Analysis code for SiPM tile tests and characterization for DarkSide. This code was used to analyze data taken in 2018, 2019 with the hardware setup to test SiPM response, and results were presented as my experimental project (Nov 2019).
Use SiPM_plot.py to plot the raw waveforms to see where the trigger peak is, and to check the noise levels. This is run with
python SiPM_plot.py
and it will output six pdf files of the first six raw waveforms.
read_txt.py and analyze_data.py are designed to analyse data from a SiPM tile, saved as a txt file with the amplitudes. The text file is expected to have headers with the record length, board ID, event number, pattern, trigger time stamp, and DC offset. The trigger time stamp is used to calculate the DCR (time difference between SiPM responses) and the record length is used to split into individual waveforms.
To run:
python read_txt.py wave4
python analyze_data.py wave4.pickle
read_txt.py will output a pickle file, that is then read into analyze_data.py to form a energy spectrum, with and without a convolution calculation.
read_txt.py calculates the average noise (start of the waveform), and uses a scanned integration window to calculate the max of the waveform for use in the energy calculation. By defining energy values around single photoelectron peaks, average waveforms for single, two, three, etc. photoelectrons are calculated. The single photoelectron peak is used as a template waveform for the convolution algorithm, with the output waveform saved in the pickle file. It also saves the timestamps of each waveform, which is used to calculate the DCR.
This is stored in /Users/gilliankopp/Documents/Princeton/Research/DarkSide/April2019Analysis. Data directory is now stores on backup drive, as the data files are rather large.