The simulation was written in Python to check if the ratio between the E11 * and E11 intensities of defect (6,5)-SWCNTs is discrete. To achieve this, the code was written to identify and track the particles in two different fluorescence channels (E11 and E11 * ). All particle coordinates were identified with a python toolkit named trackpy (minmass = 2, everything else on default). As the coordinates refer to the middle point of SWCNTs, a 7x7 pixel section was selected to capture the whole SWCNT signal. Overlaying a 7x7 gaussian mask helped to exclude the background. So, for every SWCNT, its 7x7 intensity array was multiplied with the gaussian mask to calculate the sum of the array. This value was extracted for every SWCNT coordinate. The intensity of all particles was calculated, so that the ratio of E11 * /E11 for SWCNTs with different defect densities was calculated. The defect number (k) in the Poisson probability mass function was set between 1 and 10, as previous studies have shown only a low number of defects per nanotube .