Development of software tools for optimizing the operation of gaseous detectors and gas systems

This report presents the implementation of signal processing algorithms to study eco-friendly gas mixtures. Key contributions include the implementation of peak detection algorithms, with preliminary insights indicating a negative correlation between the charge of peaks produced and HFO concentrations. The Pandas library remains the preferred data analysis tool for studies of gas mixtures. Finally, the mean over the baseline region was identified as the most effective method for baseline estimation under background radiation conditions, balancing computational efficiency and performance.