A density-based clustering algorithm for the CYGNO data analysis

Abstract

Time Projection Chambers (TPCs) working in combination with Gas Electron Multipliers (GEMs) produce a very sensitive detector capable of observing low energy events. This is achieved by capturing photons generated during the GEM electron multiplication process by means of a high-resolution camera. The CYGNO experiment has recently developed a TPC Triple GEM detector coupled to a low noise and high spatial resolution CMOS sensor. For the image analysis, an algorithm 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 DBSCAN itself and a widely used algorithm known as Nearest Neighbor Clustering (NNC). The results show that the adapted version of DBSCAN is capable of providing full signal detection efficiency and very good energy resolution while improving the detector background rejection.

References in corpus (3)

• Direct observation of avalanche scintillations in a THGEM-based two-phase Ar avalanche detector using Geiger-mode APD
• Combined readout of a triple-GEM detector
• Performance of Optically Readout GEM-based TPC with a 55Fe source

Cited by in corpus (5)

• The CYGNO Experiment
• Identification of low energy nuclear recoils in a gas TPC with optical readout
• Performance of an optically read out time projection chamber with ultra-relativistic electrons
• Enhancing the light yield of He:CF${}_4$ based gaseous detector
• LIME -- a gas TPC prototype for directional Dark Matter search for the CYGNO experiment