Jefferson Lab > CIO > IR
Privacy and Security Notice

Publications

Publication Information

Title Lattice QCD Calculations of Parton Physics
Authors Martha Constantinou,Luigi Del Debbio,Xiangdong Ji,Huey-Wen Lin,Kehfei Liu,Christopher Monahan,Kostas Orginos,Peter Petreczky,Jianwei Qiu,David Richards,Nobuo Sato Gonzalez,Phiala Shanahan,C.-P. Yuan,Jianhui Zhang,Yong Zhao
JLAB number JLAB-THY-22-3564
LANL number arXiv:2202.07193
Other number DOE/OR/23177-5427, MIT-CTP/5408, MSUHEP-22-004
Document Type(s) (Journal Article) 
Associated with EIC: No
Supported by Jefferson Lab LDRD Funding: No
Funding Source: Nuclear Physics (NP)
 

Journal
Compiled for arXiv
Publication Abstract: In this document, we summarize the status and challenges of calculating parton physics in lattice QCD for the US Particle Physics Community Planning Exercise (a.k.a. 'SSnowmass'). While PDF- moments calculations have been very successful and been continuously improved, new methods have been developed to calculate distributions directly in x-space. Many recent lattice studies have been focused on calculating isovector PDFs of the pion and nucleon, learning to control systematics asso- ciated with excited-state contamination, renormalization and continuum extrapolations, pion-mass and finite-volume effects, etc. Although in some cases, the lattice results are already competitive with experimental data, to reach the level of precision in a wide range of x for unpolarized nucleon PDFs impactful for future collider physics remains a challenge, and may require exascale supercom- puting power. The new theoretical methods open the door for calculating other partonic observables which will be the focus of the experimental program in nuclear physics, including generalized parton distributions and transverse-momentum dependent PDFs. A fruitful interplay between experimental data and lattice-QCD calculations will usher in a new era for parton physics and hadron structure.
Experiment Numbers:
Group: THEORY CENTER
Document: pdf
DOI:
Accepted Manuscript:
Supporting Documents:
Supporting Datasets: