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Title Insights into the Emergence of Mass from Studies of Pion and Kaon Structure
Authors Craig Roberts, David Richards, Tanja Horn, Lei Chang
JLAB number JLAB-THY-21-3309
LANL number arXiv:2102.01765
Other number DOE/OR/23177-5112
Document Type(s) (Journal Article) 
Associated with EIC: No
Supported by Jefferson Lab LDRD Funding: No
Funding Source: Nuclear Physics (NP)
 

Journal
Compiled for Progress in Particle and Nuclear Physics
Volume 120
Page(s) 103883
Refereed
Publication Abstract: There are two mass generating mechanisms in the standard model of particle physics (SM). One is related to the Higgs boson and fairly well understood. The other is embedded in quantum chromodynamics (QCD), the SM's strong interaction piece; and although responsible for emergence of the roughly 1 GeV mass scale that characterises the proton and hence all observable matter, the source and impacts of this emergent hadronic mass (EHM) remain puzzling. As bound states seeded by a valence-quark and -antiquark, pseudoscalar mesons present a simpler problem in quantum field theory than that associated with the nucleon. Consequently, there is a large array of robust predictions for pion and kaon properties whose empirical validation will provide a clear window onto many effects of both mass generating mechanisms and the constructive interference between them. This has now become significant because new-era experimental facilities, in operation, construction, or planning, are capable of conducting such tests and thereby contributing greatly to resolving the puzzles of EHM. These aspects of experiment, phenomenology, and theory, along with contemporary successes and challenges, are sketched herein, simultaneously highlighting the potential gains that can accrue from a coherent effort aimed at finally reaching an understanding of the character and structure of Nature's Nambu-Goldstone modes.
Experiment Numbers:
Group: THEORY CENTER
Document: pdf
DOI: https://doi.org/10.1016/j.ppnp.2021.103883
Accepted Manuscript: 2102.01765.pdf
Supporting Documents:
Supporting Datasets: