One-loop matching for transversity generalized parton distribution

Recent developments showed that light cone parton distributions can be studied by investigating the large momentum limit of the so-called quasiparton distributions, which are defined in terms of spacelike correlators, and therefore can be readily computed on the lattice. These two distributions can be connected to each other by a perturbative factorization formula or matching condition that allows one to convert the latter into the former. Here we present the one-loop matching condition for the transversity generalized quark distribution in the nonsinglet cas

QCD corrections to double J/\psi production in e+e- annihilation at \sqrt{s}=10.6 GeV

Next-to-Leading-Order(NLO) QCD corrections to double J/psi production in e^+e^- annihilation at sqrt{s}=10.6 GeV are calculated. We find that they greatly decrease the cross section, with a K factor (NLO/LO) ranging from -0.31 to 0.25 depending on the renormalization scale. Although the renormalization scale dependence indicates a large uncertainty, when combined with the NLO QCD corrections to J/psi + eta_c production, it can explain why the double J/psi$ production could not be found at B factories while the J/psi + eta_c production could, despite the fact that cross section of the former is larger than that of the latter at LO by a factor of 1.8.Comment: 4 pages, 4 figures, use revtex

QCD corrections to J/psi plus eta_c production in e+e- annihilation at sqrt{s}=10.6 GeV

Next-to-Leading-Order(NLO) QCD corrections to J/jpsi plus eta_c production in e+e- annihilation at sqrt{s}=10.6 GeV is calculated in this paper, and an analytic result is obtained. By choosing proper physical parameters, a K factor (ratio of NLO to LO) of about 2, which is in agreement with the result in Ref.\cite{Zhang:2005ch}, is obtained. Our results show that the Next-Next-to-Leading-Order(NNLO) corrections might be quite large. The plot of the K-factor vs the center-of-mass energy sqrt{s} shows that it is more difficult to obtain a convergent result from the perturbative QCD without resummation of ln(s/m_c) terms as the sqrt{s} becomes larger.Comment: 8 pages, 6 figures, two column

Next-to-Leading-Order study on the associate production of J/ψ+γJ/\psi+\gamma at the LHC

The associate $J/\psi+\gamma$ production at the LHC is studied completely at next-to-leading-order (NLO) within the framework of nonrelativistic QCD. By using three sets of color-octet long-distance matrix elements (LDMEs) obtained in previous prompt $J/\psi$ studies, we find that only one of them can result in a positive transverse momentum ($p_t$) distribution of $J/\psi$ production rate at large $p_t$ region. Based on reasonable consideration to cut down background, our estimation is measurable upto $p_t=50$GeV with present data sample collected at $8$TeV LHC. All the color-octet LDMEs in $J/\psi$ production could be fixed sensitively by including this proposed measurement and our calculation, and then confident conclusion on $J/\psi$ polarization puzzle could be achieved.Comment: 5 pages, 2 figure

Venture Capitalists and Patent Applications of Start-up Firms

In this thesis, the effects of ownership structure on the patent applications of start-up firms are examined, focusing particularly on the role of VC. A unique dataset of Japanese start-up firms is used in the analysis, controlling for firm and industry characteristics. We find that shareholding by VC has a positively significant impact on patent applications and VC is supposed to have an increasing effect on patent applications of the firms brought by R&D expenditures.Patent Applications, R&D expenditures, Venture capitalists, Shareholding, Start-up Firms

Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing

Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and inter-spatial correlations. Therefore, in this letter, we use low rank matrix completion theory to explore the inter-spatial correlation and use compressive sensing theory to take advantage of intra-temporal correlation. Our method, dubbed MCCS, can significantly reduce the amount of data that each sensor must send through network and to the sink, thus prolong the lifetime of the whole networks. Experiments using real datasets demonstrate the feasibility and efficacy of our MCCS method