QCD Factorization for Spin-Dependent Cross Sections in DIS and Drell-Yan Processes at Low Transverse Momentum

Based on a recent work on the quantum chromodynamic (QCD) factorization for semi-inclusive deep-inelastic scattering (DIS), we present a set of factorization formulas for the spin-dependent DIS and Drell-Yan cross sections at low transverse momentum.Comment: 12 pages, two figures include

Longitudinal/Goldstone boson equivalence and phenomenology of probing the electroweak symmetry breaking

We formulate the equivalence between the longitudinal weak-boson and the Goldstone boson as a criterion for sensitively probing the electroweak symmetry breaking mechanism and develop a precise power counting rule for chiral Lagrangian formulated electroweak theories. With these we semi-quatitatively analyze the sensitivities to various effective operators related to electrowaeak symmetry breaking via weak-boson scatterings at the CERN Large Hadron Collider (LHC).Comment: 6 pages, LaTex, 1 postscript figure included using psfig.te

Sensitivity of the LHC to Electroweak Symmetry Breaking: Equivalence Theorem as a Criterion

Based upon our recent study on the intrinsic connection between the longitudinal weak-boson scatterings and probing the electroweak symmetry breaking (EWSB) mechanism, we reveal the profound physical content of the Equivalence Theorem (ET) as being able to discriminate physical processes which are sensitive/insensitive to probing the EWSB sector. With this physical content of the ET as a criterion, we analyze the complete set of the bosonic operators in the electroweak chiral Lagrangian and systematically classify the sensitivities to probing all these operators at the CERN LHC via the weak-boson fusion in $W^\pm W^\pm$ channel. This is achieved by developing a precise power counting rule (a generalization from Weinberg's counting method) to {\it separately} count the power dependences on the energy $E$ and all relevant mass scales.Comment: 33 pages, LaTeX, 10 figures and Table-1b are in the separate file figtab.uu. (The only change made from the previous version is to fix the bugs in the uuencoded file.

Threshold Resummation for Higgs Production in Effective Field Theory

We present an effective field theory to resum the large double logarithms originated from soft-gluon radiations at small final-state hadron invariant masses in Higgs and vector boson (\gamma^*, $W$ and $Z$) production at hadron colliders. The approach is conceptually simple, indepaendent of details of an effective field theory formulation, and valid to all orders in sub-leading logarithms. As an example, we show the result of summing the next-to-next-to-next leading logarithms is identical to that of standard pQCD factorization method.Comment: A version to appear in Phys. Rev.

VLBI astrometry of two millisecond pulsars

We present astrometric results on two millisecond pulsars, PSR B1257+12 and PSR J1022+1001, as carried out through VLBI. For PSR B1257+12, a model-independent distance of $710_{\rm -38}^{\rm +43}$ pc and proper motion of ($\mu_{\rm \alpha}=46.44\pm0.08$ mas/yr, $\mu_{\rm \delta}=-84.87\pm0.32$ mas/yr) were obtained from 5 epochs of VLBA and 4 epochs of EVN observations, spanning about 2 years. The two dimensional proper motion of PSR J1022+1001 ($\mu_{\rm \alpha} \sim -10.13$ mas/yr, $\mu_{\delta} \sim 16.89$ mas/yr) was also estimated, using 3 epochs of EVN observations. Based on our results, the X-ray efficiency of PSR B1257+12 should be in the same range as other millisecond pulsars, and not as low as previously thought.Comment: Proceedings of IAUS 291 "Neutron Stars and Pulsars: Challenges and Opportunities after 80 years", J. van Leeuwen (ed.); 3 page

Building quantum neural networks based on swap test

Artificial neural network, consisting of many neurons in different layers, is an important method to simulate humain brain. Usually, one neuron has two operations: one is linear, the other is nonlinear. The linear operation is inner product and the nonlinear operation is represented by an activation function. In this work, we introduce a kind of quantum neuron whose inputs and outputs are quantum states. The inner product and activation operator of the quantum neurons can be realized by quantum circuits. Based on the quantum neuron, we propose a model of quantum neural network in which the weights between neurons are all quantum states. We also construct a quantum circuit to realize this quantum neural network model. A learning algorithm is proposed meanwhile. We show the validity of learning algorithm theoretically and demonstrate the potential of the quantum neural network numerically.Comment: 10 pages, 13 figure