Publications
Publication Information
| Title | Predictive power of transverse-momentum-dependent distributions |
| Authors | Andrea Signori, Jianwei Qiu, Zhongbo Kang, Manvir Grewal |
| JLAB number | JLAB-THY-20-3159 |
| LANL number | arXiv:2003.07453 |
| Other number | DOE/OR/23177-4938 |
| Document Type(s) | (Journal Article) |
| Associated with EIC: | No |
| Supported by Jefferson Lab LDRD Funding: | No |
| Funding Source: | Nuclear Physics (NP) |
| Other Funding: | National Science Foundation Grant No. PHY-1720486 European commission - MSCA Grant No. 795475 DOE Topical TMD collaboration |
|
Journal Compiled for Physical Review D Volume 101 Issue 11 Refereed | |
| Publication Abstract: | We investigate the predictive power of transverse-momentum-dependent (TMD) distributions as a function of the light-cone momentum fraction $x$ and the hard scale $Q$ defined by the process. We apply the saddle point approximation to the unpolarized quark and gluon transverse momentum distributions and evaluate the position of the saddle point as a function of the kinematics. We determine quantitatively that the predictive power for an unpolarized transverse momentum distribution is maximal in the large-$Q$ and small-$x$ region. For cross sections the predictive power of the TMD factorization formalism is generally enhanced by considering the convolution of two distributions, and we explicitly consider the case of $Z$ and $H^0$ boson production. In the kinematic regions where the predictive power is not maximal, the distributions are sensitive to the non-perturbative hadron structure. Thus, these regions are critical for investigating hadron tomography in a three-dimensional momentum space. |
| Experiment Numbers: | other |
| Group: | THEORY CENTER |
| Document: | |
| DOI: | https://doi.org/10.1103/PhysRevD.101.114023 |
| Accepted Manuscript: | PhysRevD.101.114023.pdf |
| Supporting Documents: | |
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