Speaker
Description
In this study, we present an exclusive analysis of the \textit{pp} $\to$ \textit{ppKK} reaction with data collected by the HADES detector during February 2022. In the course of this analysis, we developed a neural network-based particle identification procedure (PID), which compensates for the differences between simulation and experiment via a domain adversarial technique. We efficiently suppress background by means of kinematic refit with a 4C constraint, corresponding to the conservation of 4-momentum.
We observed clear signals from $\phi(1020) \to KK$ and $\Lambda(1520) \to pK$ with their parameters consistent with PDG data within one standard deviation. However, the formation of $p\phi$ intermediate state doesn't seem to happen. This talk will present the details of our event selection procedures, efficiency corrections and prospects for further understanding of the reaction mechanism
