71,937 research outputs found

    An Evolutionary Approach to the Design of Controllable Cellular Automata Structure for Random Number Generation

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    Cellular Automata (CA) has been used in pseudorandom number generation over a decade. Recent studies show that two-dimensional (2-d) CA Pseudorandom Number Generators (PRNGs) may generate better random sequences than conventional one-dimensional (1-d) CA PRNGs, but they are more complex to implement in hardware than 1-d CA PRNGs. In this paper, we propose a new class of 1-d CA Controllable Cellular Automata (CCA) without much deviation from the structure simplicity of conventional 1-d CA. We give a general definition of CCA first and then introduce two types of CCA – CCA0 and CCA2. Our initial study on them shows that these two CCA PRNGs have better randomness quality than conventional 1-d CA PRNGs but their randomness is affected by their structures. To find good CCA0/CCA2 structures for pseudorandom number generation, we evolve them using the Evolutionary Multi-Objective Optimization (EMOO) techniques. Three different algorithms are presented in this paper. One makes use of an aggregation function; the other two are based on the Vector Evaluated Genetic Algorithm (VEGA). Evolution results show that these three algorithms all perform well. Applying a set of randomness tests on the evolved CCA PRNGs, we demonstrate that their randomness is better than that of 1-d CA PRNGs and can be comparable to that of two-dimensional CA PRNGs

    Incremental evolution of cellular automata for random number generation

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    Cellular automata (CA) have been used in pseudorandom number generation for over a decade. Recent studies show that controllable CA (CCA) can generate better random sequences than conventional one-dimensional (1-d) CA and compete with two-dimensional (2-d) CA. Yet the structural complexity of CCA is higher than that of 1-d PCA. It would be good if CCA can attain good randomness quality with the least structural complexity. In this paper, we evolve PCA/CCA to their lowest complexity level using genetic algorithms (GAs). Meanwhile, the randomness quality and output efficiency of PCA/CCA are also evolved. The evolution process involves two algorithms a multi-objective genetic algorithm (MOGA) and an algorithm for incremental evolution. A set of PCA/CCA are evolved and compared in randomness, complexity, and efficiency. The results show that without any spacing, CCA could generate good random number sequences that could pass DIEHARD. And, to obtain the same randomness quality, the structural complexity of CCA is not higher than that of 1-d CA. Furthermore, the methodology developed could be used to evolve other CA or serve as a yardstick to compare different types of CA

    B-Physics Observables and Electroweak Precision Data in the CMSSM, mGMSB and mAMSB

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    We explore electroweak precision observables (EWPO) and BB-physics observables (BPO) in the CMSSM, the mGMSB and the mAMSB. We perform a chi^2 analysis based on the combination of current EWPO and BPO data. For the first time this allows the comparison of the mGMSB and mAMSB in terms of EWPO and BPO with the CMSSM. We find that relatively low mass scales in all three scenarios are favored. However, the current data from EWPO and BPO can hardly exclude any parameters at the level of Delta chi^2 = 9. Remarkably the mAMSB scenario, despite having one free GUT scale parameter less than the other two scenarios, has a somewhat lower total minimum chi^2. We present predictions for the lightest Higgs boson mass, based on the chi^2 analysis of current data, where relatively good compatibility with the bounds from Higgs searches at LEP is found. We also present the predictions for other Higgs sector parameters and SUSY mass scales, allowing to compare the reach of the LHC and the ILC in the three scenarios. We furthermore explore the future sensitivities of the EWPO and BPO for the current best-fit results and for a hypothetical point with somewhat higher mass scales that results in a similar Higgs and SUSY spectrum in the three scenarios. We find that the future improvement of the accuracy of the EWPO and BPO will lead to a significant gain in the indirect parameter determination. The improvement is similar in the CMSSM, mGMSB and mAMSB and will yield constraints to the parameter space even for heavy Higgs and SUSY mass scales.Comment: 53 pages, 27 figures, discussion extended. Version to appear in JHE

    Spin Current and Current-Induced Spin Transfer Torque in Ferromagnet-Quantum Dot-Ferromagnet Coupled Systems

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    Based on Keldysh's nonequilibrium Green function method, the spin-dependent transport properties in a ferromagnet-quantum dot (QD)-ferromagnet coupled system are investigated. It is shown the spin current shows quite different characteristics from its electrical counterpart, and by changing the relative orientation of both magnetizations, it can change its magnitude even sign. The current-induced spin transfer torque (CISTT) is uncovered to be greatly enhanced when the bias voltage meets with the discrete levels of the QD at resonant positions. The relationship between the CISTT, the electrical current and the spin current is also addressed.Comment: 21 pages, 8 figure

    Low Energy Precision Test of Supersymmetry

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    Supersymmetry (SUSY) remains one of the leading candidates for physics beyond the Standard Model, and the search for SUSY will be a central focus of future collider experiments. Complementary information on the viability and character of SUSY can be obtained via the analysis of precision electroweak measurements. In this review, we discuss the prospective implications for SUSY of present and future precision studies at low energy.Comment: 118 pages, review pape
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