On the Lognormal Law of Ionization Energy Loss in the TPC Detector of the MPD/NICA Experiment

Based on Monte Carlo simulation data of heavy-ion collisions, it is shown for the first time for the time projection chamber (TPC) of the MPD/NICA experiment that the distribution of ionization energy loss (signal) follows a log-normal law, both at the general sample level and at the level of individual tracks. The discovered property is physically justified due to the multiplicative nature of fluctuation accumulation in the process of charged particle registration. Based on this observation, a new approach to particle identification is proposed, utilizing a set of statistical parameters of the track signal distribution instead of the conventional mean value. Using machine learning methods, an optimal set of track parameters is obtained, providing a 10% improvement in identification quality compared to the conventional method. The results obtained can be used to improve track reconstruction and calibration algorithms for the TPC detector in the MPD experiment.