6,731 research outputs found

    Maximal Entanglement of Two-qubit States Constructed by Linearly Independent Coherent States

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    In this paper, we find the necessary and sufficient condition for the maximal entanglement of the state, ψ>=μα>β>+λα>δ>+ργ>β>+νγ>δ>, |\psi>=\mu|\alpha>|\beta>+\lambda|\alpha>|\delta>+ \rho|\gamma>|\beta>+\nu|\gamma>|\delta>, constructed by linearly independent coherent states with \emph{real parameters} when ==. This is a further generalization of the classified nonorthogonal states discussed in Ref. Physics Letters A {\bf{291}}, 73-76 (2001).Comment: some examples added; Int J Theor Phys 201

    Mechanical behavior of irregular fibers part III : the flexural buckling behavior

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    Fiber buckling behavior is associated with fabric-evoked prickle, which affects clothing comfort and aesthetics. In this paper, the flexural buckling behavior of irregular or nonuniform fibers is studied using the finite element method (FEM). Fiber dimensional irregularities are simulated with sine waves of different magnitude, frequency, and initial phase. The critical buckling loads of the simulated fibers are then calculated from the FE model. The results indicate that increasing the level of irregularity will decrease the critical buckling load of fibers, but the effect of the frequency and initial phase of irregularity on fiber buckling behavior is complicated and is affected by fiber diameter and effective length

    Quasi-optical gyrotron with arbitrary beam injection angle

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    Probability Analysis of Pit Initiation on Austenitic Stainless Steels

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    AbstractThe influence and mechanism of microscopic pit initiation on austenitic stainless steels were analyzed. Based on the electrochemical theory, a model was proposed to judge the pit initiation on austenitic stainless steels in the weak acidic chloride solution. Although the model was developed based on deterministic equations, it can be used to analyze the randomness of pit initiation. Furthermore the probability distribution of major parameters was also discussed. This study enriches the stochastic theory of pit initiation

    Manganese coordination chemistry of bis(imino)phenoxide derived [2 + 2] Schiff-base macrocyclic ligands

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    The [2 + 2] Schiff base macrocycles [2,2'-(CH₂CH₂)(C₆H₄N)₂-2,6-(4-RC₆H₃OH)]₂ (IʳH₂), upon reaction with MnCl₂ (two equivalents) afforded the bimetallic complex [Cl₃Mn(NCMe)][MnCl(IᵗᵇᵘH₂)] (2). Under similar conditions, use of the related [2 + 2] oxy-bridged macrocycle [2,2'-O(C₆H₄N=CH)₂4-RC₆H₃OH] (IIʳH₂), afforded the bimetallic complexes [(MnCl)₂IIʳ] (R = Me 3, tBu 4), whilst the macrocycle derived from 1,2-diaminobenzene and 5,5'-di-tert-butyl-2,2'-dihydroxy-3,3'-methylenedibenzaldehyde (IIIH₄) afforded the complex [(MnCl)₂(III)]·2MeCN (5·2MeCN). For comparative studies, the salt complexes [2,6-(ArNHCH)₂-4-MeC₆H₂O][MnCl₃(NCMe)] (Ar = 2,4-Me₂C₆H₃, 6) and {[2,6-(ArNHCH)₂-4-MeC₆H₂O][MnCl}₂[MnCl₄]·8CH₂Cl₂ (Ar = 4-MeC₆H₄, 7·8CH₂Cl₂) were prepared. The crystal structures of 1 - 7 are reported (synchrotron radiation was necessary for complexes 1, 3 and 5). Complexes 1 - 7 (not 5) were screened for their potential to act as pre-catalysts for the ring opening polymerization (ROP) of ε-caprolactone; 3, 4 and 6, 7 were inactive, whilst 1 and 2 exhibited only poor activity low conversion (<15 %) at temperatures above 60 °C

    LSGAN-AT: enhancing malware detector robustness against adversarial examples

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    Adversarial Malware Example (AME)-based adversarial training can effectively enhance the robustness of Machine Learning (ML)-based malware detectors against AME. AME quality is a key factor to the robustness enhancement. Generative Adversarial Network (GAN) is a kind of AME generation method, but the existing GAN-based AME generation methods have the issues of inadequate optimization, mode collapse and training instability. In this paper, we propose a novel approach (denote as LSGAN-AT) to enhance ML-based malware detector robustness against Adversarial Examples, which includes LSGAN module and AT module. LSGAN module can generate more effective and smoother AME by utilizing brand-new network structures and Least Square (LS) loss to optimize boundary samples. AT module makes adversarial training using AME generated by LSGAN to generate ML-based Robust Malware Detector (RMD). Extensive experiment results validate the better transferability of AME in terms of attacking 6 ML detectors and the RMD transferability in terms of resisting the MalGAN black-box attack. The results also verify the performance of the generated RMD in the recognition rate of AME. © 2021, The Author(s)

    Crossing Statistic: Bayesian interpretation, model selection and resolving dark energy parametrization problem

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    By introducing Crossing functions and hyper-parameters I show that the Bayesian interpretation of the Crossing Statistics [1] can be used trivially for the purpose of model selection among cosmological models. In this approach to falsify a cosmological model there is no need to compare it with other models or assume any particular form of parametrization for the cosmological quantities like luminosity distance, Hubble parameter or equation of state of dark energy. Instead, hyper-parameters of Crossing functions perform as discriminators between correct and wrong models. Using this approach one can falsify any assumed cosmological model without putting priors on the underlying actual model of the universe and its parameters, hence the issue of dark energy parametrization is resolved. It will be also shown that the sensitivity of the method to the intrinsic dispersion of the data is small that is another important characteristic of the method in testing cosmological models dealing with data with high uncertainties.Comment: 14 pages, 4 figures, discussions extended, 1 figure and two references added, main results unchanged, matches the final version to be published in JCA

    Nature of Correlated Motion of Electrons in the Parent Cobaltate Superconductors

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    Recently discovered class of cobaltate superconductors (Na0.3CoO2.nH2O) is a novel realization of interacting quantum electron systems in a triangular network with low-energy degrees of freedom. We employ angle-resolved photoemission spectroscopy to uncover the nature of microscopic electron motion in the parent superconductors for the first time. Results reveal a large hole-like Fermi surface (consistent with Luttinger theorem) generated by the crossing of super-heavy quasiparticles. The measured quasiparticle parameters collectively suggest a two orders of magnitude departure from the conventional Bardeen-Cooper-Schrieffer electron dynamics paradigm and unveils cobaltates as a rather hidden class of relatively high temperature superconductors.Comment: 5 pages, 4 figures, 1 tabl

    Superconductivity in MgB_2 doped with Ti and C

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    Measurements of the superconducting upper critical field, H_{c2}, and critical current density, J_c, have been carried out for MgB_2 doped with Ti and/or C in order to explore the problems encountered if these dopants are used to enhance the superconducting performance. Carbon replaces boron in the MgB_2 lattice and apparently shortens the electronic mean free path thereby raising H_c2. Titanium forms precipitates of either TiB or TiB_2 that enhance the flux pinning and raise J_c. Most of these precipitates are intra-granular in the MgB_2 phase. If approximately 0.5% Ti and approximately 2% C are co-deposited with B to form doped boron fibers and these fibers are in turn reacted in Mg vapor to form MgB_2, the resulting superconductor has H_{c2}(T=0) ~ 25 T and J_c ~ 10,000 A/cm**2 at 5 K and 2.2 T.Comment: 11 pages, 10 figure
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