition (PEVD) algorithms have been shown to enable a solution to the broadband angle of arrival (AoA) estimation problem. A parahermitian cross-spectral density (CSD) matrix can be generated from samples gathered by multiple array elements. The application of the PEVD to this CSD matrix leads to a paraunitary matrix which can be used within the spatio-spectral polynomial multiple signal classification (SSP-MUSIC) AoA estimation algorithm. Here, we demonstrate that the recent low-complexity divide-and-conquer sequential matrix diagonalisation (DC-SMD) algorithm, when paired with SSP-MUSIC, is able to provide superior AoA estimation versus traditional PEVD methods for the same algorithm execution time. We also provide results that quantify the performance trade-offs that DC-SMD offers for various algorithm parameters, and show that algorithm convergence speed can be increased at the expense of increased decomposition error and poorer AoA estimation performance

Complexity and search space reduction in cyclic-by-row PEVD algorithms

In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and uses paraunitary operations to diagonalise a parahermitian matrix. This paper addresses potential computational savings that can be applied to existing cyclic-by-row approaches for the PEVD. These savings are found during the search and rotation stages, and do not significantly impact on algorithm accuracy. We demonstrate that with the proposed techniques, computations can be significantly reduced. The benefits of this are important for a number of broadband multichannel problems

Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays

A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is an extension of the ordinary EVD to polynomial matrices and will diagonalise a parahermitian matrix using paraunitary operations. Inspired by recent work towards a low complexity divide-and-conquer PEVD algorithm, this paper analyses the performance of this algorithm - named divide-and-conquer sequential matrix diagonalisation (DC-SMD) - for applications involving broadband sensor arrays of various dimensionalities. We demonstrate that by using the DC-SMD algorithm instead of a traditional alternative, PEVD complexity and execution time can be significantly reduced. This reduction is shown to be especially impactful for broadband multichannel problems involving large arrays