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Study of damped oscillating structures from charged and neutral K-meson electromagnetic form factors data (2309.05354v1)

Published 11 Sep 2023 in hep-ph

Abstract: The damped oscillating structures (OS) were recently revealed in the proton "effective" form factor (FF) data. For the time being they can be neither confirmed nor disproved by investigations of timelike data on the individual proton electric and proton magnetic FFs because their precision and reliability (especially of the proton electric FF data) has not achieved required level for this aim. On the other hand, conjectures that the OS are direct manifestations of the quark-gluon structure of the proton indicate that they must not be specific only for the proton and neutron, but that they should be present also for other hadrons. This opens a plausibility to find damped oscillatory structures also from the EM FFs data of such hadrons, for which adequate EM FFs data exist, by using the same procedure as for the proton. Consequently in this paper damped oscillatory structures are investigated in the EM FFs data of the charged and neutral $K$-mesons to be extracted from the corresponding production cross sections, $\sigma{bare}_{tot}(e+e-\to K+ K-)$ measured from the threshold up to 64 GeV$2$ and $\sigma{bare}_{tot}(e+e-\to K_s K_L)$ measured from the threshold up to 9.5 GeV$2$ of the total c.m. energy squared. The following results have been obtained. If the charged and neutral K-meson EM FFs timelike data are described by the three parametric formula by means of which OS have been revealed from the "effective" proton FF data then OS appear. If physically well founded Unitary and Analytic model of the K-meson EM structure is used for a description of the charged K-meson EM FFs data, no OS are visible. However, in the case of the neutral K-meson EM FF data one cannot make a definite decision. The overall results indicate that OS obtained from the "effective" proton FF data are likely an artefact of the three parametric formula which does not describe these data well.

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