Browsing by Author "Cao F-G"

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    Radial excitation of light mesons and the γγ* → π0 transition form factor
    (American Physical Society, 2021-09-22) Cao F-G
    We investigate radial excitation of the quark-antiquark pair in the π0 meson and its effects on the γγ* → π0 transition form factor in the framework of light cone perturbative QCD. The existing constraints on the light cone wave function of the lowest Fock state Iqq¯〉 in the π0 meson allow a sizeable radial excitation of the quark-antiquark pair. We construct the light cone wave function for the quark-antiquark pair in the first radially excited state (the 2S state) using a simple harmonic oscillator potential. The distribution amplitude obtained for the 2S state has two nodes in x at low scale of Q and thereby has a much strong scale dependence than the 1S state. Contributions from this radial excitation to the γγ* → π0 transition form factor exhibit different Q2-dependence behavior from the ground state and thus can modify the prediction for the transition form factor in the medium-large region of Q2.
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    Transverse momentum and transverse momentum distributions in the MIT bag model
    (Elsevier, 10/03/2022) Signal A; Cao F-G
    The typical transverse momentum of a quark in the proton is a basic property of any QCD based model of nucleon structure. However, calculations in phenomenological models typically give rather small values of transverse momenta, which are difficult to reconcile with the larger values observed in high energy experiments such as Drell-Yan reactions and Semi-inclusive deep inelastic scattering. In this letter we calculate the leading twist transverse momentum dependent distribution functions (TMDs) using a generalization of the Adelaide group’s relativistic formalism that has previously given good fits to the parton distributions. This enables us to examine the kT dependence of the TMDs in detail, and determine typical widths of these distributions. These are found to be significantly larger than those of previous calculations. We then use TMD factorization in order to evolve these distributions up to experimental scales where we can compare with data on 〈kT 〉 and 〈k2 T 〉. Our distributions agree well with this data.