RN-NOP-2018-004

The PANDA experiment is one of the main pillars of the FAIR facility, currently under construction in Darmstadt, Germany. The PANDA will be a fixed target experiment designed for the study of non-perturbative phenomena of the strong interaction. Strange hyperon production is governed by the mass of the strange quark, m(s) ∼ 100 MeV, which corresponds to the confinement domain. Thus, hyperons are suitable probes in this energy region. This work is a simulation study focused on the feasibility of studying the production of the Sigmabar and Lambda hyperons in the pbar p ->Sigmabar Lambda reaction with the PANDA detector. A 10^4 events sample simulated at pbeam = 1.771 GeV/c is used to perform a single-tag (inclusive) and a double-tag (exclusive) event selection. From the former, it is concluded that the single-tag method does not provide with the clean signal required for spin observables extraction. In contrast, exclusive event selection provides with a signal reasonably clean from combinatorial background and completely clean from generic hadronic background events. A signal ( Sigmabar Lambda) reconstruction efficiency of e = 5.3 ± 0.2 % is obtained for exclusive event selection. The corresponding signal to background ratio is S/B Total ∼ 6 and the significance value
is ∼ 21.
In addition, an exclusive event selection is performed on a 10^4 events sample simulated at pbeam = 6 GeV/c. Almost all the generic hadronic background events are removed by the applied selection criteria. At this beam momentum, the obtained signal efficiency is e = 6.1 ± 0.3%, the signal to total background ratio is S/B Total ∼ 4 and the significance is ∼ 22. Both efficiencies are smaller compared to a previous simulation study on this channel, but are large enough to enable a study of the exclusive production of the pbar p -> Sigmabar Lambda reaction at PANDA. The difference between the results of this work and the previous work is attributed to the more realistic implementation of the signal production mechanism, as well as the detector and reconstruction algorithms.