A density-based clustering algorithm for the CYGNO data analysis

Time Projection Chambers (TPCs) working in combination with Gas ElectronMultipliers (GEMs) produce a very sensitive detector capable of observing lowenergy events. This is achieved by capturing photons generated during the GEMelectron multiplication process by means of a high-resolution camera. The CYGNOexperiment has recently developed a TPC Triple GEM detector coupled to a lownoise and high spatial resolution CMOS sensor. For the image analysis, analgorithm based on an adapted version of the well-known DBSCAN was implemented,called iDBSCAN. In this paper a description of the iDBSCAN algorithm is given,including test and validation of its parameters, and a comparison with DBSCANitself and a widely used algorithm known as Nearest Neighbor Clustering (NNC).The results show that the adapted version of DBSCAN is capable of providingfull signal detection efficiency and very good energy resolution whileimproving the detector background rejection.