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arXiv 2401.07933hep-phnucl-th
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光前夸克模型中的重介子结构

Structure of Heavy Mesons in the Light-Front Quark Model

RIKEN Nishina Center(理化学研究所西村中心);Osaka University(大阪大学);Yokohama City University(横滨市立大学);Japan Atomic Energy Agency(日本原子力机构)

Ahmad Jafar Arifi, Lucas Happ, Shuhei Ohno, Makoto Oka

AI总结:

本研究在光前夸克模型中对比单高斯假设与高斯展开法对重介子结构的描述,发现高斯展开法能更准确重现分布振幅渐近行为、波函数幂律阻尼等结构性质,更符合微扰QCD预言。

摘要:

我们在光前夸克模型框架下研究基态重介子的结构,采用由单高斯假设(Single Gaussian Ansatz, SGA)和高斯展开法(Gaussian Expansion Method, GEM)得到的波函数。通过对质谱、衰变常数等静态性质进行χ²拟合,我们确定了两种方法各自的模型参数,随后对比了两种方法对光前波函数及结构可观测量的影响。分析表明,两者的分布振幅(distribution amplitudes, DAs)ϕ_{2;M}(x)在端点附近存在显著差异:GEM的振幅更高,且具备正确的渐近行为ϕ_{2;M}(x→1)∝(1-x),与微扰QCD一致。该端点行为与由色库仑相互作用和相对论运动学主导的短程(高动量)波函数相关。GEM准确重现了幂律阻尼ψ₀(k→∞)∝1/k_⊥²,符合微扰QCD的预言。此外,低Q²区域赝标介子的电磁形状因子在GEM下的衰减速度快于SGA。总体而言,尽管两种方法都能恰当描述静态性质,但GEM对细节和渐近行为更敏感,能更准确地描述结构性质。

英文摘要:

We investigate the structure of ground-state heavy mesons within the light-front quark model, utilizing wave functions derived from the Single Gaussian Ansatz (SGA) and the Gaussian Expansion Method (GEM). By performing a $χ^2$ fit to static properties such as mass spectra and decay constants, we determine the model parameters for each approach. We then compare the impacts of both methods on the light-front wave functions and structural observables. Our analysis reveals significant differences in the distribution amplitudes (DAs) $ϕ_{2;M}(x)$ near the endpoints, with GEM showing enhanced amplitudes and correct asymptotic behavior $ϕ_{2;M}(x \to 1) \propto (1-x)$, consistent with perturbative QCD. This endpoint behavior is linked to the short-range (high-momentum) wave function governed by color Coulomb interaction and relativistic kinematics. GEM accurately reproduces a power-law damping $ψ_0(k \to \infty) \propto 1/k_\perp^2$, aligning with perturbative QCD predictions. Furthermore, the electromagnetic form factors of pseudoscalar mesons in the low-$Q^2$ region fall off faster with GEM than with SGA. Overall, while both methods adequately describe static properties, GEM provides a more accurate description of structural properties, being more sensitive to details and asymptotic behaviors.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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